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Japan’s Flagship H3 Rocket Suffers Engine Bust, Fails to Deliver Satellite

Japan’s Flagship H3 Rocket Suffers Engine Bust, Fails to Deliver Satellite

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Japan’s H3 rocket lifted off for its seventh mission on Sunday, but an engine failure foiled its attempt to insert a navigation satellite in geostationary orbit.

Japan Aerospace Exploration Agency (JAXA) revealed that its flagship rocket’s second-stage engine suffered an anomaly shortly after launch, causing it to shut down prematurely. The rocket was carrying the Michibiki 5 satellite, part of Japan’s regional navigation satellite system in geosynchronous orbit.

The space agency has already set up a special task force headed by JAXA president Hiroshi Yamakawa and “started investigations to find out the cause,” it wrote in a statement.

Japan’s H3 rocket suffered an anomaly during its inaugural launch in 2023, also due to an issue with its second stage. The recent engine failure is a major setback for Japan’s space program, casting uncertainty over several H3 launches scheduled for the coming year.

Failure to launch

The H3 rocket launched on Sunday at 8:51 p.m. ET from the Tanegashima Space Center, located on a southwestern Japanese island. The rocket’s second-stage engine burn failed to ignite on time, resulting in an unplanned shutdown. The onboard satellite, also known as QSZ-5, did not reach its designated orbit and was reportedly lost.

During a press conference, JAXA stated that telemetry data showed pressure in the second stage’s hydrogen tank began dropping during the first stage engine burn. As a result, the first stage engine cutoff took place 27 seconds later than planned, delaying the second ignition by 15 seconds. It’s not yet clear if the satellite separated from the rocket.

The launch of the QSZ-5 satellite was originally planned for December 17 but was delayed “because an uncertain incident was found in the cooling water injection equipment,” JAXA wrote in a statement on Friday.

The 207-foot-tall (63-meter) rocket is due to launch another QSZ satellite in 2026, as well as Japan’s HTV-X cargo spacecraft. Japan’s Martian Moons eXploration (MMX) mission is also scheduled to launch on board the H3 rocket in late 2026.

Japan’s H3 rocket was 11 years in the making, a successor to the H-2A, which the agency retired in June. The expendable rocket had a rocky start, forcing a dreaded self-destruct command just 15 minutes after its inaugural launch on March 6, 2023. Although the rocket’s first stage worked as planned, an electrical glitch caused the second stage to fail to ignite. The failure resulted in the loss of the $200 million ALOS-3 advanced Earth-observing satellite.

Since its failed first launch, however, H3 has pulled off five successful missions to date. Still, the latest engine failure puts a wrench in Japan’s spaceflight plans, with JAXA aiming for at least two H3 launches per year. The scheduled launches for 2026 now appear to be in limbo, pending the results of the investigation.

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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

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

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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:

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  • support for different operating systems;
  • connecting additional IP addresses;
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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.

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  • isolation of virtual servers;
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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.

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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.

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#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. 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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;
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  • drive type;
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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

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 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

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

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">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

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

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