The White House is asking OpenAI to slow roll the release of its new model over safety concerns | TechCrunch
OpenAI’s release of its newest model, GPT 5.6, reportedly won’t be like its previous releases. Instead of distributing it to the public, the company plans to share it only with a select group of close partners because the Trump administration told it to, reports The Information.
At a meeting this week, CEO Sam Altman reportedly told staff that the government would be “approving access customer by customer” during a preview period. Altman reportedly added that if the limited release goes well, OpenAI hopes to follow with a general, broader release a “couple of weeks later.”
In other words, the Trump administration appears to be pressuring OpenAI to do what Anthropic is already voluntarily doing: keeping its most powerful AI models under wraps.
According to The Information, OpenAI’s new model is not only being reviewed by the administration, but its staffers also “worked closely” with the government on the upcoming release. The agencies that reportedly asked for a limited release were the Office of the National Cyber Director and the Office of Science and Technology Policy.
The Trump administration — which originally positioned itself as taking a “hands off” approach to AI — has in recent months pushed for federal oversight of new models. Earlier this month, Trump signed an executive order directing certain AI companies to voluntarily submit new models to the government for testing and evaluation before releasing them publicly.
Earlier this year, Anthropic sparked no small amount of controversy when it announced that its new frontier cyber model, Claude Mythos, would only be released to a small coterie of partners through a program called Project Glasswing. Anthropic argued that its model was simply too powerful and could, in the wrong hands, cause more harm than good. Observers have since debated whether Anthropic’s rhetoric is a mere marketing gimmick or a legitimate attempt to keep a powerful model from being misused. The answer may be somewhere in between.
Cybercriminals have used automated tools for a very long time, but in the age of generative AI, they now have more digital ammunition than ever before. LLMs have proven adept at writing malware, and some can even execute entire ransomware attacks autonomously.
The specific concern with frontier cyber tools like Mythos is that they are ostensibly capable of both identifying and exploiting software vulnerabilities at speeds that no human analyst could match. Since many software systems contain hidden bugs that act as entry points into enterprise networks, this obviously poses an obvious and significant problem for any organization running complex software infrastructure. That said, since these models remain closed to the public, it’s difficult to tell just how much of a threat they really are.
OpenAI’s release of its newest model, GPT 5.6, reportedly won’t be like its previous releases. Instead of distributing it to the public, the company plans to share it only with a select group of close partners because the Trump administration told it to, reports The Information.
At a meeting this week, CEO Sam Altman reportedly told staff that the government would be “approving access customer by customer” during a preview period. Altman reportedly added that if the limited release goes well, OpenAI hopes to follow with a general, broader release a “couple of weeks later.”
In other words, the Trump administration appears to be pressuring OpenAI to do what Anthropic is already voluntarily doing: keeping its most powerful AI models under wraps.
According to The Information, OpenAI’s new model is not only being reviewed by the administration, but its staffers also “worked closely” with the government on the upcoming release. The agencies that reportedly asked for a limited release were the Office of the National Cyber Director and the Office of Science and Technology Policy.
The Trump administration — which originally positioned itself as taking a “hands off” approach to AI — has in recent months pushed for federal oversight of new models. Earlier this month, Trump signed an executive order directing certain AI companies to voluntarily submit new models to the government for testing and evaluation before releasing them publicly.
Earlier this year, Anthropic sparked no small amount of controversy when it announced that its new frontier cyber model, Claude Mythos, would only be released to a small coterie of partners through a program called Project Glasswing. Anthropic argued that its model was simply too powerful and could, in the wrong hands, cause more harm than good. Observers have since debated whether Anthropic’s rhetoric is a mere marketing gimmick or a legitimate attempt to keep a powerful model from being misused. The answer may be somewhere in between.
Cybercriminals have used automated tools for a very long time, but in the age of generative AI, they now have more digital ammunition than ever before. LLMs have proven adept at writing malware, and some can even execute entire ransomware attacks autonomously.
The specific concern with frontier cyber tools like Mythos is that they are ostensibly capable of both identifying and exploiting software vulnerabilities at speeds that no human analyst could match. Since many software systems contain hidden bugs that act as entry points into enterprise networks, this obviously poses an obvious and significant problem for any organization running complex software infrastructure. That said, since these models remain closed to the public, it’s difficult to tell just how much of a threat they really are.
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#White #House #OpenAI #slow #roll #release #model #safety #concerns #TechCrunchAnthropic,Mythos,OpenAI,sam altman,Trump
![IBM Crosses One of Computing’s Biggest Barriers With World’s First Sub-1 Nanometer Chip
In a major breakthrough, IBM revealed the world’s first semiconductor chip technology built on a sub-1 nanometer chipmaking process. For comparison, the process uses transistor features smaller than the width of a DNA strand, which measures about 2.5 nanometers across. The chip itself is about the size of a fingernail but holds almost 100 billion transistors, and the company expects it could enter markets as early as the next five years. In a statement released today, IBM said the new chip features nearly twice the density of its 2-nanometer chip, released in 2021. According to an accompanying technical report, the chip also demonstrated up to 70% greater energy efficiency than its predecessor. In designing the chip, researchers developed an “entirely new transistor architecture” called nanostack, which “vertically stacks and staggers transistors” to enable IBM’s 0.7-nanometer chip technology, IBM explained. A section of the chip seen with a transmission electron microscope. Credit: IBM “With our new nanostack architecture, we’re not just making smaller transistors,” Jay Gambetta, director of IBM Research, said in the statement. “We’re reinventing how chips are built to deliver dramatically more power and energy efficiency.”
Smaller and smaller Semiconductor chips enable things like computers, home appliances, communications, and transportation devices. In 1965, Intel co-founder Gordon Moore surmised that transistor capacities evolved at a predictable and consistent rate. Specifically, all things considered, the number of transistors on a semiconductor chip would double about every two years. For a while, the so-called Moore’s Law held rather well—until, that is, things hit a literal wall.
“Moore’s Law was never meant to last forever,” according to a blog post by the Massachusetts Institute of Technology’s (MIT) Computer Science and Artificial Intelligence Lab. “Transistors can only get so small and, eventually, the more permanent laws of physics get in the way.” That is, as companies try to cram more transistors into smaller chips, new advances in transistor technology take longer than two years, so Moore’s Law has been over since at least 2016, Charles Leiserson, a computer scientist at MIT, said in the blog. Accordingly, the issue now is to consider how improvements in chip performance fit into a longer-term picture, Willy Shih, an economist at Harvard Business School, said in an explainer.
Reaching atomic levels In that sense, IBM’s latest chip represents an inventive approach for bypassing the limits of physical scaling. Specifically, two wafers with nanosheet-style transistors are glued together like a sandwich to vertically stack two layers of transistors, and related technical assessments suggested that the wafer stacking was flexible and scalable enough to support real computation, Huiming Bu, vice president of IBM’s silicon technology research team, said in a press briefing on the chip. Researcher holding IBM’s sub-1 nm node wafer. Credit: IBM That said, this chip isn’t quite ready for manufacturing just yet. The company’s goal is to enter production in the next five years, but there’s still work to be done. For instance, Bu pointed out that the team was still working on pathways to prevent thermal noise or integration into existing systems in the high-performance computing community. “From my perspective, I hope to see it be as successful as the 2-nanometer [chip] and become the industry platform,” Gambetta said during the briefing. “And as we see with AI and classical computing in general, we are only seeing more and more consumption.” #IBM #Crosses #Computings #Biggest #Barriers #Worlds #Sub1 #Nanometer #ChipIBM,Semiconductors,transistors](https://gizmodo.com/app/uploads/2026/06/nanostacking-ibm-sub-nm-chip-1280x720.jpg "IBM Crosses One of Computing’s Biggest Barriers With World’s First Sub-1 Nanometer Chip
In a major breakthrough, IBM revealed the world’s first semiconductor chip technology built on a sub-1 nanometer chipmaking process. For comparison, the process uses transistor features smaller than the width of a DNA strand, which measures about 2.5 nanometers across. The chip itself is about the size of a fingernail but holds almost 100 billion transistors, and the company expects it could enter markets as early as the next five years. In a statement released today, IBM said the new chip features nearly twice the density of its 2-nanometer chip, released in 2021. According to an accompanying technical report, the chip also demonstrated up to 70% greater energy efficiency than its predecessor. In designing the chip, researchers developed an “entirely new transistor architecture” called nanostack, which “vertically stacks and staggers transistors” to enable IBM’s 0.7-nanometer chip technology, IBM explained. A section of the chip seen with a transmission electron microscope. Credit: IBM “With our new nanostack architecture, we’re not just making smaller transistors,” Jay Gambetta, director of IBM Research, said in the statement. “We’re reinventing how chips are built to deliver dramatically more power and energy efficiency.”
Smaller and smaller Semiconductor chips enable things like computers, home appliances, communications, and transportation devices. In 1965, Intel co-founder Gordon Moore surmised that transistor capacities evolved at a predictable and consistent rate. Specifically, all things considered, the number of transistors on a semiconductor chip would double about every two years. For a while, the so-called Moore’s Law held rather well—until, that is, things hit a literal wall.
“Moore’s Law was never meant to last forever,” according to a blog post by the Massachusetts Institute of Technology’s (MIT) Computer Science and Artificial Intelligence Lab. “Transistors can only get so small and, eventually, the more permanent laws of physics get in the way.” That is, as companies try to cram more transistors into smaller chips, new advances in transistor technology take longer than two years, so Moore’s Law has been over since at least 2016, Charles Leiserson, a computer scientist at MIT, said in the blog. Accordingly, the issue now is to consider how improvements in chip performance fit into a longer-term picture, Willy Shih, an economist at Harvard Business School, said in an explainer.
Reaching atomic levels In that sense, IBM’s latest chip represents an inventive approach for bypassing the limits of physical scaling. Specifically, two wafers with nanosheet-style transistors are glued together like a sandwich to vertically stack two layers of transistors, and related technical assessments suggested that the wafer stacking was flexible and scalable enough to support real computation, Huiming Bu, vice president of IBM’s silicon technology research team, said in a press briefing on the chip. Researcher holding IBM’s sub-1 nm node wafer. Credit: IBM That said, this chip isn’t quite ready for manufacturing just yet. The company’s goal is to enter production in the next five years, but there’s still work to be done. For instance, Bu pointed out that the team was still working on pathways to prevent thermal noise or integration into existing systems in the high-performance computing community. “From my perspective, I hope to see it be as successful as the 2-nanometer [chip] and become the industry platform,” Gambetta said during the briefing. “And as we see with AI and classical computing in general, we are only seeing more and more consumption.” #IBM #Crosses #Computings #Biggest #Barriers #Worlds #Sub1 #Nanometer #ChipIBM,Semiconductors,transistors")
![IBM Crosses One of Computing’s Biggest Barriers With World’s First Sub-1 Nanometer Chip
In a major breakthrough, IBM revealed the world’s first semiconductor chip technology built on a sub-1 nanometer chipmaking process. For comparison, the process uses transistor features smaller than the width of a DNA strand, which measures about 2.5 nanometers across. The chip itself is about the size of a fingernail but holds almost 100 billion transistors, and the company expects it could enter markets as early as the next five years. In a statement released today, IBM said the new chip features nearly twice the density of its 2-nanometer chip, released in 2021. According to an accompanying technical report, the chip also demonstrated up to 70% greater energy efficiency than its predecessor. In designing the chip, researchers developed an “entirely new transistor architecture” called nanostack, which “vertically stacks and staggers transistors” to enable IBM’s 0.7-nanometer chip technology, IBM explained. A section of the chip seen with a transmission electron microscope. Credit: IBM “With our new nanostack architecture, we’re not just making smaller transistors,” Jay Gambetta, director of IBM Research, said in the statement. “We’re reinventing how chips are built to deliver dramatically more power and energy efficiency.”
Smaller and smaller Semiconductor chips enable things like computers, home appliances, communications, and transportation devices. In 1965, Intel co-founder Gordon Moore surmised that transistor capacities evolved at a predictable and consistent rate. Specifically, all things considered, the number of transistors on a semiconductor chip would double about every two years. For a while, the so-called Moore’s Law held rather well—until, that is, things hit a literal wall.
“Moore’s Law was never meant to last forever,” according to a blog post by the Massachusetts Institute of Technology’s (MIT) Computer Science and Artificial Intelligence Lab. “Transistors can only get so small and, eventually, the more permanent laws of physics get in the way.” That is, as companies try to cram more transistors into smaller chips, new advances in transistor technology take longer than two years, so Moore’s Law has been over since at least 2016, Charles Leiserson, a computer scientist at MIT, said in the blog. Accordingly, the issue now is to consider how improvements in chip performance fit into a longer-term picture, Willy Shih, an economist at Harvard Business School, said in an explainer.
Reaching atomic levels In that sense, IBM’s latest chip represents an inventive approach for bypassing the limits of physical scaling. Specifically, two wafers with nanosheet-style transistors are glued together like a sandwich to vertically stack two layers of transistors, and related technical assessments suggested that the wafer stacking was flexible and scalable enough to support real computation, Huiming Bu, vice president of IBM’s silicon technology research team, said in a press briefing on the chip. Researcher holding IBM’s sub-1 nm node wafer. Credit: IBM That said, this chip isn’t quite ready for manufacturing just yet. The company’s goal is to enter production in the next five years, but there’s still work to be done. For instance, Bu pointed out that the team was still working on pathways to prevent thermal noise or integration into existing systems in the high-performance computing community. “From my perspective, I hope to see it be as successful as the 2-nanometer [chip] and become the industry platform,” Gambetta said during the briefing. “And as we see with AI and classical computing in general, we are only seeing more and more consumption.” #IBM #Crosses #Computings #Biggest #Barriers #Worlds #Sub1 #Nanometer #ChipIBM,Semiconductors,transistors](https://i1.wp.com/gizmodo.com/app/uploads/2026/06/nanostacking-ibm-sub-nm-chip-1280x720.jpg?ssl=1 "IBM Crosses One of Computing’s Biggest Barriers With World’s First Sub-1 Nanometer Chip
In a major breakthrough, IBM revealed the world’s first semiconductor chip technology built on a sub-1 nanometer chipmaking process. For comparison, the process uses transistor features smaller than the width of a DNA strand, which measures about 2.5 nanometers across. The chip itself is about the size of a fingernail but holds almost 100 billion transistors, and the company expects it could enter markets as early as the next five years. In a statement released today, IBM said the new chip features nearly twice the density of its 2-nanometer chip, released in 2021. According to an accompanying technical report, the chip also demonstrated up to 70% greater energy efficiency than its predecessor. In designing the chip, researchers developed an “entirely new transistor architecture” called nanostack, which “vertically stacks and staggers transistors” to enable IBM’s 0.7-nanometer chip technology, IBM explained. A section of the chip seen with a transmission electron microscope. Credit: IBM “With our new nanostack architecture, we’re not just making smaller transistors,” Jay Gambetta, director of IBM Research, said in the statement. “We’re reinventing how chips are built to deliver dramatically more power and energy efficiency.”
Smaller and smaller Semiconductor chips enable things like computers, home appliances, communications, and transportation devices. In 1965, Intel co-founder Gordon Moore surmised that transistor capacities evolved at a predictable and consistent rate. Specifically, all things considered, the number of transistors on a semiconductor chip would double about every two years. For a while, the so-called Moore’s Law held rather well—until, that is, things hit a literal wall.
“Moore’s Law was never meant to last forever,” according to a blog post by the Massachusetts Institute of Technology’s (MIT) Computer Science and Artificial Intelligence Lab. “Transistors can only get so small and, eventually, the more permanent laws of physics get in the way.” That is, as companies try to cram more transistors into smaller chips, new advances in transistor technology take longer than two years, so Moore’s Law has been over since at least 2016, Charles Leiserson, a computer scientist at MIT, said in the blog. Accordingly, the issue now is to consider how improvements in chip performance fit into a longer-term picture, Willy Shih, an economist at Harvard Business School, said in an explainer.
Reaching atomic levels In that sense, IBM’s latest chip represents an inventive approach for bypassing the limits of physical scaling. Specifically, two wafers with nanosheet-style transistors are glued together like a sandwich to vertically stack two layers of transistors, and related technical assessments suggested that the wafer stacking was flexible and scalable enough to support real computation, Huiming Bu, vice president of IBM’s silicon technology research team, said in a press briefing on the chip. Researcher holding IBM’s sub-1 nm node wafer. Credit: IBM That said, this chip isn’t quite ready for manufacturing just yet. The company’s goal is to enter production in the next five years, but there’s still work to be done. For instance, Bu pointed out that the team was still working on pathways to prevent thermal noise or integration into existing systems in the high-performance computing community. “From my perspective, I hope to see it be as successful as the 2-nanometer [chip] and become the industry platform,” Gambetta said during the briefing. “And as we see with AI and classical computing in general, we are only seeing more and more consumption.” #IBM #Crosses #Computings #Biggest #Barriers #Worlds #Sub1 #Nanometer #ChipIBM,Semiconductors,transistors")
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