搜索“OpenAI”

in during the coming years and basically to tell Wall Street to take a chill pill on the GenAI bubble bursting. Across the six XPU customers that Broadcom has – Google, Anthropic, OpenAI, and Meta Platforms for sure, and possibly ByteDance (which owns TikTok) or Apple for the other two, but Amazon Web Services is using Broadcom for packaging and integration for Trainium 4 – there is about 30 gigawatts of total compute capacity, which suggests that you can install XPU systems for somewhere around

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up for AI safety talks in mid-September as both sides lay groundwork for a Trump-Xi summit; separately, Beijing rebuked Anthropic and set its own terms for the dialogue, while an OpenAI executive publicly urged the two governments to prioritize safety talks. (Reuters/Bloomberg/SCMP); Separately, a bill advanced in the US Congress aims to give America an edge in the open-source AI race with China. (SCMP); Manus has now resumed independent operations under its founding team, restoring user data i

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d the decision by Hugging Face executives to approach Huang. However, Delangue pointed to a security incident over the summer that also fueled their thoughts. In July, hundreds of OpenAI agents that were being evaluated escaped their testing environment that was isolated from the internet and breached Hugging Face’s infrastructure. For the industry, the actions of the agents – which also included collaborating via a message board they created without authorization – was a warning shot about the

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atform. The lower cost and lower latency of this approach may even enable new use cases, such as in-game AI video generation, which is currently prohibitively slow and expensive. “OpenAI last year had US $30 billion in revenue, but they closed the financial year at an $8 billion loss. Why? The official reason is due to the high cost of inference,” Shazhaev says. “And those are mostly text models. For gameplay, you have audio, video, animations: It’s heavy data, and you need real-time responses.

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tting explicit boundaries in the prompt, establishing processes for verifying that a sandbox is sealed where intended, and implementing monitoring that can intervene in real time. OpenAI's disclosure (which prompted our investigation in July) that models used an unknown vulnerability to escape a sealed sandbox during an evaluation also made clear that we should focus on hardening the sandbox itself. While evaluations were paused, we put in place the following preliminary measures: 1) We built an

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components covering the gamut inside of its servers and networks. This gear is used in Google Cloud, and some of it will no doubt appear in TPU systems being sold to the likes of OpenAI and Anthropic. The increasing share of the rise in market cap that Google will gain – presuming, of course, there is one – is a kind of rebate on paying Marvell to do chip shepherding. Google pays real money for the chippery and gets a kind of funny money that strengthens its balance sheet back, and that helps G

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this year. Salesforce had organically adopted Linear, which made the partnership with Salesforce Ventures feel like a natural fit. Many of today’s leading AI companies, including OpenAI, Cursor, Cognition, Harvey, Physical Intelligence, Legora, and Baseten, also run product development in Linear. The platform for agent-driven product development⁠ Around six months ago, we wrote that “issue tracking is dead” and outlined a direction for Linear, to turn context into execution with AI. We launched

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seems to be a constant game of musical chairs across top model researchers for the past two years. Moreover, Google’s top-end Gemini model is falling behind Anthropic’s Claude and OpenAI’s GPT GenAI models – even though Google invented the transformer model that underpins all GenAI models – with its flagship Gemini 3.5 Pro model, which was announced in May and expected to ship in June still not available and no delivery date been given. “We have to accelerate all this work and stay focused on th

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ide, infosec's a good bet for a long, stable career FOSS NetBSD may have found a new role: The AI-free FOSS OS Increasing awareness and adoption, followed by increasing donations; OpenAI dots inspire open source imitators amid technical difficulties Persistent agents appeal to AI companies, but demand isn't obvious; Ubuntu 'Stonking Stingray' beta swims out: Deeper Rust 'oxidization' plus LLM speech-to-text GNOME 51 is here, and Ubuntu interim releases are getting interesting again; Revive Raski

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is only asking for pseudonymization of search data instead of full anonymization. Google also expressed concern over handing search data to AI chatbots, saying that companies like OpenAI could slurp up search data en masse to train their models – an argument we note is somewhat rebuffed by the Commission's point that search data won't be freely available under its proposed schema. As for the AI interoperability concerns, Google told us third-party AI assistants are gaining distribution on Androi

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ide, infosec's a good bet for a long, stable career FOSS NetBSD may have found a new role: The AI-free FOSS OS Increasing awareness and adoption, followed by increasing donations; OpenAI dots inspire open source imitators amid technical difficulties Persistent agents appeal to AI companies, but demand isn't obvious; Ubuntu 'Stonking Stingray' beta swims out: Deeper Rust 'oxidization' plus LLM speech-to-text GNOME 51 is here, and Ubuntu interim releases are getting interesting again; Revive Raski

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r the camera, ignoring a control input, or collapsing through a hard scene transition. Through active exploration, an agent can therefore improve a world model. Readers may recall OpenAI’s “Faulty reward functions in the wild” from 2016, where an RL agent steering a boat learned to rack up points by spinning in circles instead of finishing the race. RL agents are unreasonably good at finding the cracks in a system. PROWL points that talent at the world model itself: the agent hunts a weakness, t

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wed a report that we believe is the basis of the government's directive and validated that the level of capability displayed there is widely available from other models (including OpenAI’s GPT-5.5), and is used every day by the defenders who keep systems safe. We will share more details over the next 24 hours. We are complying with the government’s legal directive and are removing access to Fable 5 and Mythos 5 for all users. However, we disagree that the finding of a narrow potential jailbreak

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ide, infosec's a good bet for a long, stable career FOSS NetBSD may have found a new role: The AI-free FOSS OS Increasing awareness and adoption, followed by increasing donations; OpenAI dots inspire open source imitators amid technical difficulties Persistent agents appeal to AI companies, but demand isn't obvious; Ubuntu 'Stonking Stingray' beta swims out: Deeper Rust 'oxidization' plus LLM speech-to-text GNOME 51 is here, and Ubuntu interim releases are getting interesting again; Revive Raski

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aining to open research. Today, we're announcing that we've raised $15M in funding, led by Founders Fund, with participation from Menlo Ventures, Andrej Karpathy (EurekaAI, Tesla, OpenAI), Clem Delangue (Hugging Face), Dylan Patel (SemiAnalysis), Tri Dao (Together.AI), Emad Mostaque (Stability AI), Jake Medwell (8VC Co-Founder) and many others. This brings our total funding to over $20M, accelerating our work on the open superintelligence stack. Scaling Open + Democratized AI Prime Intellect is

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the more our AI learns. We train our models on medium- and high-quality music we can find on the open internet — just as Google's Gemini, Microsoft's Copilot, Anthropic's Claude, OpenAI's ChatGPT, and even Apple's new Apple Intelligence train their models on the open internet. The timing of this lawsuit was somewhat surprising. When this lawsuit landed, Suno was, in fact, having productive discussions with a number of the RIAA's major record label members to find ways of expanding the pie for m

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ocking scheduler is a key bottleneck for models running on fast GPUs (H100s). We are working on making the schedule asynchronous and plan steps ahead of time; We identified vLLM’s OpenAI-compatible API frontend has higher than desired overhead. We are working on isolating it from the critical path of scheduler and model inference; We identified vLLM’s input preparation, and output processing scale suboptimally with the data size. Many of the operations can be vectorized and enhanced by moving th

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