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Kickstarter project has finally given us a Juicero for the robotics era, and it’s called E.G.O.R. (that’s Efficient Gastronomic Operational Robot), brought to you by the startup Cheffy. It’s an automated egg maker that promises perfect cracks every time with no shell in the yolk. It has seven different ways that it can cook them up for you, or you can just use it to do the cracking. You can also pair it with a toaster so your eggs and toast finish at the exact right time.

This isn’t something anyone really needs. Cooking an egg over easy takes about two minutes, so calling this a time-saver is a stretch. And if you really don’t want to use the stove, you can buy a basic egg cooker for around $20 almost anywhere. Maybe you’re bad at cracking eggs, but $400 (well, $200 if you get in on the early bird deal) is a lot to pay to not have to pick the occasional shell pieces out.

But hey, the robotics era needed its Juicero moment. To the creator’s credit: it seems like they’re treating this more like a fun novelty (albeit a pretty pricey one) rather than something revolutionary. They also aren’t making you buy proprietary eggs that are required to make the machine work, so they’ve got the Juicero bros beat there.

We’re increasingly seeing robots positioned to do basic tasks. A company called Weave got attention earlier this year with an $8,000 robot that folds clothes. There’s a company in San Francisco offering house cleanings performed by humanoid robots. Last year, 1x made waves by introducing its Neo humanoid robot, which the Wall Street Journal reported “nearly toppled over” while closing a dishwasher and struggled to open the refrigerator.

All of these machines cost an inordinate amount of money to do things that do not cost the average person that much time or money to accomplish. They’re novel, sure. But you don’t have to pay a premium to be a beta tester.

#Robot #Revolution #Juiceroartifical intelligence,automation,Robotics"> The Robot Revolution Gets Its Own Juicero The price of eggs has become a marker of the state of the economy. But how about the cost of making eggs? Sure, you might be able to do it for next to nothing in your kitchen with nothing but a pan and a burner. But you could also pay 0 for a robot that will do it for you—as long as you don’t want your eggs scrambled, that is. A new Kickstarter project has finally given us a Juicero for the robotics era, and it’s called E.G.O.R. (that’s Efficient Gastronomic Operational Robot), brought to you by the startup Cheffy. It’s an automated egg maker that promises perfect cracks every time with no shell in the yolk. It has seven different ways that it can cook them up for you, or you can just use it to do the cracking. You can also pair it with a toaster so your eggs and toast finish at the exact right time. NEW: Cheffy just launched a robot that cracks and cooks your eggs. Egor automates breakfast by cooking eggs 7 ways, while Toastr syncs your toast so everything finishes together. -Automatically cracks eggs with no shells or mess-Cooks eggs 7 ways, from sunny-side up to hard… pic.twitter.com/auE3SnfrS3 — Ritwik Pavan (@ritwikpavan) July 30, 2026 This isn’t something anyone really needs. Cooking an egg over easy takes about two minutes, so calling this a time-saver is a stretch. And if you really don’t want to use the stove, you can buy a basic egg cooker for around almost anywhere. Maybe you’re bad at cracking eggs, but 0 (well, 0 if you get in on the early bird deal) is a lot to pay to not have to pick the occasional shell pieces out. But hey, the robotics era needed its Juicero moment. To the creator’s credit: it seems like they’re treating this more like a fun novelty (albeit a pretty pricey one) rather than something revolutionary. They also aren’t making you buy proprietary eggs that are required to make the machine work, so they’ve got the Juicero bros beat there. We’re increasingly seeing robots positioned to do basic tasks. A company called Weave got attention earlier this year with an ,000 robot that folds clothes. There’s a company in San Francisco offering house cleanings performed by humanoid robots. Last year, 1x made waves by introducing its Neo humanoid robot, which the Wall Street Journal reported “nearly toppled over” while closing a dishwasher and struggled to open the refrigerator. All of these machines cost an inordinate amount of money to do things that do not cost the average person that much time or money to accomplish. They’re novel, sure. But you don’t have to pay a premium to be a beta tester. #Robot #Revolution #Juiceroartifical intelligence,automation,Robotics
Tech-news

Kickstarter project has finally given us a Juicero for the robotics era, and it’s called E.G.O.R. (that’s Efficient Gastronomic Operational Robot), brought to you by the startup Cheffy. It’s an automated egg maker that promises perfect cracks every time with no shell in the yolk. It has seven different ways that it can cook them up for you, or you can just use it to do the cracking. You can also pair it with a toaster so your eggs and toast finish at the exact right time.

This isn’t something anyone really needs. Cooking an egg over easy takes about two minutes, so calling this a time-saver is a stretch. And if you really don’t want to use the stove, you can buy a basic egg cooker for around $20 almost anywhere. Maybe you’re bad at cracking eggs, but $400 (well, $200 if you get in on the early bird deal) is a lot to pay to not have to pick the occasional shell pieces out.

But hey, the robotics era needed its Juicero moment. To the creator’s credit: it seems like they’re treating this more like a fun novelty (albeit a pretty pricey one) rather than something revolutionary. They also aren’t making you buy proprietary eggs that are required to make the machine work, so they’ve got the Juicero bros beat there.

We’re increasingly seeing robots positioned to do basic tasks. A company called Weave got attention earlier this year with an $8,000 robot that folds clothes. There’s a company in San Francisco offering house cleanings performed by humanoid robots. Last year, 1x made waves by introducing its Neo humanoid robot, which the Wall Street Journal reported “nearly toppled over” while closing a dishwasher and struggled to open the refrigerator.

All of these machines cost an inordinate amount of money to do things that do not cost the average person that much time or money to accomplish. They’re novel, sure. But you don’t have to pay a premium to be a beta tester.

#Robot #Revolution #Juiceroartifical intelligence,automation,Robotics">The Robot Revolution Gets Its Own JuiceroThe Robot Revolution Gets Its Own Juicero The price of eggs has become a marker of the state of the economy. But how about the cost of making eggs? Sure, you might be able to do it for next to nothing in your kitchen with nothing but a pan and a burner. But you could also pay $400 for a robot that will do it for you—as long as you don’t want your eggs scrambled, that is. A new Kickstarter project has finally given us a Juicero for the robotics era, and it’s called E.G.O.R. (that’s Efficient Gastronomic Operational Robot), brought to you by the startup Cheffy. It’s an automated egg maker that promises perfect cracks every time with no shell in the yolk. It has seven different ways that it can cook them up for you, or you can just use it to do the cracking. You can also pair it with a toaster so your eggs and toast finish at the exact right time. NEW: Cheffy just launched a robot that cracks and cooks your eggs. Egor automates breakfast by cooking eggs 7 ways, while Toastr syncs your toast so everything finishes together. -Automatically cracks eggs with no shells or mess-Cooks eggs 7 ways, from sunny-side up to hard… pic.twitter.com/auE3SnfrS3 — Ritwik Pavan (@ritwikpavan) July 30, 2026 This isn’t something anyone really needs. Cooking an egg over easy takes about two minutes, so calling this a time-saver is a stretch. And if you really don’t want to use the stove, you can buy a basic egg cooker for around $20 almost anywhere. Maybe you’re bad at cracking eggs, but $400 (well, $200 if you get in on the early bird deal) is a lot to pay to not have to pick the occasional shell pieces out. But hey, the robotics era needed its Juicero moment. To the creator’s credit: it seems like they’re treating this more like a fun novelty (albeit a pretty pricey one) rather than something revolutionary. They also aren’t making you buy proprietary eggs that are required to make the machine work, so they’ve got the Juicero bros beat there. We’re increasingly seeing robots positioned to do basic tasks. A company called Weave got attention earlier this year with an $8,000 robot that folds clothes. There’s a company in San Francisco offering house cleanings performed by humanoid robots. Last year, 1x made waves by introducing its Neo humanoid robot, which the Wall Street Journal reported “nearly toppled over” while closing a dishwasher and struggled to open the refrigerator. All of these machines cost an inordinate amount of money to do things that do not cost the average person that much time or money to accomplish. They’re novel, sure. But you don’t have to pay a premium to be a beta tester. #Robot #Revolution #Juiceroartifical intelligence,automation,Robotics

The price of eggs has become a marker of the state of the economy. But how about the cost of making eggs? Sure, you might be able to do it for next to nothing in your kitchen with nothing but a pan and a burner. But you could also pay $400 for a robot that will do it for you—as long as you don’t want your eggs scrambled, that is.

A new Kickstarter project has finally given us a Juicero for the robotics era, and it’s called E.G.O.R. (that’s Efficient Gastronomic Operational Robot), brought to you by the startup Cheffy. It’s an automated egg maker that promises perfect cracks every time with no shell in the yolk. It has seven different ways that it can cook them up for you, or you can just use it to do the cracking. You can also pair it with a toaster so your eggs and toast finish at the exact right time.

This isn’t something anyone really needs. Cooking an egg over easy takes about two minutes, so calling this a time-saver is a stretch. And if you really don’t want to use the stove, you can buy a basic egg cooker for around $20 almost anywhere. Maybe you’re bad at cracking eggs, but $400 (well, $200 if you get in on the early bird deal) is a lot to pay to not have to pick the occasional shell pieces out.

But hey, the robotics era needed its Juicero moment. To the creator’s credit: it seems like they’re treating this more like a fun novelty (albeit a pretty pricey one) rather than something revolutionary. They also aren’t making you buy proprietary eggs that are required to make the machine work, so they’ve got the Juicero bros beat there.

We’re increasingly seeing robots positioned to do basic tasks. A company called Weave got attention earlier this year with an $8,000 robot that folds clothes. There’s a company in San Francisco offering house cleanings performed by humanoid robots. Last year, 1x made waves by introducing its Neo humanoid robot, which the Wall Street Journal reported “nearly toppled over” while closing a dishwasher and struggled to open the refrigerator.

All of these machines cost an inordinate amount of money to do things that do not cost the average person that much time or money to accomplish. They’re novel, sure. But you don’t have to pay a premium to be a beta tester.

#Robot #Revolution #Juiceroartifical intelligence,automation,Robotics

The price of eggs has become a marker of the state of the economy. But…

Chinese AI models like Kimi K3 and DeepSeek R1 came out of nowhere. But the truth is that even if you never travel to China, there’s an easy way to get a sense of what Chinese AI researchers are up to: log on to X.

In the past year, I’ve seen a steady increase of Chinese artificial intelligence researchers joining X and participating in the wider discourse about AI development and commercialization. Take Moonshot AI, the company behind Kimi K3, as an example. On Thursday, I was able to quickly find around 30 accounts on X run by people who claim to be currently affiliated with Moonshot, including two of the startup’s cofounders, as well as half a dozen former employees and collaborators. And these are not dormant accounts: They talk about Moonshot’s big releases and incremental research papers, make friends with Western researchers, and share details about their personal life and hobbies.

Moonshot is arguably the Chinese AI lab that’s most active on X, but you will easily find executives and technical staff from other leading Chinese startups, like Minimax and Z.ai. Even several employees at DeepSeek, who reportedly are unable to leave China because the government confiscated their passports, regularly post on X about the latest AI news and share job listings to recruit new talent.

“X is the best community” for AI discussions right now, says Meng Fanqing, cofounder of the startup Evolvent AI and a former intern at Moonshot, where he worked on the Kimi K2.5 model. “There are both Chinese and overseas audiences, and the recommendation algorithm works pretty well for showing you content in the same circle that you are in,” he says. Compared with Chinese platforms, where it’s often hard to have serious technical discussions, Chinese researchers like Meng say they would rather spend their time on X.

Meng says he started actively posting on X in mid-2025. At the start of the year, DeepSeek’s R1 model went viral around the world, shining a bright spotlight on China’s AI industry. Many Chinese researchers seized the moment and joined X to start sharing their perspective. “Around that time, all the Chinese researchers are starting to think about branding on an international level,” Meng says.

Chinese AI researchers may also be helping fill a growing gap left by researchers at OpenAI and Anthropic, who have become more reluctant to share their thinking online as their employers have grown into behemoth companies, says Tiezhen Wang, an independent AI analyst and former researcher at Hugging Face. “I guess they feel that their model architecture and how they train the model is kind of a secret, so they’re posting less,” Wang explains. As a result, Chinese researchers are getting more attention from audiences on X who are hungry to make sense of what’s happening in the fast-moving world of AI.

Why Choose X?

One reason X may have become popular among Chinese AI researchers is that there’s not really a comparable social platform in China for high-quality technical discussions about AI and other emerging technologies.

Some people say they used to post on Zhihu, a Quora-like platform that once branded itself as the premier destination for educated professionals to show and tell. But since 2020, Zhihu has increasingly pivoted to hosting fiction content, and expert contributors have gradually fallen off. For example, Deng Yu, a Chinese mathematician who was awarded a Fields Medal this year, publicly wrote on Zhihu in 2018 that he decided to stop posting on the site due to the rise of low-quality content.

#Chinese #Researchers #Finding #Voicemade in china,china,artificial intelligence,x,twitter,rednote,deepseek"> Chinese AI Researchers Are Finding Their Voice on XThe prevailing narrative in Silicon Valley is that Chinese AI models like Kimi K3 and DeepSeek R1 came out of nowhere. But the truth is that even if you never travel to China, there’s an easy way to get a sense of what Chinese AI researchers are up to: log on to X.In the past year, I’ve seen a steady increase of Chinese artificial intelligence researchers joining X and participating in the wider discourse about AI development and commercialization. Take Moonshot AI, the company behind Kimi K3, as an example. On Thursday, I was able to quickly find around 30 accounts on X run by people who claim to be currently affiliated with Moonshot, including two of the startup’s cofounders, as well as half a dozen former employees and collaborators. And these are not dormant accounts: They talk about Moonshot’s big releases and incremental research papers, make friends with Western researchers, and share details about their personal life and hobbies.Moonshot is arguably the Chinese AI lab that’s most active on X, but you will easily find executives and technical staff from other leading Chinese startups, like Minimax and Z.ai. Even several employees at DeepSeek, who reportedly are unable to leave China because the government confiscated their passports, regularly post on X about the latest AI news and share job listings to recruit new talent.“X is the best community” for AI discussions right now, says Meng Fanqing, cofounder of the startup Evolvent AI and a former intern at Moonshot, where he worked on the Kimi K2.5 model. “There are both Chinese and overseas audiences, and the recommendation algorithm works pretty well for showing you content in the same circle that you are in,” he says. Compared with Chinese platforms, where it’s often hard to have serious technical discussions, Chinese researchers like Meng say they would rather spend their time on X.Meng says he started actively posting on X in mid-2025. At the start of the year, DeepSeek’s R1 model went viral around the world, shining a bright spotlight on China’s AI industry. Many Chinese researchers seized the moment and joined X to start sharing their perspective. “Around that time, all the Chinese researchers are starting to think about branding on an international level,” Meng says.Chinese AI researchers may also be helping fill a growing gap left by researchers at OpenAI and Anthropic, who have become more reluctant to share their thinking online as their employers have grown into behemoth companies, says Tiezhen Wang, an independent AI analyst and former researcher at Hugging Face. “I guess they feel that their model architecture and how they train the model is kind of a secret, so they’re posting less,” Wang explains. As a result, Chinese researchers are getting more attention from audiences on X who are hungry to make sense of what’s happening in the fast-moving world of AI.Why Choose X?One reason X may have become popular among Chinese AI researchers is that there’s not really a comparable social platform in China for high-quality technical discussions about AI and other emerging technologies.Some people say they used to post on Zhihu, a Quora-like platform that once branded itself as the premier destination for educated professionals to show and tell. But since 2020, Zhihu has increasingly pivoted to hosting fiction content, and expert contributors have gradually fallen off. For example, Deng Yu, a Chinese mathematician who was awarded a Fields Medal this year, publicly wrote on Zhihu in 2018 that he decided to stop posting on the site due to the rise of low-quality content.#Chinese #Researchers #Finding #Voicemade in china,china,artificial intelligence,x,twitter,rednote,deepseek
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Chinese AI models like Kimi K3 and DeepSeek R1 came out of nowhere. But the truth is that even if you never travel to China, there’s an easy way to get a sense of what Chinese AI researchers are up to: log on to X.

In the past year, I’ve seen a steady increase of Chinese artificial intelligence researchers joining X and participating in the wider discourse about AI development and commercialization. Take Moonshot AI, the company behind Kimi K3, as an example. On Thursday, I was able to quickly find around 30 accounts on X run by people who claim to be currently affiliated with Moonshot, including two of the startup’s cofounders, as well as half a dozen former employees and collaborators. And these are not dormant accounts: They talk about Moonshot’s big releases and incremental research papers, make friends with Western researchers, and share details about their personal life and hobbies.

Moonshot is arguably the Chinese AI lab that’s most active on X, but you will easily find executives and technical staff from other leading Chinese startups, like Minimax and Z.ai. Even several employees at DeepSeek, who reportedly are unable to leave China because the government confiscated their passports, regularly post on X about the latest AI news and share job listings to recruit new talent.

“X is the best community” for AI discussions right now, says Meng Fanqing, cofounder of the startup Evolvent AI and a former intern at Moonshot, where he worked on the Kimi K2.5 model. “There are both Chinese and overseas audiences, and the recommendation algorithm works pretty well for showing you content in the same circle that you are in,” he says. Compared with Chinese platforms, where it’s often hard to have serious technical discussions, Chinese researchers like Meng say they would rather spend their time on X.

Meng says he started actively posting on X in mid-2025. At the start of the year, DeepSeek’s R1 model went viral around the world, shining a bright spotlight on China’s AI industry. Many Chinese researchers seized the moment and joined X to start sharing their perspective. “Around that time, all the Chinese researchers are starting to think about branding on an international level,” Meng says.

Chinese AI researchers may also be helping fill a growing gap left by researchers at OpenAI and Anthropic, who have become more reluctant to share their thinking online as their employers have grown into behemoth companies, says Tiezhen Wang, an independent AI analyst and former researcher at Hugging Face. “I guess they feel that their model architecture and how they train the model is kind of a secret, so they’re posting less,” Wang explains. As a result, Chinese researchers are getting more attention from audiences on X who are hungry to make sense of what’s happening in the fast-moving world of AI.

Why Choose X?

One reason X may have become popular among Chinese AI researchers is that there’s not really a comparable social platform in China for high-quality technical discussions about AI and other emerging technologies.

Some people say they used to post on Zhihu, a Quora-like platform that once branded itself as the premier destination for educated professionals to show and tell. But since 2020, Zhihu has increasingly pivoted to hosting fiction content, and expert contributors have gradually fallen off. For example, Deng Yu, a Chinese mathematician who was awarded a Fields Medal this year, publicly wrote on Zhihu in 2018 that he decided to stop posting on the site due to the rise of low-quality content.

#Chinese #Researchers #Finding #Voicemade in china,china,artificial intelligence,x,twitter,rednote,deepseek">Chinese AI Researchers Are Finding Their Voice on X

The prevailing narrative in Silicon Valley is that Chinese AI models like Kimi K3 and DeepSeek R1 came out of nowhere. But the truth is that even if you never travel to China, there’s an easy way to get a sense of what Chinese AI researchers are up to: log on to X.

In the past year, I’ve seen a steady increase of Chinese artificial intelligence researchers joining X and participating in the wider discourse about AI development and commercialization. Take Moonshot AI, the company behind Kimi K3, as an example. On Thursday, I was able to quickly find around 30 accounts on X run by people who claim to be currently affiliated with Moonshot, including two of the startup’s cofounders, as well as half a dozen former employees and collaborators. And these are not dormant accounts: They talk about Moonshot’s big releases and incremental research papers, make friends with Western researchers, and share details about their personal life and hobbies.

Moonshot is arguably the Chinese AI lab that’s most active on X, but you will easily find executives and technical staff from other leading Chinese startups, like Minimax and Z.ai. Even several employees at DeepSeek, who reportedly are unable to leave China because the government confiscated their passports, regularly post on X about the latest AI news and share job listings to recruit new talent.

“X is the best community” for AI discussions right now, says Meng Fanqing, cofounder of the startup Evolvent AI and a former intern at Moonshot, where he worked on the Kimi K2.5 model. “There are both Chinese and overseas audiences, and the recommendation algorithm works pretty well for showing you content in the same circle that you are in,” he says. Compared with Chinese platforms, where it’s often hard to have serious technical discussions, Chinese researchers like Meng say they would rather spend their time on X.

Meng says he started actively posting on X in mid-2025. At the start of the year, DeepSeek’s R1 model went viral around the world, shining a bright spotlight on China’s AI industry. Many Chinese researchers seized the moment and joined X to start sharing their perspective. “Around that time, all the Chinese researchers are starting to think about branding on an international level,” Meng says.

Chinese AI researchers may also be helping fill a growing gap left by researchers at OpenAI and Anthropic, who have become more reluctant to share their thinking online as their employers have grown into behemoth companies, says Tiezhen Wang, an independent AI analyst and former researcher at Hugging Face. “I guess they feel that their model architecture and how they train the model is kind of a secret, so they’re posting less,” Wang explains. As a result, Chinese researchers are getting more attention from audiences on X who are hungry to make sense of what’s happening in the fast-moving world of AI.

Why Choose X?

One reason X may have become popular among Chinese AI researchers is that there’s not really a comparable social platform in China for high-quality technical discussions about AI and other emerging technologies.

Some people say they used to post on Zhihu, a Quora-like platform that once branded itself as the premier destination for educated professionals to show and tell. But since 2020, Zhihu has increasingly pivoted to hosting fiction content, and expert contributors have gradually fallen off. For example, Deng Yu, a Chinese mathematician who was awarded a Fields Medal this year, publicly wrote on Zhihu in 2018 that he decided to stop posting on the site due to the rise of low-quality content.

#Chinese #Researchers #Finding #Voicemade in china,china,artificial intelligence,x,twitter,rednote,deepseek

The prevailing narrative in Silicon Valley is that Chinese AI models like Kimi K3 and…

T-Mobile service was disrupted on Monday, you may be able to get some compensation for your troubles.

Multiple outlets, including KTLA in Los Angeles, have reported that some T-Mobile customers have been able to get at least $20 off their next bill because of the outage. One Reddit user said they were able to save as much as $80 (spread out over multiple billing cycles) by telling customer service that they missed out on a work opportunity because of the outage.

SEE ALSO: T-Mobile is giving away the Apple iPhone 17 for free — how to qualify

Generally, it seems that these credits are not automatic, and you may have to personally contact T-Mobile customer service to be compensated for your troubles.

After a major Verizon mobile outage in January, Verizon offered all affected customers a $20 credit.

Millions of T-Mobile users found their phones stuck in SOS mode on Monday afternoon, which led to plenty of criticism of the brand on social media. T-Mobile did acknowledge and apologize for the outage, though it has not explained what happened.

Mashable contacted T-Mobile repeatedly to ask about the outage and its causes, but so far, the company has been silent. The most recent post at the T-Mobile news page is the company’s Q2 2026 earnings report, in which the company saw growing revenue and profits, with total revenue for the quarter of $22.7 billion.

#TMobile #outage #credit #bill"> T-Mobile outage: You might be able to get credit on your bill If your T-Mobile service was disrupted on Monday, you may be able to get some compensation for your troubles.Multiple outlets, including KTLA in Los Angeles, have reported that some T-Mobile customers have been able to get at least off their next bill because of the outage. One Reddit user said they were able to save as much as (spread out over multiple billing cycles) by telling customer service that they missed out on a work opportunity because of the outage. SEE ALSO: T-Mobile is giving away the Apple iPhone 17 for free — how to qualify Generally, it seems that these credits are not automatic, and you may have to personally contact T-Mobile customer service to be compensated for your troubles. Mashable Light Speed After a major Verizon mobile outage in January, Verizon offered all affected customers a credit.Millions of T-Mobile users found their phones stuck in SOS mode on Monday afternoon, which led to plenty of criticism of the brand on social media. T-Mobile did acknowledge and apologize for the outage, though it has not explained what happened. This Tweet is currently unavailable. It might be loading or has been removed. Mashable contacted T-Mobile repeatedly to ask about the outage and its causes, but so far, the company has been silent. The most recent post at the T-Mobile news page is the company’s Q2 2026 earnings report, in which the company saw growing revenue and profits, with total revenue for the quarter of .7 billion. #TMobile #outage #credit #bill
Tech-news

T-Mobile service was disrupted on Monday, you may be able to get some compensation for your troubles.

Multiple outlets, including KTLA in Los Angeles, have reported that some T-Mobile customers have been able to get at least $20 off their next bill because of the outage. One Reddit user said they were able to save as much as $80 (spread out over multiple billing cycles) by telling customer service that they missed out on a work opportunity because of the outage.

SEE ALSO: T-Mobile is giving away the Apple iPhone 17 for free — how to qualify

Generally, it seems that these credits are not automatic, and you may have to personally contact T-Mobile customer service to be compensated for your troubles.

After a major Verizon mobile outage in January, Verizon offered all affected customers a $20 credit.

Millions of T-Mobile users found their phones stuck in SOS mode on Monday afternoon, which led to plenty of criticism of the brand on social media. T-Mobile did acknowledge and apologize for the outage, though it has not explained what happened.

Mashable contacted T-Mobile repeatedly to ask about the outage and its causes, but so far, the company has been silent. The most recent post at the T-Mobile news page is the company’s Q2 2026 earnings report, in which the company saw growing revenue and profits, with total revenue for the quarter of $22.7 billion.

#TMobile #outage #credit #bill">T-Mobile outage: You might be able to get credit on your bill

If your T-Mobile service was disrupted on Monday, you may be able to get some compensation for your troubles.

Multiple outlets, including KTLA in Los Angeles, have reported that some T-Mobile customers have been able to get at least $20 off their next bill because of the outage. One Reddit user said they were able to save as much as $80 (spread out over multiple billing cycles) by telling customer service that they missed out on a work opportunity because of the outage.

SEE ALSO: T-Mobile is giving away the Apple iPhone 17 for free — how to qualify

Generally, it seems that these credits are not automatic, and you may have to personally contact T-Mobile customer service to be compensated for your troubles.

After a major Verizon mobile outage in January, Verizon offered all affected customers a $20 credit.

Millions of T-Mobile users found their phones stuck in SOS mode on Monday afternoon, which led to plenty of criticism of the brand on social media. T-Mobile did acknowledge and apologize for the outage, though it has not explained what happened.

Mashable contacted T-Mobile repeatedly to ask about the outage and its causes, but so far, the company has been silent. The most recent post at the T-Mobile news page is the company’s Q2 2026 earnings report, in which the company saw growing revenue and profits, with total revenue for the quarter of $22.7 billion.

#TMobile #outage #credit #bill

If your T-Mobile service was disrupted on Monday, you may be able to get some…

we have an AI problem. This week, we learned more about exactly how OpenAI’s agent broke out of a sandbox and autonomously traversed the web, including a bunch of other supposedly secure web services, all in the name of cheating on a benchmark tests.

The fact that this hack happened is a problem. So is the fact that it took a while for anyone to notice. And the fact that it seems no one is willing or able to do much to stop it. (And lest you think it’s just an OpenAI problem, since we recorded this episode Anthropic acknowledged its models have also hacked a bunch of other companies without either party knowing.) It might all just be a bunch of posturing and hype, but it’s also increasingly clear that the companies building large language models either can’t or won’t put the right guardrails on them. So who will?

After all that, it’s time for Brendan Carr is a Dummy, a bunch of vertical video news, and the smashing success of the Ferrari Luce. People are buying it! If one of them is you, we’d love to hear about it.

#time #panic #safetyAI,OpenAI,Podcasts,Policy,Vergecast"> It’s time to panic about AI safetyWhen the phrase “OpenAI hacked Hugging Face” has more or less entered mainstream culture, you know we have an AI problem. This week, we learned more about exactly how OpenAI’s agent broke out of a sandbox and autonomously traversed the web, including a bunch of other supposedly secure web services, all in the name of cheating on a benchmark tests.The fact that this hack happened is a problem. So is the fact that it took a while for anyone to notice. And the fact that it seems no one is willing or able to do much to stop it. (And lest you think it’s just an OpenAI problem, since we recorded this episode Anthropic acknowledged its models have also hacked a bunch of other companies without either party knowing.) It might all just be a bunch of posturing and hype, but it’s also increasingly clear that the companies building large language models either can’t or won’t put the right guardrails on them. So who will?After all that, it’s time for Brendan Carr is a Dummy, a bunch of vertical video news, and the smashing success of the Ferrari Luce. People are buying it! If one of them is you, we’d love to hear about it.#time #panic #safetyAI,OpenAI,Podcasts,Policy,Vergecast
Tech-news

we have an AI problem. This week, we learned more about exactly how OpenAI’s agent broke out of a sandbox and autonomously traversed the web, including a bunch of other supposedly secure web services, all in the name of cheating on a benchmark tests.

The fact that this hack happened is a problem. So is the fact that it took a while for anyone to notice. And the fact that it seems no one is willing or able to do much to stop it. (And lest you think it’s just an OpenAI problem, since we recorded this episode Anthropic acknowledged its models have also hacked a bunch of other companies without either party knowing.) It might all just be a bunch of posturing and hype, but it’s also increasingly clear that the companies building large language models either can’t or won’t put the right guardrails on them. So who will?

After all that, it’s time for Brendan Carr is a Dummy, a bunch of vertical video news, and the smashing success of the Ferrari Luce. People are buying it! If one of them is you, we’d love to hear about it.

#time #panic #safetyAI,OpenAI,Podcasts,Policy,Vergecast">It’s time to panic about AI safety

When the phrase “OpenAI hacked Hugging Face” has more or less entered mainstream culture, you know we have an AI problem. This week, we learned more about exactly how OpenAI’s agent broke out of a sandbox and autonomously traversed the web, including a bunch of other supposedly secure web services, all in the name of cheating on a benchmark tests.

The fact that this hack happened is a problem. So is the fact that it took a while for anyone to notice. And the fact that it seems no one is willing or able to do much to stop it. (And lest you think it’s just an OpenAI problem, since we recorded this episode Anthropic acknowledged its models have also hacked a bunch of other companies without either party knowing.) It might all just be a bunch of posturing and hype, but it’s also increasingly clear that the companies building large language models either can’t or won’t put the right guardrails on them. So who will?

After all that, it’s time for Brendan Carr is a Dummy, a bunch of vertical video news, and the smashing success of the Ferrari Luce. People are buying it! If one of them is you, we’d love to hear about it.

#time #panic #safetyAI,OpenAI,Podcasts,Policy,Vergecast

When the phrase “OpenAI hacked Hugging Face” has more or less entered mainstream culture, you…

Hugging Face’s systems during internal testing.

In all three cases, a Claude model reached the internet from within a testing environment while interacting with a third party and then gained unauthorized access to the live systems of these organizations, Anthropic said in a blog post, describing what it found and what the company plans to change to prevent this from happening again.

Anthropic said the OpenAI episode earlier this month prompted the company to conduct its own cybersecurity evaluation. It specifically looked for evidence that Claude had accessed the internet from within testing environments, which are designed to act as sandboxes and keep models isolated.

Among the 141,006 evaluation runs it reviewed, the AI lab found three incidents in which its model accessed the internet while interacting with Irregular, one of its third-party partners. Anthropic said the access traced back to a misconfiguration in the evaluation environment run with Irregular. It called this a “misunderstanding” between the two companies over whether the test setup had internet access, when in fact it did.

Anthropic said it isn’t placing blame and is “approaching the fixes as if the responsibility were ours alone,” while observing that Irregular is conducting its own separate investigation.

Because of that open connection, the model gained unauthorized access to the production infrastructure of three different organizations. Anthropic said the incidents involved three different Claude models: Opus 4.7, Mythos 5, and an internal research test model.

Notably, Anthropic said that in each of these cases “Claude was explicitly told by our prompt that it had no internet access.” It appears that the AI model assumed real-world systems to be part of the exercise it was asked to perform.

That assumption didn’t hold up uniformly, as it turns out. The three models didn’t behave the same way once evidence emerged that their targets were real, which Anthropic flagged as one of the more eye-opening findings Thursday.

Opus 4.7, the oldest of the three, recognized that it had reached a real production system in all four runs of that incident. In two of them, it rationalized that the real company must somehow be part of the exercise, but in all four, it kept attacking anyway, including pulling credentials and touching a database of production data. Mythos 5 also picked up on signs that it was on the real internet, but it talked itself back into believing it was still in a simulation, going on to publish a malicious software package to the public Python software registry PyPI, which was then downloaded and run by outside systems before being caught. Only the internal research test model, Anthropic’s newest, stopped on its own once it concluded the target was real.

In response, Anthropic said significant controls must be placed on these kinds of evaluations if powerful AI models are involved, echoing some sentiments within the cybersecurity community.

The company also noted that Claude was running without the additional safety monitoring and classifiers it deploys on generally available models — safeguards it said would have blocked the behavior, because the evaluations are designed to measure the underlying model’s raw capabilities.

Importantly, Anthropic said it found no evidence of any model “pursuing a goal of its own” and instead merely tried to complete the task it was asked to do.

Though comparisons between the mishaps of these fiercely competitive companies are inevitable, Anthropic in its blog post drew a clear distinction between its cybersecurity tests and those of OpenAI, noting where OpenAI’s model exploited an unknown software vulnerability to break out of its test environment, Anthropic’s models instead reached the internet through a path that had, by mistake, been left open.

Anthropic also drew a distinction between itself and OpenAI by noting that it discovered the incidents itself, through a proactive review, and that the two affected organizations it was able to reach hadn’t previously detected the activity or flagged it to Anthropic. (In contrast, Hugging Face detected the recent intrusion of its own systems first; it was only in the following days that OpenAI identified and disclosed that its own AI agent was the perpetrator.)

The company added that it’s now working with the independent evaluation group METR on a third-party review of the incidents.

OpenAI’s accidental breach of Hugging Face, which was the first verifiable case of an AI lab losing control of its model, has sparked a string of wildly differing reactions from the industry and politicians. This latest disclosure from Anthropic ensures the debate over AI models and security will continue.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#Anthropic #models #breached #companies #security #tests #TechCrunchAnthropic,OpenAI"> Anthropic says its own AI models breached three companies during security tests | TechCrunch Anthropic said Thursday that an internal investigation uncovered three incidents in which its AI model Claude breached the systems of three organizations while conducting cybersecurity tests. The investigation, and disclosure, comes more than a week after OpenAI disclosed that one of its unreleased models breached Hugging Face’s systems during internal testing. In all three cases, a Claude model reached the internet from within a testing environment while interacting with a third party and then gained unauthorized access to the live systems of these organizations, Anthropic said in a blog post, describing what it found and what the company plans to change to prevent this from happening again. Anthropic said the OpenAI episode earlier this month prompted the company to conduct its own cybersecurity evaluation. It specifically looked for evidence that Claude had accessed the internet from within testing environments, which are designed to act as sandboxes and keep models isolated. Among the 141,006 evaluation runs it reviewed, the AI lab found three incidents in which its model accessed the internet while interacting with Irregular, one of its third-party partners. Anthropic said the access traced back to a misconfiguration in the evaluation environment run with Irregular. It called this a “misunderstanding” between the two companies over whether the test setup had internet access, when in fact it did. Anthropic said it isn’t placing blame and is “approaching the fixes as if the responsibility were ours alone,” while observing that Irregular is conducting its own separate investigation. Because of that open connection, the model gained unauthorized access to the production infrastructure of three different organizations. Anthropic said the incidents involved three different Claude models: Opus 4.7, Mythos 5, and an internal research test model. Notably, Anthropic said that in each of these cases “Claude was explicitly told by our prompt that it had no internet access.” It appears that the AI model assumed real-world systems to be part of the exercise it was asked to perform. That assumption didn’t hold up uniformly, as it turns out. The three models didn’t behave the same way once evidence emerged that their targets were real, which Anthropic flagged as one of the more eye-opening findings Thursday. Opus 4.7, the oldest of the three, recognized that it had reached a real production system in all four runs of that incident. In two of them, it rationalized that the real company must somehow be part of the exercise, but in all four, it kept attacking anyway, including pulling credentials and touching a database of production data. Mythos 5 also picked up on signs that it was on the real internet, but it talked itself back into believing it was still in a simulation, going on to publish a malicious software package to the public Python software registry PyPI, which was then downloaded and run by outside systems before being caught. Only the internal research test model, Anthropic’s newest, stopped on its own once it concluded the target was real. In response, Anthropic said significant controls must be placed on these kinds of evaluations if powerful AI models are involved, echoing some sentiments within the cybersecurity community. The company also noted that Claude was running without the additional safety monitoring and classifiers it deploys on generally available models — safeguards it said would have blocked the behavior, because the evaluations are designed to measure the underlying model’s raw capabilities. Importantly, Anthropic said it found no evidence of any model “pursuing a goal of its own” and instead merely tried to complete the task it was asked to do. Though comparisons between the mishaps of these fiercely competitive companies are inevitable, Anthropic in its blog post drew a clear distinction between its cybersecurity tests and those of OpenAI, noting where OpenAI’s model exploited an unknown software vulnerability to break out of its test environment, Anthropic’s models instead reached the internet through a path that had, by mistake, been left open. Anthropic also drew a distinction between itself and OpenAI by noting that it discovered the incidents itself, through a proactive review, and that the two affected organizations it was able to reach hadn’t previously detected the activity or flagged it to Anthropic. (In contrast, Hugging Face detected the recent intrusion of its own systems first; it was only in the following days that OpenAI identified and disclosed that its own AI agent was the perpetrator.) The company added that it’s now working with the independent evaluation group METR on a third-party review of the incidents. OpenAI’s accidental breach of Hugging Face, which was the first verifiable case of an AI lab losing control of its model, has sparked a string of wildly differing reactions from the industry and politicians. This latest disclosure from Anthropic ensures the debate over AI models and security will continue. When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Anthropic #models #breached #companies #security #tests #TechCrunchAnthropic,OpenAI
Tech-news

Hugging Face’s systems during internal testing.

In all three cases, a Claude model reached the internet from within a testing environment while interacting with a third party and then gained unauthorized access to the live systems of these organizations, Anthropic said in a blog post, describing what it found and what the company plans to change to prevent this from happening again.

Anthropic said the OpenAI episode earlier this month prompted the company to conduct its own cybersecurity evaluation. It specifically looked for evidence that Claude had accessed the internet from within testing environments, which are designed to act as sandboxes and keep models isolated.

Among the 141,006 evaluation runs it reviewed, the AI lab found three incidents in which its model accessed the internet while interacting with Irregular, one of its third-party partners. Anthropic said the access traced back to a misconfiguration in the evaluation environment run with Irregular. It called this a “misunderstanding” between the two companies over whether the test setup had internet access, when in fact it did.

Anthropic said it isn’t placing blame and is “approaching the fixes as if the responsibility were ours alone,” while observing that Irregular is conducting its own separate investigation.

Because of that open connection, the model gained unauthorized access to the production infrastructure of three different organizations. Anthropic said the incidents involved three different Claude models: Opus 4.7, Mythos 5, and an internal research test model.

Notably, Anthropic said that in each of these cases “Claude was explicitly told by our prompt that it had no internet access.” It appears that the AI model assumed real-world systems to be part of the exercise it was asked to perform.

That assumption didn’t hold up uniformly, as it turns out. The three models didn’t behave the same way once evidence emerged that their targets were real, which Anthropic flagged as one of the more eye-opening findings Thursday.

Opus 4.7, the oldest of the three, recognized that it had reached a real production system in all four runs of that incident. In two of them, it rationalized that the real company must somehow be part of the exercise, but in all four, it kept attacking anyway, including pulling credentials and touching a database of production data. Mythos 5 also picked up on signs that it was on the real internet, but it talked itself back into believing it was still in a simulation, going on to publish a malicious software package to the public Python software registry PyPI, which was then downloaded and run by outside systems before being caught. Only the internal research test model, Anthropic’s newest, stopped on its own once it concluded the target was real.

In response, Anthropic said significant controls must be placed on these kinds of evaluations if powerful AI models are involved, echoing some sentiments within the cybersecurity community.

The company also noted that Claude was running without the additional safety monitoring and classifiers it deploys on generally available models — safeguards it said would have blocked the behavior, because the evaluations are designed to measure the underlying model’s raw capabilities.

Importantly, Anthropic said it found no evidence of any model “pursuing a goal of its own” and instead merely tried to complete the task it was asked to do.

Though comparisons between the mishaps of these fiercely competitive companies are inevitable, Anthropic in its blog post drew a clear distinction between its cybersecurity tests and those of OpenAI, noting where OpenAI’s model exploited an unknown software vulnerability to break out of its test environment, Anthropic’s models instead reached the internet through a path that had, by mistake, been left open.

Anthropic also drew a distinction between itself and OpenAI by noting that it discovered the incidents itself, through a proactive review, and that the two affected organizations it was able to reach hadn’t previously detected the activity or flagged it to Anthropic. (In contrast, Hugging Face detected the recent intrusion of its own systems first; it was only in the following days that OpenAI identified and disclosed that its own AI agent was the perpetrator.)

The company added that it’s now working with the independent evaluation group METR on a third-party review of the incidents.

OpenAI’s accidental breach of Hugging Face, which was the first verifiable case of an AI lab losing control of its model, has sparked a string of wildly differing reactions from the industry and politicians. This latest disclosure from Anthropic ensures the debate over AI models and security will continue.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#Anthropic #models #breached #companies #security #tests #TechCrunchAnthropic,OpenAI">Anthropic says its own AI models breached three companies during security tests | TechCrunch

Anthropic said Thursday that an internal investigation uncovered three incidents in which its AI model Claude breached the systems of three organizations while conducting cybersecurity tests. The investigation, and disclosure, comes more than a week after OpenAI disclosed that one of its unreleased models breached Hugging Face’s systems during internal testing.

In all three cases, a Claude model reached the internet from within a testing environment while interacting with a third party and then gained unauthorized access to the live systems of these organizations, Anthropic said in a blog post, describing what it found and what the company plans to change to prevent this from happening again.

Anthropic said the OpenAI episode earlier this month prompted the company to conduct its own cybersecurity evaluation. It specifically looked for evidence that Claude had accessed the internet from within testing environments, which are designed to act as sandboxes and keep models isolated.

Among the 141,006 evaluation runs it reviewed, the AI lab found three incidents in which its model accessed the internet while interacting with Irregular, one of its third-party partners. Anthropic said the access traced back to a misconfiguration in the evaluation environment run with Irregular. It called this a “misunderstanding” between the two companies over whether the test setup had internet access, when in fact it did.

Anthropic said it isn’t placing blame and is “approaching the fixes as if the responsibility were ours alone,” while observing that Irregular is conducting its own separate investigation.

Because of that open connection, the model gained unauthorized access to the production infrastructure of three different organizations. Anthropic said the incidents involved three different Claude models: Opus 4.7, Mythos 5, and an internal research test model.

Notably, Anthropic said that in each of these cases “Claude was explicitly told by our prompt that it had no internet access.” It appears that the AI model assumed real-world systems to be part of the exercise it was asked to perform.

That assumption didn’t hold up uniformly, as it turns out. The three models didn’t behave the same way once evidence emerged that their targets were real, which Anthropic flagged as one of the more eye-opening findings Thursday.

Opus 4.7, the oldest of the three, recognized that it had reached a real production system in all four runs of that incident. In two of them, it rationalized that the real company must somehow be part of the exercise, but in all four, it kept attacking anyway, including pulling credentials and touching a database of production data. Mythos 5 also picked up on signs that it was on the real internet, but it talked itself back into believing it was still in a simulation, going on to publish a malicious software package to the public Python software registry PyPI, which was then downloaded and run by outside systems before being caught. Only the internal research test model, Anthropic’s newest, stopped on its own once it concluded the target was real.

In response, Anthropic said significant controls must be placed on these kinds of evaluations if powerful AI models are involved, echoing some sentiments within the cybersecurity community.

The company also noted that Claude was running without the additional safety monitoring and classifiers it deploys on generally available models — safeguards it said would have blocked the behavior, because the evaluations are designed to measure the underlying model’s raw capabilities.

Importantly, Anthropic said it found no evidence of any model “pursuing a goal of its own” and instead merely tried to complete the task it was asked to do.

Though comparisons between the mishaps of these fiercely competitive companies are inevitable, Anthropic in its blog post drew a clear distinction between its cybersecurity tests and those of OpenAI, noting where OpenAI’s model exploited an unknown software vulnerability to break out of its test environment, Anthropic’s models instead reached the internet through a path that had, by mistake, been left open.

Anthropic also drew a distinction between itself and OpenAI by noting that it discovered the incidents itself, through a proactive review, and that the two affected organizations it was able to reach hadn’t previously detected the activity or flagged it to Anthropic. (In contrast, Hugging Face detected the recent intrusion of its own systems first; it was only in the following days that OpenAI identified and disclosed that its own AI agent was the perpetrator.)

The company added that it’s now working with the independent evaluation group METR on a third-party review of the incidents.

OpenAI’s accidental breach of Hugging Face, which was the first verifiable case of an AI lab losing control of its model, has sparked a string of wildly differing reactions from the industry and politicians. This latest disclosure from Anthropic ensures the debate over AI models and security will continue.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#Anthropic #models #breached #companies #security #tests #TechCrunchAnthropic,OpenAI

Anthropic said Thursday that an internal investigation uncovered three incidents in which its AI model…

for their Linux VPS hosting to get the job done. Flexible server solutions make it possible to configure resources, select a suitable location, and deploy the environment automatically.

The list of users who will find this helpful is extensive: DevOps engineers, web application developers, SaaS platforms, and many others. Using open-source tools helps them create a reliable, transparent, and scalable environment for development and operations.

DevOps is today one of the key approaches to creating and managing software products. It connects development, testing, and operations, helping teams work faster. Open-source tools make workflows easier and flexible. Open source is basically built to bend. You can customize your tools, stitch them together, and automate the boring stuff. Honestly, it’s a perfect fit for pretty much anything — web, mobile, cloud, data, or AI. 

It is fair to say that several specific DevOps components help automate processes, improve system stability, and shorten the time between product development and launch. These include:

  • application build automation;
  • containerization of production services;
  • server configuration management;
  • infrastructure health monitoring;
  • secure storage of credentials.

Less manual grunt work means fewer mistakes. Auto-deploys let you ship updates in a flash, while smart monitoring catches performance bottlenecks before they become fires. 

Scalable Infrastructure for DevOps Teams

In practice, any DevOps model requires a reliable and powerful infrastructure. Every project, even the smallest one, must have the ability to quickly scale resources as more and more users join or as technical requirements change. The server environment must support flexible power settings, rapid creation of new environments, and stable service operation.

International IaaS providers offer VPS/VDS, dedicated servers, VPN services, and additional infrastructure solutions. Users can configure key server parameters, including:

  • processing power;
  • amount of RAM;
  • drive type;
  • data center location.

A broad infrastructure geography makes it possible to select suitable locations for different projects and reduce access latency. Such opportunities are in demand in various fields. Online stores use scalable servers to handle large numbers of requests.

When choosing DevOps infrastructure, it is important to consider not only current challenges but also growth prospects. A flexible server platform should allow configuration changes without complex migrations. Among the most popular features are:

  • setting up CPU and RAM;
  • use of fast NVMe drives;
  • support for different operating systems;
  • connecting additional IP addresses;
  • automatic deployment of environments;
  • integration via API tools.

This model makes it easier for technicians and helps launch new projects faster. DevOps teams can create test environments, run experiments, and migrate applications between environments with minimal time investment.

Fundamentals of System Security and Resilience

As soon as digital products begin to evolve, securing the system as a whole becomes just as important as maintaining performance. Good companies must secure the users data, provide uninterrupted service, and minimize the risk of breakdowns.

It is exactly these advanced open-source tools that help not only manage the entire system but also monitor it clearly. Teams will be able to track changes, audit settings, and implement additional security measures. When building a secure DevOps environment, special attention is paid to the following aspects:

  • isolation of virtual servers;
  • data backup;
  • protecting network connections;
  • use of IPv4 and IPv6;
  • user access control.

KVM technology ensures effective isolation of virtual machines and stable operation of VPS servers. SSDs and NVMe drives enable faster processing, and the latest generation of Intel Xeon and AMD EPYC processors allows you to run resource-intensive applications.

How to Choose Infrastructure for Long-Term Development

Choose a server that actually grows with you. You want to scale smoothly without hitting hidden fees. Look for clear, pay-as-you-go pricing — it’s the smartest way for startups to get top-tier tech without breaking the bank. 

Flexible servers work for almost any project. Building an edtech app? Marketing tools? Analytics? AI? To summarize, good infrastructure is the secret sauce to keep your product growing smoothly.

When you need a comprehensive strategy, keep in mind that it can only be based on a successful combination of elements. This includes automation, open-source tools, and high-quality server infrastructure. Together, they create a secure and scalable DevOps environment. These technologies help developers build products faster, monitor all critical processes, and manage resources as efficiently as possible.

#Building #Secure #Scalable #DevOps #Environment #OpenSource #ToolsDevOps"> Building a Secure and Scalable DevOps Environment Using Open-Source Tools We can all see how the newest digital products require flexibility and the ability to scale quickly together with the business. At the same time, they must cope with growing workloads. That’s why teams choose is*hosting for their Linux VPS hosting to get the job done. Flexible server solutions make it possible to configure resources, select a suitable location, and deploy the environment automatically. The list of users who will find this helpful is extensive: DevOps engineers, web application developers, SaaS platforms, and many others. Using open-source tools helps them create a reliable, transparent, and scalable environment for development and operations. DevOps is today one of the key approaches to creating and managing software products. It connects development, testing, and operations, helping teams work faster. Open-source tools make workflows easier and flexible. Open source is basically built to bend. You can customize your tools, stitch them together, and automate the boring stuff. Honestly, it’s a perfect fit for pretty much anything — web, mobile, cloud, data, or AI.  It is fair to say that several specific DevOps components help automate processes, improve system stability, and shorten the time between product development and launch. These include: application build automation; containerization of production services; server configuration management; infrastructure health monitoring; secure storage of credentials. Less manual grunt work means fewer mistakes. Auto-deploys let you ship updates in a flash, while smart monitoring catches performance bottlenecks before they become fires.  Scalable Infrastructure for DevOps Teams In practice, any DevOps model requires a reliable and powerful infrastructure. Every project, even the smallest one, must have the ability to quickly scale resources as more and more users join or as technical requirements change. The server environment must support flexible power settings, rapid creation of new environments, and stable service operation. International IaaS providers offer VPS/VDS, dedicated servers, VPN services, and additional infrastructure solutions. Users can configure key server parameters, including: processing power; amount of RAM; drive type; data center location. A broad infrastructure geography makes it possible to select suitable locations for different projects and reduce access latency. Such opportunities are in demand in various fields. Online stores use scalable servers to handle large numbers of requests. When choosing DevOps infrastructure, it is important to consider not only current challenges but also growth prospects. A flexible server platform should allow configuration changes without complex migrations. Among the most popular features are: setting up CPU and RAM; use of fast NVMe drives; support for different operating systems; connecting additional IP addresses; automatic deployment of environments; integration via API tools. This model makes it easier for technicians and helps launch new projects faster. DevOps teams can create test environments, run experiments, and migrate applications between environments with minimal time investment. Fundamentals of System Security and Resilience As soon as digital products begin to evolve, securing the system as a whole becomes just as important as maintaining performance. Good companies must secure the users data, provide uninterrupted service, and minimize the risk of breakdowns. It is exactly these advanced open-source tools that help not only manage the entire system but also monitor it clearly. Teams will be able to track changes, audit settings, and implement additional security measures. When building a secure DevOps environment, special attention is paid to the following aspects: isolation of virtual servers; data backup; protecting network connections; use of IPv4 and IPv6; user access control. KVM technology ensures effective isolation of virtual machines and stable operation of VPS servers. SSDs and NVMe drives enable faster processing, and the latest generation of Intel Xeon and AMD EPYC processors allows you to run resource-intensive applications. How to Choose Infrastructure for Long-Term Development Choose a server that actually grows with you. You want to scale smoothly without hitting hidden fees. Look for clear, pay-as-you-go pricing — it’s the smartest way for startups to get top-tier tech without breaking the bank.  Flexible servers work for almost any project. Building an edtech app? Marketing tools? Analytics? AI? To summarize, good infrastructure is the secret sauce to keep your product growing smoothly. When you need a comprehensive strategy, keep in mind that it can only be based on a successful combination of elements. This includes automation, open-source tools, and high-quality server infrastructure. Together, they create a secure and scalable DevOps environment. These technologies help developers build products faster, monitor all critical processes, and manage resources as efficiently as possible. #Building #Secure #Scalable #DevOps #Environment #OpenSource #ToolsDevOps
Tech-news

for their Linux VPS hosting to get the job done. Flexible server solutions make it possible to configure resources, select a suitable location, and deploy the environment automatically.

The list of users who will find this helpful is extensive: DevOps engineers, web application developers, SaaS platforms, and many others. Using open-source tools helps them create a reliable, transparent, and scalable environment for development and operations.

DevOps is today one of the key approaches to creating and managing software products. It connects development, testing, and operations, helping teams work faster. Open-source tools make workflows easier and flexible. Open source is basically built to bend. You can customize your tools, stitch them together, and automate the boring stuff. Honestly, it’s a perfect fit for pretty much anything — web, mobile, cloud, data, or AI. 

It is fair to say that several specific DevOps components help automate processes, improve system stability, and shorten the time between product development and launch. These include:

  • application build automation;
  • containerization of production services;
  • server configuration management;
  • infrastructure health monitoring;
  • secure storage of credentials.

Less manual grunt work means fewer mistakes. Auto-deploys let you ship updates in a flash, while smart monitoring catches performance bottlenecks before they become fires. 

Scalable Infrastructure for DevOps Teams

In practice, any DevOps model requires a reliable and powerful infrastructure. Every project, even the smallest one, must have the ability to quickly scale resources as more and more users join or as technical requirements change. The server environment must support flexible power settings, rapid creation of new environments, and stable service operation.

International IaaS providers offer VPS/VDS, dedicated servers, VPN services, and additional infrastructure solutions. Users can configure key server parameters, including:

  • processing power;
  • amount of RAM;
  • drive type;
  • data center location.

A broad infrastructure geography makes it possible to select suitable locations for different projects and reduce access latency. Such opportunities are in demand in various fields. Online stores use scalable servers to handle large numbers of requests.

When choosing DevOps infrastructure, it is important to consider not only current challenges but also growth prospects. A flexible server platform should allow configuration changes without complex migrations. Among the most popular features are:

  • setting up CPU and RAM;
  • use of fast NVMe drives;
  • support for different operating systems;
  • connecting additional IP addresses;
  • automatic deployment of environments;
  • integration via API tools.

This model makes it easier for technicians and helps launch new projects faster. DevOps teams can create test environments, run experiments, and migrate applications between environments with minimal time investment.

Fundamentals of System Security and Resilience

As soon as digital products begin to evolve, securing the system as a whole becomes just as important as maintaining performance. Good companies must secure the users data, provide uninterrupted service, and minimize the risk of breakdowns.

It is exactly these advanced open-source tools that help not only manage the entire system but also monitor it clearly. Teams will be able to track changes, audit settings, and implement additional security measures. When building a secure DevOps environment, special attention is paid to the following aspects:

  • isolation of virtual servers;
  • data backup;
  • protecting network connections;
  • use of IPv4 and IPv6;
  • user access control.

KVM technology ensures effective isolation of virtual machines and stable operation of VPS servers. SSDs and NVMe drives enable faster processing, and the latest generation of Intel Xeon and AMD EPYC processors allows you to run resource-intensive applications.

How to Choose Infrastructure for Long-Term Development

Choose a server that actually grows with you. You want to scale smoothly without hitting hidden fees. Look for clear, pay-as-you-go pricing — it’s the smartest way for startups to get top-tier tech without breaking the bank. 

Flexible servers work for almost any project. Building an edtech app? Marketing tools? Analytics? AI? To summarize, good infrastructure is the secret sauce to keep your product growing smoothly.

When you need a comprehensive strategy, keep in mind that it can only be based on a successful combination of elements. This includes automation, open-source tools, and high-quality server infrastructure. Together, they create a secure and scalable DevOps environment. These technologies help developers build products faster, monitor all critical processes, and manage resources as efficiently as possible.

#Building #Secure #Scalable #DevOps #Environment #OpenSource #ToolsDevOps">Building a Secure and Scalable DevOps Environment Using Open-Source Tools

We can all see how the newest digital products require flexibility and the ability to scale quickly together with the business. At the same time, they must cope with growing workloads. That’s why teams choose is*hosting for their Linux VPS hosting to get the job done. Flexible server solutions make it possible to configure resources, select a suitable location, and deploy the environment automatically.

The list of users who will find this helpful is extensive: DevOps engineers, web application developers, SaaS platforms, and many others. Using open-source tools helps them create a reliable, transparent, and scalable environment for development and operations.

DevOps is today one of the key approaches to creating and managing software products. It connects development, testing, and operations, helping teams work faster. Open-source tools make workflows easier and flexible. Open source is basically built to bend. You can customize your tools, stitch them together, and automate the boring stuff. Honestly, it’s a perfect fit for pretty much anything — web, mobile, cloud, data, or AI. 

It is fair to say that several specific DevOps components help automate processes, improve system stability, and shorten the time between product development and launch. These include:

Less manual grunt work means fewer mistakes. Auto-deploys let you ship updates in a flash, while smart monitoring catches performance bottlenecks before they become fires. 

Scalable Infrastructure for DevOps Teams

In practice, any DevOps model requires a reliable and powerful infrastructure. Every project, even the smallest one, must have the ability to quickly scale resources as more and more users join or as technical requirements change. The server environment must support flexible power settings, rapid creation of new environments, and stable service operation.

International IaaS providers offer VPS/VDS, dedicated servers, VPN services, and additional infrastructure solutions. Users can configure key server parameters, including:

A broad infrastructure geography makes it possible to select suitable locations for different projects and reduce access latency. Such opportunities are in demand in various fields. Online stores use scalable servers to handle large numbers of requests.

When choosing DevOps infrastructure, it is important to consider not only current challenges but also growth prospects. A flexible server platform should allow configuration changes without complex migrations. Among the most popular features are:

This model makes it easier for technicians and helps launch new projects faster. DevOps teams can create test environments, run experiments, and migrate applications between environments with minimal time investment.

Fundamentals of System Security and Resilience

As soon as digital products begin to evolve, securing the system as a whole becomes just as important as maintaining performance. Good companies must secure the users data, provide uninterrupted service, and minimize the risk of breakdowns.

It is exactly these advanced open-source tools that help not only manage the entire system but also monitor it clearly. Teams will be able to track changes, audit settings, and implement additional security measures. When building a secure DevOps environment, special attention is paid to the following aspects:

KVM technology ensures effective isolation of virtual machines and stable operation of VPS servers. SSDs and NVMe drives enable faster processing, and the latest generation of Intel Xeon and AMD EPYC processors allows you to run resource-intensive applications.

How to Choose Infrastructure for Long-Term Development

Choose a server that actually grows with you. You want to scale smoothly without hitting hidden fees. Look for clear, pay-as-you-go pricing — it’s the smartest way for startups to get top-tier tech without breaking the bank. 

Flexible servers work for almost any project. Building an edtech app? Marketing tools? Analytics? AI? To summarize, good infrastructure is the secret sauce to keep your product growing smoothly.

When you need a comprehensive strategy, keep in mind that it can only be based on a successful combination of elements. This includes automation, open-source tools, and high-quality server infrastructure. Together, they create a secure and scalable DevOps environment. These technologies help developers build products faster, monitor all critical processes, and manage resources as efficiently as possible.

#Building #Secure #Scalable #DevOps #Environment #OpenSource #ToolsDevOps

We can all see how the newest digital products require flexibility and the ability to…

Judge Rita Lin wasted little time pouring cold water on the federal government’s position. “I don’t see additional evidence from the government really justifying what it did. If anything, it seems like the record, in some ways, has gotten worse for the government,” she reportedly said.

She also did not seem convinced by the Pentagon’s apparent argument that it was concerned Anthropic would mess with its model to prevent the military from using it how they intended. “I don’t see evidence that Anthropic could alter the model after it was delivered or flip some kind of kill switch,” she said, per Axios.

This doesn’t come as a major surprise, given Judge Lin’s general vibe since this case landed in her court. Back in March when Anthropic first brought its challenge to the government’s designation, the judge said that “it looks like an attempt to cripple Anthropic.” She ultimately granted a temporary injunction on the government’s attempt to basically blacklist the AI firm.

You’ll recall the origin of this whole fight came earlier this year when negotiations between Anthropic and the Department of Defense fell through after the company refused to agree to a deal that would have allowed the Pentagon to use its AI models for “all lawful purposes.” Anthropic reportedly sought to clarify that it would not include using the model to launch weapons without human involvement or to perform surveillance on American citizens. The Pentagon was unwilling to agree to honor Anthropic’s redlines.

Under a normal administration, that would likely just lead to the government moving on to another company. Under the Trump administration, though, refusal to comply makes you an enemy of the country. Trump and company moved to label Anthropic a supply chain risk, a designation typically reserved for foreign adversaries, not domestic companies. Getting slapped with that tag meant the rest of the federal government would have to stop doing business with Anthropic, which would be a blow to the company.

Instead, the whole thing is in limbo—though it’s not looking great for the administration. Of course, they could just cancel the contracts and do business with less scrupulous AI companies. There are plenty willing to abandon their beliefs for a nice, fat contract, after all.

#Pentagons #Case #Anthropic #IsntAnthropic,artifical intelligence,Department of Defense,Lawsuit,pentagon"> The Pentagon’s Case Against Anthropic Isn’t Going Well The Department of Defense labeled AI lab Anthropic a supply-chain risk after the company refused to agree to allow the Pentagon to use its models for autonomous weapons systems and domestic surveillance. It seems the company isn’t just winning the moral argument on this front, but the legal one, too. According to Axios, the judge hearing Anthropic’s challenge to the Trump administration’s designation has thus far not found the Pentagon’s case to be particularly compelling. Per the report, U.S. District Judge Rita Lin wasted little time pouring cold water on the federal government’s position. “I don’t see additional evidence from the government really justifying what it did. If anything, it seems like the record, in some ways, has gotten worse for the government,” she reportedly said. She also did not seem convinced by the Pentagon’s apparent argument that it was concerned Anthropic would mess with its model to prevent the military from using it how they intended. “I don’t see evidence that Anthropic could alter the model after it was delivered or flip some kind of kill switch,” she said, per Axios. This doesn’t come as a major surprise, given Judge Lin’s general vibe since this case landed in her court. Back in March when Anthropic first brought its challenge to the government’s designation, the judge said that “it looks like an attempt to cripple Anthropic.” She ultimately granted a temporary injunction on the government’s attempt to basically blacklist the AI firm. You’ll recall the origin of this whole fight came earlier this year when negotiations between Anthropic and the Department of Defense fell through after the company refused to agree to a deal that would have allowed the Pentagon to use its AI models for “all lawful purposes.” Anthropic reportedly sought to clarify that it would not include using the model to launch weapons without human involvement or to perform surveillance on American citizens. The Pentagon was unwilling to agree to honor Anthropic’s redlines. Under a normal administration, that would likely just lead to the government moving on to another company. Under the Trump administration, though, refusal to comply makes you an enemy of the country. Trump and company moved to label Anthropic a supply chain risk, a designation typically reserved for foreign adversaries, not domestic companies. Getting slapped with that tag meant the rest of the federal government would have to stop doing business with Anthropic, which would be a blow to the company. Instead, the whole thing is in limbo—though it’s not looking great for the administration. Of course, they could just cancel the contracts and do business with less scrupulous AI companies. There are plenty willing to abandon their beliefs for a nice, fat contract, after all. #Pentagons #Case #Anthropic #IsntAnthropic,artifical intelligence,Department of Defense,Lawsuit,pentagon
Tech-news

Judge Rita Lin wasted little time pouring cold water on the federal government’s position. “I don’t see additional evidence from the government really justifying what it did. If anything, it seems like the record, in some ways, has gotten worse for the government,” she reportedly said.

She also did not seem convinced by the Pentagon’s apparent argument that it was concerned Anthropic would mess with its model to prevent the military from using it how they intended. “I don’t see evidence that Anthropic could alter the model after it was delivered or flip some kind of kill switch,” she said, per Axios.

This doesn’t come as a major surprise, given Judge Lin’s general vibe since this case landed in her court. Back in March when Anthropic first brought its challenge to the government’s designation, the judge said that “it looks like an attempt to cripple Anthropic.” She ultimately granted a temporary injunction on the government’s attempt to basically blacklist the AI firm.

You’ll recall the origin of this whole fight came earlier this year when negotiations between Anthropic and the Department of Defense fell through after the company refused to agree to a deal that would have allowed the Pentagon to use its AI models for “all lawful purposes.” Anthropic reportedly sought to clarify that it would not include using the model to launch weapons without human involvement or to perform surveillance on American citizens. The Pentagon was unwilling to agree to honor Anthropic’s redlines.

Under a normal administration, that would likely just lead to the government moving on to another company. Under the Trump administration, though, refusal to comply makes you an enemy of the country. Trump and company moved to label Anthropic a supply chain risk, a designation typically reserved for foreign adversaries, not domestic companies. Getting slapped with that tag meant the rest of the federal government would have to stop doing business with Anthropic, which would be a blow to the company.

Instead, the whole thing is in limbo—though it’s not looking great for the administration. Of course, they could just cancel the contracts and do business with less scrupulous AI companies. There are plenty willing to abandon their beliefs for a nice, fat contract, after all.

#Pentagons #Case #Anthropic #IsntAnthropic,artifical intelligence,Department of Defense,Lawsuit,pentagon">The Pentagon’s Case Against Anthropic Isn’t Going WellThe Pentagon’s Case Against Anthropic Isn’t Going Well The Department of Defense labeled AI lab Anthropic a supply-chain risk after the company refused to agree to allow the Pentagon to use its models for autonomous weapons systems and domestic surveillance. It seems the company isn’t just winning the moral argument on this front, but the legal one, too. According to Axios, the judge hearing Anthropic’s challenge to the Trump administration’s designation has thus far not found the Pentagon’s case to be particularly compelling. Per the report, U.S. District Judge Rita Lin wasted little time pouring cold water on the federal government’s position. “I don’t see additional evidence from the government really justifying what it did. If anything, it seems like the record, in some ways, has gotten worse for the government,” she reportedly said. She also did not seem convinced by the Pentagon’s apparent argument that it was concerned Anthropic would mess with its model to prevent the military from using it how they intended. “I don’t see evidence that Anthropic could alter the model after it was delivered or flip some kind of kill switch,” she said, per Axios. This doesn’t come as a major surprise, given Judge Lin’s general vibe since this case landed in her court. Back in March when Anthropic first brought its challenge to the government’s designation, the judge said that “it looks like an attempt to cripple Anthropic.” She ultimately granted a temporary injunction on the government’s attempt to basically blacklist the AI firm. You’ll recall the origin of this whole fight came earlier this year when negotiations between Anthropic and the Department of Defense fell through after the company refused to agree to a deal that would have allowed the Pentagon to use its AI models for “all lawful purposes.” Anthropic reportedly sought to clarify that it would not include using the model to launch weapons without human involvement or to perform surveillance on American citizens. The Pentagon was unwilling to agree to honor Anthropic’s redlines. Under a normal administration, that would likely just lead to the government moving on to another company. Under the Trump administration, though, refusal to comply makes you an enemy of the country. Trump and company moved to label Anthropic a supply chain risk, a designation typically reserved for foreign adversaries, not domestic companies. Getting slapped with that tag meant the rest of the federal government would have to stop doing business with Anthropic, which would be a blow to the company. Instead, the whole thing is in limbo—though it’s not looking great for the administration. Of course, they could just cancel the contracts and do business with less scrupulous AI companies. There are plenty willing to abandon their beliefs for a nice, fat contract, after all. #Pentagons #Case #Anthropic #IsntAnthropic,artifical intelligence,Department of Defense,Lawsuit,pentagon

The Department of Defense labeled AI lab Anthropic a supply-chain risk after the company refused to agree to allow the Pentagon to use its models for autonomous weapons systems and domestic surveillance. It seems the company isn’t just winning the moral argument on this front, but the legal one, too. According to Axios, the judge hearing Anthropic’s challenge to the Trump administration’s designation has thus far not found the Pentagon’s case to be particularly compelling.

Per the report, U.S. District Judge Rita Lin wasted little time pouring cold water on the federal government’s position. “I don’t see additional evidence from the government really justifying what it did. If anything, it seems like the record, in some ways, has gotten worse for the government,” she reportedly said.

She also did not seem convinced by the Pentagon’s apparent argument that it was concerned Anthropic would mess with its model to prevent the military from using it how they intended. “I don’t see evidence that Anthropic could alter the model after it was delivered or flip some kind of kill switch,” she said, per Axios.

This doesn’t come as a major surprise, given Judge Lin’s general vibe since this case landed in her court. Back in March when Anthropic first brought its challenge to the government’s designation, the judge said that “it looks like an attempt to cripple Anthropic.” She ultimately granted a temporary injunction on the government’s attempt to basically blacklist the AI firm.

You’ll recall the origin of this whole fight came earlier this year when negotiations between Anthropic and the Department of Defense fell through after the company refused to agree to a deal that would have allowed the Pentagon to use its AI models for “all lawful purposes.” Anthropic reportedly sought to clarify that it would not include using the model to launch weapons without human involvement or to perform surveillance on American citizens. The Pentagon was unwilling to agree to honor Anthropic’s redlines.

Under a normal administration, that would likely just lead to the government moving on to another company. Under the Trump administration, though, refusal to comply makes you an enemy of the country. Trump and company moved to label Anthropic a supply chain risk, a designation typically reserved for foreign adversaries, not domestic companies. Getting slapped with that tag meant the rest of the federal government would have to stop doing business with Anthropic, which would be a blow to the company.

Instead, the whole thing is in limbo—though it’s not looking great for the administration. Of course, they could just cancel the contracts and do business with less scrupulous AI companies. There are plenty willing to abandon their beliefs for a nice, fat contract, after all.

#Pentagons #Case #Anthropic #IsntAnthropic,artifical intelligence,Department of Defense,Lawsuit,pentagon

The Department of Defense labeled AI lab Anthropic a supply-chain risk after the company refused…

OpenAI, Anthropic, and other AI labs signed a petition earlier this week arguing the US should find a way to “pace” the AI race—a diplomatic way of saying the industry should have the option to coordinate a temporary pause on AI development, or slow things down if they get out of hand. OpenAI and Anthropic themselves ended up supporting the letter.

The petition arrived a week after OpenAI revealed it had caused an unprecedented cybersecurity incident in which one of its AI agents hacked into Hugging Face’s platform and several other services during internal testing.

Around the same time, top Trump administration officials started freaking out about an impressive new Chinese open weight AI model called Kimi K3, which was allegedly distilled from Anthropic’s Fable 5. In response, most of the tech industry—except Anthropic—signed onto an open letter from Nvidia asking the US government to protect open-weight AI models, arguing they’re a necessary counterbalance to their closed counterparts.

These events might look like a whole bunch of disjointed chaos. But I think they are evidence of a larger worldview taking hold in Silicon Valley, where many tech insiders are increasingly worried about OpenAI and Anthropic’s dominance. Researchers and investors I’ve talked to recently have framed the AI industry as a two-horse race that doesn’t seem to be slowing down, and that’s a cause for concern.

But different groups have their own reasons to be worried. Some OpenAI and Anthropic staffers think their employers are behaving recklessly in their pursuit to take over the market, and that the AI industry may soon develop models that are too capable for current safety methods to contain. They have said as much in public statements attached to this week’s Pacing the Frontier petition.

“I’ve seen how the relentless pace of AI makes it hard for society to keep up and how it puts pressure on labs to cut corners on safety,” Jeremy Hadfield, a research product manager at Anthropic, said in a statement attached to the petition.

For some AI employees, the Hugging Face debacle was a warning shot that demonstrated how OpenAI’s efforts to mitigate the risks of its most capable AI technology are already falling short. Granted, the incident happened when OpenAI was testing an AI model on its ability to find software exploits, and the company had intentionally turned off safeguards designed to rein in its cybersecurity capabilities.

OpenAI said in its postmortem that these tests were conducted in a sandbox, but the model ultimately gained access to the open internet. Some experts previously told WIRED that OpenAI’s security practices should have been more robust.

Other groups in Silicon Valley are more worried about power than safety. Venture capitalists, tech executives, and startup founders are concerned that OpenAI and Anthropic will simply become the next generation of Apple and Google, forcing the rest of the tech industry to play by their rules. It is slightly strange to argue that private startups with little to no profit are acting like monopolies, but that’s the lens through which many—including Mark Zuckerberg—are starting to view the two biggest AI labs.

The Meta CEO wrote a Wall Street Journal op-ed this week warning against the centralization of power in the AI industry, saying that superintelligence should be widely distributed. Zuckerberg is arguably talking out of both sides of his mouth—Meta recently decided to stop open sourcing its best AI models and instead offering them through a paid API and subscription service, just like OpenAI and Anthropic.

#Freaking #OpenAI #Anthropics #Race #Dominancemodel behavior,artificial intelligence,robotics,generative ai,anthropic,openai,ai safety"> Everyone Is Freaking Out About OpenAI and Anthropic’s Race for DominanceI was offline last week in my home state of New Jersey, but when I got back to Silicon Valley, everyone was panicking again about how quickly artificial intelligence is advancing. While this is certainly not the first time I’ve seen such concerns, it’s the biggest anxiety attack I’ve seen in years.More than 1,000 employees at OpenAI, Anthropic, and other AI labs signed a petition earlier this week arguing the US should find a way to “pace” the AI race—a diplomatic way of saying the industry should have the option to coordinate a temporary pause on AI development, or slow things down if they get out of hand. OpenAI and Anthropic themselves ended up supporting the letter.The petition arrived a week after OpenAI revealed it had caused an unprecedented cybersecurity incident in which one of its AI agents hacked into Hugging Face’s platform and several other services during internal testing.Around the same time, top Trump administration officials started freaking out about an impressive new Chinese open weight AI model called Kimi K3, which was allegedly distilled from Anthropic’s Fable 5. In response, most of the tech industry—except Anthropic—signed onto an open letter from Nvidia asking the US government to protect open-weight AI models, arguing they’re a necessary counterbalance to their closed counterparts.These events might look like a whole bunch of disjointed chaos. But I think they are evidence of a larger worldview taking hold in Silicon Valley, where many tech insiders are increasingly worried about OpenAI and Anthropic’s dominance. Researchers and investors I’ve talked to recently have framed the AI industry as a two-horse race that doesn’t seem to be slowing down, and that’s a cause for concern.But different groups have their own reasons to be worried. Some OpenAI and Anthropic staffers think their employers are behaving recklessly in their pursuit to take over the market, and that the AI industry may soon develop models that are too capable for current safety methods to contain. They have said as much in public statements attached to this week’s Pacing the Frontier petition.“I’ve seen how the relentless pace of AI makes it hard for society to keep up and how it puts pressure on labs to cut corners on safety,” Jeremy Hadfield, a research product manager at Anthropic, said in a statement attached to the petition.For some AI employees, the Hugging Face debacle was a warning shot that demonstrated how OpenAI’s efforts to mitigate the risks of its most capable AI technology are already falling short. Granted, the incident happened when OpenAI was testing an AI model on its ability to find software exploits, and the company had intentionally turned off safeguards designed to rein in its cybersecurity capabilities.OpenAI said in its postmortem that these tests were conducted in a sandbox, but the model ultimately gained access to the open internet. Some experts previously told WIRED that OpenAI’s security practices should have been more robust.Other groups in Silicon Valley are more worried about power than safety. Venture capitalists, tech executives, and startup founders are concerned that OpenAI and Anthropic will simply become the next generation of Apple and Google, forcing the rest of the tech industry to play by their rules. It is slightly strange to argue that private startups with little to no profit are acting like monopolies, but that’s the lens through which many—including Mark Zuckerberg—are starting to view the two biggest AI labs.The Meta CEO wrote a Wall Street Journal op-ed this week warning against the centralization of power in the AI industry, saying that superintelligence should be widely distributed. Zuckerberg is arguably talking out of both sides of his mouth—Meta recently decided to stop open sourcing its best AI models and instead offering them through a paid API and subscription service, just like OpenAI and Anthropic.#Freaking #OpenAI #Anthropics #Race #Dominancemodel behavior,artificial intelligence,robotics,generative ai,anthropic,openai,ai safety
Tech-news

OpenAI, Anthropic, and other AI labs signed a petition earlier this week arguing the US should find a way to “pace” the AI race—a diplomatic way of saying the industry should have the option to coordinate a temporary pause on AI development, or slow things down if they get out of hand. OpenAI and Anthropic themselves ended up supporting the letter.

The petition arrived a week after OpenAI revealed it had caused an unprecedented cybersecurity incident in which one of its AI agents hacked into Hugging Face’s platform and several other services during internal testing.

Around the same time, top Trump administration officials started freaking out about an impressive new Chinese open weight AI model called Kimi K3, which was allegedly distilled from Anthropic’s Fable 5. In response, most of the tech industry—except Anthropic—signed onto an open letter from Nvidia asking the US government to protect open-weight AI models, arguing they’re a necessary counterbalance to their closed counterparts.

These events might look like a whole bunch of disjointed chaos. But I think they are evidence of a larger worldview taking hold in Silicon Valley, where many tech insiders are increasingly worried about OpenAI and Anthropic’s dominance. Researchers and investors I’ve talked to recently have framed the AI industry as a two-horse race that doesn’t seem to be slowing down, and that’s a cause for concern.

But different groups have their own reasons to be worried. Some OpenAI and Anthropic staffers think their employers are behaving recklessly in their pursuit to take over the market, and that the AI industry may soon develop models that are too capable for current safety methods to contain. They have said as much in public statements attached to this week’s Pacing the Frontier petition.

“I’ve seen how the relentless pace of AI makes it hard for society to keep up and how it puts pressure on labs to cut corners on safety,” Jeremy Hadfield, a research product manager at Anthropic, said in a statement attached to the petition.

For some AI employees, the Hugging Face debacle was a warning shot that demonstrated how OpenAI’s efforts to mitigate the risks of its most capable AI technology are already falling short. Granted, the incident happened when OpenAI was testing an AI model on its ability to find software exploits, and the company had intentionally turned off safeguards designed to rein in its cybersecurity capabilities.

OpenAI said in its postmortem that these tests were conducted in a sandbox, but the model ultimately gained access to the open internet. Some experts previously told WIRED that OpenAI’s security practices should have been more robust.

Other groups in Silicon Valley are more worried about power than safety. Venture capitalists, tech executives, and startup founders are concerned that OpenAI and Anthropic will simply become the next generation of Apple and Google, forcing the rest of the tech industry to play by their rules. It is slightly strange to argue that private startups with little to no profit are acting like monopolies, but that’s the lens through which many—including Mark Zuckerberg—are starting to view the two biggest AI labs.

The Meta CEO wrote a Wall Street Journal op-ed this week warning against the centralization of power in the AI industry, saying that superintelligence should be widely distributed. Zuckerberg is arguably talking out of both sides of his mouth—Meta recently decided to stop open sourcing its best AI models and instead offering them through a paid API and subscription service, just like OpenAI and Anthropic.

#Freaking #OpenAI #Anthropics #Race #Dominancemodel behavior,artificial intelligence,robotics,generative ai,anthropic,openai,ai safety">Everyone Is Freaking Out About OpenAI and Anthropic’s Race for Dominance

I was offline last week in my home state of New Jersey, but when I got back to Silicon Valley, everyone was panicking again about how quickly artificial intelligence is advancing. While this is certainly not the first time I’ve seen such concerns, it’s the biggest anxiety attack I’ve seen in years.

More than 1,000 employees at OpenAI, Anthropic, and other AI labs signed a petition earlier this week arguing the US should find a way to “pace” the AI race—a diplomatic way of saying the industry should have the option to coordinate a temporary pause on AI development, or slow things down if they get out of hand. OpenAI and Anthropic themselves ended up supporting the letter.

The petition arrived a week after OpenAI revealed it had caused an unprecedented cybersecurity incident in which one of its AI agents hacked into Hugging Face’s platform and several other services during internal testing.

Around the same time, top Trump administration officials started freaking out about an impressive new Chinese open weight AI model called Kimi K3, which was allegedly distilled from Anthropic’s Fable 5. In response, most of the tech industry—except Anthropic—signed onto an open letter from Nvidia asking the US government to protect open-weight AI models, arguing they’re a necessary counterbalance to their closed counterparts.

These events might look like a whole bunch of disjointed chaos. But I think they are evidence of a larger worldview taking hold in Silicon Valley, where many tech insiders are increasingly worried about OpenAI and Anthropic’s dominance. Researchers and investors I’ve talked to recently have framed the AI industry as a two-horse race that doesn’t seem to be slowing down, and that’s a cause for concern.

But different groups have their own reasons to be worried. Some OpenAI and Anthropic staffers think their employers are behaving recklessly in their pursuit to take over the market, and that the AI industry may soon develop models that are too capable for current safety methods to contain. They have said as much in public statements attached to this week’s Pacing the Frontier petition.

“I’ve seen how the relentless pace of AI makes it hard for society to keep up and how it puts pressure on labs to cut corners on safety,” Jeremy Hadfield, a research product manager at Anthropic, said in a statement attached to the petition.

For some AI employees, the Hugging Face debacle was a warning shot that demonstrated how OpenAI’s efforts to mitigate the risks of its most capable AI technology are already falling short. Granted, the incident happened when OpenAI was testing an AI model on its ability to find software exploits, and the company had intentionally turned off safeguards designed to rein in its cybersecurity capabilities.

OpenAI said in its postmortem that these tests were conducted in a sandbox, but the model ultimately gained access to the open internet. Some experts previously told WIRED that OpenAI’s security practices should have been more robust.

Other groups in Silicon Valley are more worried about power than safety. Venture capitalists, tech executives, and startup founders are concerned that OpenAI and Anthropic will simply become the next generation of Apple and Google, forcing the rest of the tech industry to play by their rules. It is slightly strange to argue that private startups with little to no profit are acting like monopolies, but that’s the lens through which many—including Mark Zuckerberg—are starting to view the two biggest AI labs.

The Meta CEO wrote a Wall Street Journal op-ed this week warning against the centralization of power in the AI industry, saying that superintelligence should be widely distributed. Zuckerberg is arguably talking out of both sides of his mouth—Meta recently decided to stop open sourcing its best AI models and instead offering them through a paid API and subscription service, just like OpenAI and Anthropic.

#Freaking #OpenAI #Anthropics #Race #Dominancemodel behavior,artificial intelligence,robotics,generative ai,anthropic,openai,ai safety

I was offline last week in my home state of New Jersey, but when I…

eBay and several former executives agreed to pay $55.7 million to resolve the couple’s lawsuit over the 2019 corporate harassment campaign.

The Steiners are the married founders of EcommerceBytes, a news site covering eBay and the broader ecommerce industry. They filed the civil case in 2021 after members of eBay’s security team sent them threats, disturbing packages, and unwanted visitors in an effort to influence the site’s reporting.

Of the $55.7 million settlement, $48.7 million will go directly to the Steiners. EBay will pay $46.15 million, former CEO Devin Wenig will pay $2 million, former senior vice president Wendy Jones will pay $500,000, and former chief communications officer Steve Wymer will pay $50,000. The remaining $7 million will go to nonprofit organizations. EBay will contribute $6 million, while Wenig will donate another $1 million to a group protecting First Amendment rights in Ina Steiner’s name.

The agreement also allows the Steiners to keep talking publicly about the case. It contains no confidentiality provision, a priority for the couple because they wanted the settlement to discourage other corporations from trying to intimidate journalists over critical coverage.

To understand why the Steiners considered that transparency so important, it helps to go back to how the campaign began.

From critical coverage to criminal charges

When eBay’s security team began targeting the Steiners in 2019, the couple had already spent two decades covering the company and other online marketplaces, such as Amazon and Etsy. Through EcommerceBytes, they reported on the issues affecting online sellers, including fees, policy changes, and the executives making those decisions.

The internal lead-up to the campaign only became clear years later — the Steiners initially filed their civil lawsuit in July 2021 and amended it in March 2023. Ina Steiner later told Wired in July 2026 that the litigation gave the couple access to roughly 68,000 documents showing how eBay executives discussed the site behind the scenes.

Those records traced a steady escalation. According to the amended complaint, Wenig sent Wymer a link to an April 10, 2019, EcommerceBytes article about his compensation. Wymer responded, “We are going to crush this lady.”

The following month, Jones allegedly asked eBay security chief Jim Baugh to address criticism of the company “off the radar” and told him she did not want to know the details. Then, on Aug. 1, 2019, EcommerceBytes published an article questioning Wenig’s handling of eBay’s litigation against Amazon. Within half an hour, Wenig allegedly told Wymer that if they were ever going to “take her down,” referring to Ina Steiner, “now is the time.”

Four days later, the harassment campaign allegedly began. According to eBay’s admissions to federal prosecutors, members of its security team targeted the Steiners between Aug. 5 and Aug. 23, 2019. Anonymous accounts on what was then Twitter criticized EcommerceBytes and threatened to show up at the couple’s home in Natick, Massachusetts.

The campaign quickly reached their front door. In addition to the cockroaches, fetal pig, and bloody mask, the group allegedly sent live spiders, fly larvae, a funeral wreath, and a book about surviving the death of a spouse. Pornographic magazines addressed to David were allegedly delivered to a neighbor, while Craigslist ads allegedly invited strangers to the Steiners’ home for sex, a block party, and an estate sale. One night, an emergency plumber even arrived unannounced.

As the messages and deliveries continued, the language inside eBay remained aggressive. On Aug. 11, Wymer allegedly told Baugh, “I want to see ashes. As long as it takes. Whatever it takes.” The group also took the harassment offline — several members of eBay’s security team allegedly traveled from California to Massachusetts, followed the Steiners in a rented van, and attempted to install a GPS tracker on their car.

They also had an unusual plan for how the campaign would end. EBay security manager Brian Gilbert, a former police captain, was allegedly supposed to approach the Steiners and offer to stop the attacks his colleagues were secretly carrying out. EBay would then appear to have solved a problem its own employees had created.

That plan unraveled when the Steiners realized they were being followed and contacted local police. Once members of the group learned they were under investigation, they allegedly made false statements, deleted digital evidence, and falsified records in an attempt to hide eBay’s involvement.

Wenig, Wymer, and Jones were not criminally charged, and Wenig has maintained that he was requesting a communications response and knew nothing about the harassment. EBay’s internal investigation found his messages inappropriate but said it uncovered no evidence that he authorized the security team’s actions.

Federal prosecutors eventually charged seven former eBay employees and contractors in 2020, all of whom eventually pleaded guilty. Four received prison sentences between July 2021 and October 2022, including Baugh, who was sentenced to 57 months in September 2022. Two others received one year of home confinement later that year. The final defendant, Gilbert, was sentenced in July 2024 to time served and one year of supervised release.

The consequences also reached eBay itself. In January 2024, federal prosecutors charged the company with six felony offenses, including stalking, witness tampering, and obstruction of justice. EBay admitted to a detailed account of the campaign, paid the maximum penalty of $3 million, and agreed to retain an independent compliance monitor for three years.

The new settlement, though, resolves the Steiners’ civil claims against eBay, Wenig, Jones, and Wymer. The couple also reached separate settlements with the other former employees named in the lawsuit, although those terms were not disclosed.

EBay says it has changed

In a public statement published July 28, 2026, eBay called what happened “wrong, reprehensible and should never have happened.” The company condemned the employees who pleaded guilty and acknowledged the “unprofessional tone” of messages involving Wenig, Wymer, and Jones.

EBay said new leaders have joined the company since 2019 and that it has strengthened its policies, internal controls, and employee training. Wenig has continued to maintain that he knew nothing about the campaign, saying through a representative that he was saddened it happened while he was CEO.

After the packages, threats, surveillance, criminal cases, and six years of litigation, the campaign still failed at its original goal. EcommerceBytes remains online, and Ina Steiner got to publish the news of eBay’s settlement herself. Talk about closure!

#EBay #pay #million #journalists #cyberstalking #case"> EBay to pay .7 million in journalists’ cyberstalking case Critical coverage usually draws an angry email or two. For Ina and David Steiner, it led to live cockroaches, a fetal pig, and a bloody Halloween mask.On Monday, July 27, eBay and several former executives agreed to pay .7 million to resolve the couple’s lawsuit over the 2019 corporate harassment campaign.The Steiners are the married founders of EcommerceBytes, a news site covering eBay and the broader ecommerce industry. They filed the civil case in 2021 after members of eBay’s security team sent them threats, disturbing packages, and unwanted visitors in an effort to influence the site’s reporting. Of the .7 million settlement, .7 million will go directly to the Steiners. EBay will pay .15 million, former CEO Devin Wenig will pay million, former senior vice president Wendy Jones will pay 0,000, and former chief communications officer Steve Wymer will pay ,000. The remaining million will go to nonprofit organizations. EBay will contribute million, while Wenig will donate another million to a group protecting First Amendment rights in Ina Steiner’s name.The agreement also allows the Steiners to keep talking publicly about the case. It contains no confidentiality provision, a priority for the couple because they wanted the settlement to discourage other corporations from trying to intimidate journalists over critical coverage.To understand why the Steiners considered that transparency so important, it helps to go back to how the campaign began.From critical coverage to criminal chargesWhen eBay’s security team began targeting the Steiners in 2019, the couple had already spent two decades covering the company and other online marketplaces, such as Amazon and Etsy. Through EcommerceBytes, they reported on the issues affecting online sellers, including fees, policy changes, and the executives making those decisions.The internal lead-up to the campaign only became clear years later — the Steiners initially filed their civil lawsuit in July 2021 and amended it in March 2023. Ina Steiner later told Wired in July 2026 that the litigation gave the couple access to roughly 68,000 documents showing how eBay executives discussed the site behind the scenes.Those records traced a steady escalation. According to the amended complaint, Wenig sent Wymer a link to an April 10, 2019, EcommerceBytes article about his compensation. Wymer responded, “We are going to crush this lady.” Mashable Light Speed The following month, Jones allegedly asked eBay security chief Jim Baugh to address criticism of the company “off the radar” and told him she did not want to know the details. Then, on Aug. 1, 2019, EcommerceBytes published an article questioning Wenig’s handling of eBay’s litigation against Amazon. Within half an hour, Wenig allegedly told Wymer that if they were ever going to “take her down,” referring to Ina Steiner, “now is the time.” This Tweet is currently unavailable. It might be loading or has been removed. Four days later, the harassment campaign allegedly began. According to eBay’s admissions to federal prosecutors, members of its security team targeted the Steiners between Aug. 5 and Aug. 23, 2019. Anonymous accounts on what was then Twitter criticized EcommerceBytes and threatened to show up at the couple’s home in Natick, Massachusetts.The campaign quickly reached their front door. In addition to the cockroaches, fetal pig, and bloody mask, the group allegedly sent live spiders, fly larvae, a funeral wreath, and a book about surviving the death of a spouse. Pornographic magazines addressed to David were allegedly delivered to a neighbor, while Craigslist ads allegedly invited strangers to the Steiners’ home for sex, a block party, and an estate sale. One night, an emergency plumber even arrived unannounced.As the messages and deliveries continued, the language inside eBay remained aggressive. On Aug. 11, Wymer allegedly told Baugh, “I want to see ashes. As long as it takes. Whatever it takes.” The group also took the harassment offline — several members of eBay’s security team allegedly traveled from California to Massachusetts, followed the Steiners in a rented van, and attempted to install a GPS tracker on their car. This Tweet is currently unavailable. It might be loading or has been removed. They also had an unusual plan for how the campaign would end. EBay security manager Brian Gilbert, a former police captain, was allegedly supposed to approach the Steiners and offer to stop the attacks his colleagues were secretly carrying out. EBay would then appear to have solved a problem its own employees had created.That plan unraveled when the Steiners realized they were being followed and contacted local police. Once members of the group learned they were under investigation, they allegedly made false statements, deleted digital evidence, and falsified records in an attempt to hide eBay’s involvement. This Tweet is currently unavailable. It might be loading or has been removed. Wenig, Wymer, and Jones were not criminally charged, and Wenig has maintained that he was requesting a communications response and knew nothing about the harassment. EBay’s internal investigation found his messages inappropriate but said it uncovered no evidence that he authorized the security team’s actions.Federal prosecutors eventually charged seven former eBay employees and contractors in 2020, all of whom eventually pleaded guilty. Four received prison sentences between July 2021 and October 2022, including Baugh, who was sentenced to 57 months in September 2022. Two others received one year of home confinement later that year. The final defendant, Gilbert, was sentenced in July 2024 to time served and one year of supervised release. This Tweet is currently unavailable. It might be loading or has been removed. The consequences also reached eBay itself. In January 2024, federal prosecutors charged the company with six felony offenses, including stalking, witness tampering, and obstruction of justice. EBay admitted to a detailed account of the campaign, paid the maximum penalty of million, and agreed to retain an independent compliance monitor for three years.The new settlement, though, resolves the Steiners’ civil claims against eBay, Wenig, Jones, and Wymer. The couple also reached separate settlements with the other former employees named in the lawsuit, although those terms were not disclosed.EBay says it has changedIn a public statement published July 28, 2026, eBay called what happened “wrong, reprehensible and should never have happened.” The company condemned the employees who pleaded guilty and acknowledged the “unprofessional tone” of messages involving Wenig, Wymer, and Jones.EBay said new leaders have joined the company since 2019 and that it has strengthened its policies, internal controls, and employee training. Wenig has continued to maintain that he knew nothing about the campaign, saying through a representative that he was saddened it happened while he was CEO.After the packages, threats, surveillance, criminal cases, and six years of litigation, the campaign still failed at its original goal. EcommerceBytes remains online, and Ina Steiner got to publish the news of eBay’s settlement herself. Talk about closure! #EBay #pay #million #journalists #cyberstalking #case
Tech-news

eBay and several former executives agreed to pay $55.7 million to resolve the couple’s lawsuit over the 2019 corporate harassment campaign.

The Steiners are the married founders of EcommerceBytes, a news site covering eBay and the broader ecommerce industry. They filed the civil case in 2021 after members of eBay’s security team sent them threats, disturbing packages, and unwanted visitors in an effort to influence the site’s reporting.

Of the $55.7 million settlement, $48.7 million will go directly to the Steiners. EBay will pay $46.15 million, former CEO Devin Wenig will pay $2 million, former senior vice president Wendy Jones will pay $500,000, and former chief communications officer Steve Wymer will pay $50,000. The remaining $7 million will go to nonprofit organizations. EBay will contribute $6 million, while Wenig will donate another $1 million to a group protecting First Amendment rights in Ina Steiner’s name.

The agreement also allows the Steiners to keep talking publicly about the case. It contains no confidentiality provision, a priority for the couple because they wanted the settlement to discourage other corporations from trying to intimidate journalists over critical coverage.

To understand why the Steiners considered that transparency so important, it helps to go back to how the campaign began.

From critical coverage to criminal charges

When eBay’s security team began targeting the Steiners in 2019, the couple had already spent two decades covering the company and other online marketplaces, such as Amazon and Etsy. Through EcommerceBytes, they reported on the issues affecting online sellers, including fees, policy changes, and the executives making those decisions.

The internal lead-up to the campaign only became clear years later — the Steiners initially filed their civil lawsuit in July 2021 and amended it in March 2023. Ina Steiner later told Wired in July 2026 that the litigation gave the couple access to roughly 68,000 documents showing how eBay executives discussed the site behind the scenes.

Those records traced a steady escalation. According to the amended complaint, Wenig sent Wymer a link to an April 10, 2019, EcommerceBytes article about his compensation. Wymer responded, “We are going to crush this lady.”

The following month, Jones allegedly asked eBay security chief Jim Baugh to address criticism of the company “off the radar” and told him she did not want to know the details. Then, on Aug. 1, 2019, EcommerceBytes published an article questioning Wenig’s handling of eBay’s litigation against Amazon. Within half an hour, Wenig allegedly told Wymer that if they were ever going to “take her down,” referring to Ina Steiner, “now is the time.”

Four days later, the harassment campaign allegedly began. According to eBay’s admissions to federal prosecutors, members of its security team targeted the Steiners between Aug. 5 and Aug. 23, 2019. Anonymous accounts on what was then Twitter criticized EcommerceBytes and threatened to show up at the couple’s home in Natick, Massachusetts.

The campaign quickly reached their front door. In addition to the cockroaches, fetal pig, and bloody mask, the group allegedly sent live spiders, fly larvae, a funeral wreath, and a book about surviving the death of a spouse. Pornographic magazines addressed to David were allegedly delivered to a neighbor, while Craigslist ads allegedly invited strangers to the Steiners’ home for sex, a block party, and an estate sale. One night, an emergency plumber even arrived unannounced.

As the messages and deliveries continued, the language inside eBay remained aggressive. On Aug. 11, Wymer allegedly told Baugh, “I want to see ashes. As long as it takes. Whatever it takes.” The group also took the harassment offline — several members of eBay’s security team allegedly traveled from California to Massachusetts, followed the Steiners in a rented van, and attempted to install a GPS tracker on their car.

They also had an unusual plan for how the campaign would end. EBay security manager Brian Gilbert, a former police captain, was allegedly supposed to approach the Steiners and offer to stop the attacks his colleagues were secretly carrying out. EBay would then appear to have solved a problem its own employees had created.

That plan unraveled when the Steiners realized they were being followed and contacted local police. Once members of the group learned they were under investigation, they allegedly made false statements, deleted digital evidence, and falsified records in an attempt to hide eBay’s involvement.

Wenig, Wymer, and Jones were not criminally charged, and Wenig has maintained that he was requesting a communications response and knew nothing about the harassment. EBay’s internal investigation found his messages inappropriate but said it uncovered no evidence that he authorized the security team’s actions.

Federal prosecutors eventually charged seven former eBay employees and contractors in 2020, all of whom eventually pleaded guilty. Four received prison sentences between July 2021 and October 2022, including Baugh, who was sentenced to 57 months in September 2022. Two others received one year of home confinement later that year. The final defendant, Gilbert, was sentenced in July 2024 to time served and one year of supervised release.

The consequences also reached eBay itself. In January 2024, federal prosecutors charged the company with six felony offenses, including stalking, witness tampering, and obstruction of justice. EBay admitted to a detailed account of the campaign, paid the maximum penalty of $3 million, and agreed to retain an independent compliance monitor for three years.

The new settlement, though, resolves the Steiners’ civil claims against eBay, Wenig, Jones, and Wymer. The couple also reached separate settlements with the other former employees named in the lawsuit, although those terms were not disclosed.

EBay says it has changed

In a public statement published July 28, 2026, eBay called what happened “wrong, reprehensible and should never have happened.” The company condemned the employees who pleaded guilty and acknowledged the “unprofessional tone” of messages involving Wenig, Wymer, and Jones.

EBay said new leaders have joined the company since 2019 and that it has strengthened its policies, internal controls, and employee training. Wenig has continued to maintain that he knew nothing about the campaign, saying through a representative that he was saddened it happened while he was CEO.

After the packages, threats, surveillance, criminal cases, and six years of litigation, the campaign still failed at its original goal. EcommerceBytes remains online, and Ina Steiner got to publish the news of eBay’s settlement herself. Talk about closure!

#EBay #pay #million #journalists #cyberstalking #case">EBay to pay $55.7 million in journalists’ cyberstalking case

Critical coverage usually draws an angry email or two. For Ina and David Steiner, it led to live cockroaches, a fetal pig, and a bloody Halloween mask.

On Monday, July 27, eBay and several former executives agreed to pay $55.7 million to resolve the couple’s lawsuit over the 2019 corporate harassment campaign.

The Steiners are the married founders of EcommerceBytes, a news site covering eBay and the broader ecommerce industry. They filed the civil case in 2021 after members of eBay’s security team sent them threats, disturbing packages, and unwanted visitors in an effort to influence the site’s reporting.

Of the $55.7 million settlement, $48.7 million will go directly to the Steiners. EBay will pay $46.15 million, former CEO Devin Wenig will pay $2 million, former senior vice president Wendy Jones will pay $500,000, and former chief communications officer Steve Wymer will pay $50,000. The remaining $7 million will go to nonprofit organizations. EBay will contribute $6 million, while Wenig will donate another $1 million to a group protecting First Amendment rights in Ina Steiner’s name.

The agreement also allows the Steiners to keep talking publicly about the case. It contains no confidentiality provision, a priority for the couple because they wanted the settlement to discourage other corporations from trying to intimidate journalists over critical coverage.

To understand why the Steiners considered that transparency so important, it helps to go back to how the campaign began.

From critical coverage to criminal charges

When eBay’s security team began targeting the Steiners in 2019, the couple had already spent two decades covering the company and other online marketplaces, such as Amazon and Etsy. Through EcommerceBytes, they reported on the issues affecting online sellers, including fees, policy changes, and the executives making those decisions.

The internal lead-up to the campaign only became clear years later — the Steiners initially filed their civil lawsuit in July 2021 and amended it in March 2023. Ina Steiner later told Wired in July 2026 that the litigation gave the couple access to roughly 68,000 documents showing how eBay executives discussed the site behind the scenes.

Those records traced a steady escalation. According to the amended complaint, Wenig sent Wymer a link to an April 10, 2019, EcommerceBytes article about his compensation. Wymer responded, “We are going to crush this lady.”

The following month, Jones allegedly asked eBay security chief Jim Baugh to address criticism of the company “off the radar” and told him she did not want to know the details. Then, on Aug. 1, 2019, EcommerceBytes published an article questioning Wenig’s handling of eBay’s litigation against Amazon. Within half an hour, Wenig allegedly told Wymer that if they were ever going to “take her down,” referring to Ina Steiner, “now is the time.”

Four days later, the harassment campaign allegedly began. According to eBay’s admissions to federal prosecutors, members of its security team targeted the Steiners between Aug. 5 and Aug. 23, 2019. Anonymous accounts on what was then Twitter criticized EcommerceBytes and threatened to show up at the couple’s home in Natick, Massachusetts.

The campaign quickly reached their front door. In addition to the cockroaches, fetal pig, and bloody mask, the group allegedly sent live spiders, fly larvae, a funeral wreath, and a book about surviving the death of a spouse. Pornographic magazines addressed to David were allegedly delivered to a neighbor, while Craigslist ads allegedly invited strangers to the Steiners’ home for sex, a block party, and an estate sale. One night, an emergency plumber even arrived unannounced.

As the messages and deliveries continued, the language inside eBay remained aggressive. On Aug. 11, Wymer allegedly told Baugh, “I want to see ashes. As long as it takes. Whatever it takes.” The group also took the harassment offline — several members of eBay’s security team allegedly traveled from California to Massachusetts, followed the Steiners in a rented van, and attempted to install a GPS tracker on their car.

They also had an unusual plan for how the campaign would end. EBay security manager Brian Gilbert, a former police captain, was allegedly supposed to approach the Steiners and offer to stop the attacks his colleagues were secretly carrying out. EBay would then appear to have solved a problem its own employees had created.

That plan unraveled when the Steiners realized they were being followed and contacted local police. Once members of the group learned they were under investigation, they allegedly made false statements, deleted digital evidence, and falsified records in an attempt to hide eBay’s involvement.

Wenig, Wymer, and Jones were not criminally charged, and Wenig has maintained that he was requesting a communications response and knew nothing about the harassment. EBay’s internal investigation found his messages inappropriate but said it uncovered no evidence that he authorized the security team’s actions.

Federal prosecutors eventually charged seven former eBay employees and contractors in 2020, all of whom eventually pleaded guilty. Four received prison sentences between July 2021 and October 2022, including Baugh, who was sentenced to 57 months in September 2022. Two others received one year of home confinement later that year. The final defendant, Gilbert, was sentenced in July 2024 to time served and one year of supervised release.

The consequences also reached eBay itself. In January 2024, federal prosecutors charged the company with six felony offenses, including stalking, witness tampering, and obstruction of justice. EBay admitted to a detailed account of the campaign, paid the maximum penalty of $3 million, and agreed to retain an independent compliance monitor for three years.

The new settlement, though, resolves the Steiners’ civil claims against eBay, Wenig, Jones, and Wymer. The couple also reached separate settlements with the other former employees named in the lawsuit, although those terms were not disclosed.

EBay says it has changed

In a public statement published July 28, 2026, eBay called what happened “wrong, reprehensible and should never have happened.” The company condemned the employees who pleaded guilty and acknowledged the “unprofessional tone” of messages involving Wenig, Wymer, and Jones.

EBay said new leaders have joined the company since 2019 and that it has strengthened its policies, internal controls, and employee training. Wenig has continued to maintain that he knew nothing about the campaign, saying through a representative that he was saddened it happened while he was CEO.

After the packages, threats, surveillance, criminal cases, and six years of litigation, the campaign still failed at its original goal. EcommerceBytes remains online, and Ina Steiner got to publish the news of eBay’s settlement herself. Talk about closure!

#EBay #pay #million #journalists #cyberstalking #case

Critical coverage usually draws an angry email or two. For Ina and David Steiner, it…

announced it has granted the Amazon-owned Zoox a temporary exemption, allowing it to deploy up to 2,500 vehicles annually over the next two years, as reported earlier by Reuters.

In its decision, the NHTSA says it determined that Zoox robotaxis “have an equivalent or greater level of motor vehicle safety” compared to vehicles compliant with federal vehicle safety standards. Under the exemption, Zoox will be subject to “an enhanced oversight condition” that “may update and expand” as the company’s self-driving technology evolves. Zoox issued a software recall for its vehicles earlier this month over concerns that they may not detect smoke.

#Zoox #charge #rides #steeringwheelfree #robotaxisAmazon,Autonomous Cars,Electric Cars,News,Tech,Transportation"> Zoox can now charge for rides in its steering-wheel-free robotaxisZoox just got permission to charge for robotaxi rides in its boxy, steering-wheel-less vehicles. On Thursday, the National Highway Traffic Safety Administration announced it has granted the Amazon-owned Zoox a temporary exemption, allowing it to deploy up to 2,500 vehicles annually over the next two years, as reported earlier by Reuters.In its decision, the NHTSA says it determined that Zoox robotaxis “have an equivalent or greater level of motor vehicle safety” compared to vehicles compliant with federal vehicle safety standards. Under the exemption, Zoox will be subject to “an enhanced oversight condition” that “may update and expand” as the company’s self-driving technology evolves. Zoox issued a software recall for its vehicles earlier this month over concerns that they may not detect smoke.#Zoox #charge #rides #steeringwheelfree #robotaxisAmazon,Autonomous Cars,Electric Cars,News,Tech,Transportation
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announced it has granted the Amazon-owned Zoox a temporary exemption, allowing it to deploy up to 2,500 vehicles annually over the next two years, as reported earlier by Reuters.

In its decision, the NHTSA says it determined that Zoox robotaxis “have an equivalent or greater level of motor vehicle safety” compared to vehicles compliant with federal vehicle safety standards. Under the exemption, Zoox will be subject to “an enhanced oversight condition” that “may update and expand” as the company’s self-driving technology evolves. Zoox issued a software recall for its vehicles earlier this month over concerns that they may not detect smoke.

#Zoox #charge #rides #steeringwheelfree #robotaxisAmazon,Autonomous Cars,Electric Cars,News,Tech,Transportation">Zoox can now charge for rides in its steering-wheel-free robotaxis

Zoox just got permission to charge for robotaxi rides in its boxy, steering-wheel-less vehicles. On Thursday, the National Highway Traffic Safety Administration announced it has granted the Amazon-owned Zoox a temporary exemption, allowing it to deploy up to 2,500 vehicles annually over the next two years, as reported earlier by Reuters.

In its decision, the NHTSA says it determined that Zoox robotaxis “have an equivalent or greater level of motor vehicle safety” compared to vehicles compliant with federal vehicle safety standards. Under the exemption, Zoox will be subject to “an enhanced oversight condition” that “may update and expand” as the company’s self-driving technology evolves. Zoox issued a software recall for its vehicles earlier this month over concerns that they may not detect smoke.

#Zoox #charge #rides #steeringwheelfree #robotaxisAmazon,Autonomous Cars,Electric Cars,News,Tech,Transportation

Zoox just got permission to charge for robotaxi rides in its boxy, steering-wheel-less vehicles. On…