An anonymous reader quotes a report from Reuters: The OpenAI agent that broke into tech firm Hugging Face went on a dayslong hacking spree that OpenAI didn't notice until well after the threat was contained and the FBI was alerted, according to people familiar with the investigation. The agent -- a program capable of making decisions and executing complex tasks with little or no human oversight -- attempted to break out of its isolated testing environment at OpenAI around July 9, according to two of the people. The intrusion at Hugging Face, which operates as a repository for AI tools and models, began two days later on July 11 and lasted until July 13, said Thomas Wolf, Hugging Face's co-founder. It took several more days for OpenAI to realize its agent was behind the hack, and the two companies only communicated about it for the first time on or around July 20, according to Wolf and three of the people familiar with the investigation. OpenAI's public disclosure, on July 21, thatone of its agents had slipped out of control and carried out the break-in at Hugging Facedrew global attention. But many details of the hack, including how long the agent went rogue and OpenAI's belated knowledge of it, are being reported here for the first time. Hugging Face is preparing a public timeline of the hack, Wolf said, adding that he could not speak to what happened at OpenAI. In a statement, OpenAI said the hack was unprecedented and "marks an important moment for AI safety." It added that it was reviewing the incident with outside advisers and would eventually publish a technical report. "Does that mean that they left it unattended and didn't realize what it was doing? Or maybe they did and didn't know how to contain it? Both are equally dangerous and alarming," asked Marley Smith, the principal intelligence specialist at the nonprofit World Ethical Data Foundation. "The models lie, they cheat, they hack," said Jeffrey Ladish, whose organization, Palisade Research, studies the capabilities and motivations of AI agents. Ladish said the hack should spark broader questions over how much all the leading AI companies are willing to invest in onerous security measures while locked in a race with one another to deploy the best and fastest models. "There has to be government oversight," Ladish said, "because it won't happen otherwise."

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Nvidia, Microsoft, Meta, Palantir, and more than 20 other tech companies signed an open letter urging policymakers not to impose "premature restrictions" on open-weight AI models, warning that broad limits could "stifle competition or drive innovation overseas." CNBC reports: They wrote that open-weight models strengthen competition and ensure that the benefits of the technology are "broadly shared rather than concentrated in a few hands." "Relying solely on closed models is not inherently safe: they can be breached, misused, or fail in ways that outsiders cannot detect," the letter said. "And concentrating advanced AI capabilities behind a small number of closed models compounds that risk." Elon Musk, who runs an AI business under his rocket company SpaceX, also amplified the letter on social media, writing that it has his "full support" in a post on X. SpaceX did not officially sign the letter. Greg Brockman, OpenAI's president, said Thursday that the company believes in broad access, and that he has not been involved in any conversations with the Trump administration about potentially banning Chinese open-weight models in the U.S. "I think that, that fundamentally, AI and AI usage is something that is actually very important to democratize," Brockman told reporters during a briefing in New York City. "And so, for me, at a sort of deep level, I think that having more models, more usage, that is a good thing." OpenAI CEO Sam Altman addressed the letter in a post on X on Friday, writing that he wants the U.S. to win with both open-weight and proprietary models, and that he is "glad to see this." [...] In the letter on Friday, the U.S. tech companies said that concerns about unlawful distillation should be addressed through "targeted legal and commercial frameworks" instead of with "sweeping restrictions on techniques that play an important role in AI innovation." "Our AI leadership will be judged not by one frontier AI model, but by whether the United States builds a strong, open ecosystem that diffuses into every sector," the letter said. "This is essential for creating opportunities for innovation and prosperity across the country." The letter follows a separate appeal signed by nearly 200 Silicon Valley companies, including Proton and Y Combinator, warning that restricting U.S. access to Chinese open-weight AI models could cripple the next generation of American startups. "American leadership requires two things: world-leading American open-weight models and continued access for U.S. builders to open models already available worldwide," the startup founders wrote. Instead of broad prohibitions, they argue the government should adopt targeted safeguards. Of course, these signees "have an obvious economic stake in seeing open AI models flourish," notes TechCrunch. "Companies like Nvidia, Microsoft Azure, and other infrastructure providers have a vested interest in pushing for commoditized models: If models are interchangeable, people will buy more GPUs, rent more cloud capacity, and build more applications."

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Anthropic has released Opus 5, a new Claude model that it says comes close to its higher-end Fable 5 model at half the price while improving on Opus 4.8 in knowledge work, coding, and scientific research tasks. "At the same time, Anthropic says it has managed to make the model more resistant to being tricked," notes Engadget. Additionally, the company says Opus 5 "exhibits the lowest rates of deceptive behavior." From the report: One important distinction between Opus 5 and Mythos, which is currently only available to a limited number of vetted organizations through Anthropic's Project Glasswing initiative, is that the company has specifically avoided training the new model on cyber-related tasks. Due to more its powerful capabilities, Opus 5 is broadly better at those tasks than its predecessor, making it more useful for finding cybersecurity vulnerabilities, but the company says Opus 5 is "substantially behind" its flagship model at exploiting those vulnerabilities. [...] Anthropic says "Claude Opus 5's safeguards are designed to allow beneficial uses of the model in both cybersecurity and biology." The company has strengthened some of the model's cyber-related guardrails, but notes it did so along a "narrow range" of specific tasks. "Based on our testing, we expect the classifiers to intervene around 85 percent less often than they do for Fable 5," Anthropic said. With Opus 5, Anthropic also isn't including it in its recently announced 30-day data retention policy, which the company introduced alongside Fable and Mythos 5. As for pricing. Anthropic says API costs for Opus 5 will remain at $5 per one million input tokens and $25 per one million output tokens. Anthropic has also added an "effort" menu for Opus that users can tweak to tell the model whether they want it to be more thorough or fast and efficient to conserve tokens.

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At libraries around the country, "Avoiding AI" workshops have elicited unprecedented demand.

Explore o Shadowfetch Linux, a distribuição baseada em Debian que traz AI local integrada para uma experiência segura e criativa.

O post Conheça o Shadowfetch Linux, a distro Debian com AI local integrada apareceu primeiro em Blog do Edivaldo - Informações e Notícias sobre Linux.

A close call in Northern Virginia revealed just how poorly data centers respond to grid disruptions. Here's how to fix the problem.

Artificial intelligence may not deliver on its promise of vast economic opportunity at a price that humanity is willing to pay

In March, Anthropic, the cutting-edge artificial intelligence business that gave us the chatbot Claude, published an analysis on the impact of AI on employment, to help us assess the claim that intelligent robots were about to redefine human existence, ending demand for human labor.

Last year in May, Anthropic’s co-founder, Dario Amodei, claimed AI could wipe out half of all entry-level jobs in one to five years. Last January, he told us AI would probably become a “general labor substitute for humans”. In June he said we risk “a world where the economic trade-off dial is stuck on the hypergrowth, hyper-inequality setting”.

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© Photograph: DragonImages/Getty Images

© Photograph: DragonImages/Getty Images

© Photograph: DragonImages/Getty Images

As AI reshapes the way we communicate, researchers at Texas A&M University are developing an artificial intelligence-powered platform that could transform care for children with autism and older adults living with dementia. The technology learns each person’s unique communication style, behaviors, and preferences, enabling increasingly personalized support for caregivers, therapists, and families over time.

Called VoiceLove, it is one of three projects being developed with support from the Advanced Research Projects Agency for Health (ARPA-H).

At the core of the system is an AI engine that analyzes both speech and nonverbal behaviors documented through short videos recorded by caregivers or therapists during daily communications and interactions. Rather than comparing participants against a general model, the platform focuses on understanding each person’s individual patterns and communication style.

“Every child with autism is unique, and effective support should reflect that,” he said. “Our project leverages artificial intelligence to understand each child’s individual behaviors, communication styles, and preferences. The goal is to deliver personalized recommendations that help families, educators, and clinicians work together more effectively, enabling more responsive, data-driven care and improving the health and well-being of children with autism,” says Dr. Junhyoung Kim, associate professor in the School of Public Health, one of the principal investigators on the project, in a statement. 

The AI system was created to identify behavioral patterns in communication, interests, and responses across different situations. Based on its observations, the program provides personalized recommendations that could help therapists or caregivers create individualized intervention plans.

“The key innovation behind this platform is its ability to understand each child individually and learn their unique preferences, needs, communication styles, and strengths to deliver personalized recommendations,” Kim said. “For people living with dementia, the platform is designed to enhance person-centered care by helping residents communicate their needs, preferences, and daily experiences more effectively.”

Researchers say the technology could support a wide range of developmental goals, including improving communication skills, encouraging self-care, strengthening social engagement, and enhancing a person’s quality of life.

The same personalized approach could also benefit people living with dementia, where communication challenges often make it difficult for individuals to express their needs and wants. 

“Our vision is to create an AI platform that continuously learns from each child’s daily experiences,” Kim said. “As the system identifies patterns in behaviors, preferences, and responses to different activities, it can provide therapists and caregivers with personalized recommendations that evolve over time.”

“This adaptive approach helps explain why certain behaviors occur and supports more individualized, proactive care,” Kim added. 

VoiceLove is designed to keep learning. As caregivers continue using the app, the AI analyzes new interactions while also incorporating caregiver observations, experiences, and responses to daily prompts. 

The research team plans to begin with a small pilot study involving children with autism and older adults living with dementia after receiving Institutional Review Board approval.

Participants will use the platform for approximately one month while researchers evaluate its usability, feasibility, and overall user experience, and from there, insights derived from the pilot will help to inform a larger-scale study at some point in the future. 

Chrissy Newton is a PR professional and the founder of VOCAB Communications. She currently appears on The Discovery Channel and Max and hosts the Rebelliously Curious podcast, which can be found on YouTube and on all audio podcast streaming platforms. Follow her on X: @ChrissyNewton, Instagram: @BeingChrissyNewton, and chrissynewton.com. To contact Chrissy with a story, please email chrissy @ thedebrief.org.

What if a computer did not rely on electronic chips or tiny transistors, but instead used hundreds of microscopic particles moving through a liquid? That futuristic idea has now become a reality in a laboratory, where researchers have created a completely different kind of computer that performs calculations using the natural movement of tiny particles. […]

The post Scientists create a liquid computer that uses tiny moving particles instead of chips appeared first on Knowridge Science Report.

Reuters reports that the OpenAI agent that hacked Hugging Face had been free for a week before the company noticed.

OpenAI's fancy new AI keypad will be a lot of fun for some, while many others are probably not going to touch it.

The neolab is betting that automating routine computer tasks will soon outpace coding as AI's biggest use case.

Anyone who has used the Internet in recent years is probably used to encountering telltale signs of LLM prompting that lazy users sometimes forget to remove from their AI-generated pabulum. But a Canadian legislator took that idea to an embarrassing new level this week, reading an apparent LLM prompt instruction into the record during a floor speech.

Bill Oliver, a Progressive Conservative Party member of the legislative assembly of New Brunswick, noted in a speech last month that "One of the dangers associated with creating advocacy offices is that citizens often develop expectations that exceed the powers actually granted to those offices." He then went on to say out loud that "here’s a more natural, flowing version of that section that reads like a legislative speech rather than a series of short points," a line with all the hallmarks of an LLM presenting an alternative style option in response to a prompt.

The odd reading went more or less unnoticed at the time, but video of the remarks started spreading around social media networks like Reddit and Threads earlier this week. In Canada, the snafu is now getting mainstream attention from the likes of the Canadian Broadcasting Corporation and The Toronto Star, the latter of which called it a sign of "a growing divide in our society: between the elites, who are only too happy to delegate their duties to the Borg; and the masses, who find this objectionable."

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Today, Anthropic rolled out Opus 5, the newest update for the model that has recently become a popular choice for coding and other software development tasks, among other things.

While this is a noteworthy bump for Opus, it doesn't seem to be an Opus 4.5-level breakthrough in agentic coding performance.

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Co-Star CEO Banu Guler is also becoming the company's Chief Design Officer.

An OpenAI model being tested for cybersecurity capabilities decided to cheat rather than solve its assigned test, breaking out of its sandbox and hacking into Hugging Face to steal the answers. Simon Willison calls it “science fiction that happened.”

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The acquisition brings Poke’s conversational style and interaction model to Cognition’s coding agent Devin, reflecting a growing belief that how AI assistants interact with users is as important as the models powering them.

By Alius Noreika Key takeaways The question comes up in almost every firm that has started experimenting with

A couple of decades after the discovery of systems that could selectively target DNA, we're starting to see the first therapies based on gene editing. One challenge these developments have faced is safety. While we can make them pretty specific to the gene we want edited, the human genome is very large, and even rare DNA sequences can appear a couple of times by chance.

As a result, all the original gene-editing systems had known rates of what are called off-target effects, in which they simply edit the wrong sequence. This may be a low-probability event, but edit enough cells—and therapies generally have to edit many—and errors become inevitable.

A lot of effort has gone into finding ways to minimize or eliminate off-target edits. In a recent issue of Nature, researchers described modifying the AI protein-folding software AlphaFold to help identify key areas of gene-editing proteins responsible for off-target effects. Those areas were then modified to reduce the problems.

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© Anton Vierietin

A couple of decades after the discovery of systems that could selectively target DNA, we're starting to see the first therapies based on gene editing. One challenge these developments have faced is safety. While we can make them pretty specific to the gene we want edited, the human genome is very large, and even rare DNA sequences can appear a couple of times by chance.

As a result, all the original gene-editing systems had known rates of what are called off-target effects, in which they simply edit the wrong sequence. This may be a low-probability event, but edit enough cells—and therapies generally have to edit many—and errors become inevitable.

A lot of effort has gone into finding ways to minimize or eliminate off-target edits. In a recent issue of Nature, researchers described modifying the AI protein-folding software AlphaFold to help identify key areas of gene-editing proteins responsible for off-target effects. Those areas were then modified to reduce the problems.

Read full article

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© Anton Vierietin