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A New Algorithm Makes It Faster to Find the Shortest Paths

A New Algorithm Makes It Faster to Find the Shortest Paths

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The original version of this story appeared in Quanta Magazine.

If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle the easiest pieces first. But this kind of sorting has a cost. You may end up spending too much time putting the pieces in order.

This dilemma is especially relevant to one of the most iconic problems in computer science: finding the shortest path from a specific starting point in a network to every other point. It’s like a souped-up version of a problem you need to solve each time you move: learning the best route from your new home to work, the gym, and the supermarket.

“Shortest paths is a beautiful problem that anyone in the world can relate to,” said Mikkel Thorup, a computer scientist at the University of Copenhagen.

Intuitively, it should be easiest to find the shortest path to nearby destinations. So if you want to design the fastest possible algorithm for the shortest-paths problem, it seems reasonable to start by finding the closest point, then the next-closest, and so on. But to do that, you need to repeatedly figure out which point is closest. You’ll sort the points by distance as you go. There’s a fundamental speed limit for any algorithm that follows this approach: You can’t go any faster than the time it takes to sort.

Forty years ago, researchers designing shortest-paths algorithms ran up against this “sorting barrier.” Now, a team of researchers has devised a new algorithm that breaks it. It doesn’t sort, and it runs faster than any algorithm that does.

“The authors were audacious in thinking they could break this barrier,” said Robert Tarjan, a computer scientist at Princeton University. “It’s an amazing result.”

The Frontier of Knowledge

To analyze the shortest-paths problem mathematically, researchers use the language of graphs—networks of points, or nodes, connected by lines. Each link between nodes is labeled with a number called its weight, which can represent the length of that segment or the time needed to traverse it. There are usually many routes between any two nodes, and the shortest is the one whose weights add up to the smallest number. Given a graph and a specific “source” node, an algorithm’s goal is to find the shortest path to every other node.

The most famous shortest-paths algorithm, devised by the pioneering computer scientist Edsger Dijkstra in 1956, starts at the source and works outward step by step. It’s an effective approach, because knowing the shortest path to nearby nodes can help you find the shortest paths to more distant ones. But because the end result is a sorted list of shortest paths, the sorting barrier sets a fundamental limit on how fast the algorithm can run.

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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">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

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

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">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

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

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

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

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