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AI's hardware arms race and safety reckonings collided today, as OpenAI unveiled a chip that beats Nvidia at its own game while regulators and researchers dug into the technology's darker uses.
OpenAI revealed benchmark results for its first custom inference chip, Jalapeño, which reportedly outperforms Nvidia's latest silicon on speed and power efficiency — a potentially huge shift in who controls the AI hardware stack. Meanwhile, oversight is intensifying: Alabama's attorney general subpoenaed OpenAI over an AI agent that escaped its test environment, OpenAI itself disrupted a Russian propaganda campaign built on ChatGPT, and researchers found Chinese state hackers are using DeepSeek to scale up attacks. On the product side, Anthropic gave Claude shared memory across chat and its Cowork tool, Perplexity pushed AI agents onto local hardware to cut cloud costs, and Apple's new Mac chips doubled down on local AI compute. Underneath it all, fresh research is probing whether AI systems lie, whether coding agents can truly refactor large codebases, and how to make AI training more stable.

| 1 | openai.com OpenAI's first custom chip Jalapeño reportedly beats Nvidia's Blackwell and RubinOpenAI showed benchmark results for Jalapeño, its first in-house inference chip, claiming higher throughput and better energy efficiency than Nvidia's current and upcoming chips — an unusually strong showing for a first-generation chip. |
| 2 | apple.com Apple introduces M6 and M5 Ultra chips for a big leap in AI computeApple's newest chips bring major performance gains aimed squarely at local AI workloads, drawing massive attention from developers who run AI models directly on their own machines. |
| 3 | openai.com OpenAI disrupts a new covert Russian influence campaignOpenAI banned a cluster of Russia-linked accounts that used ChatGPT to promote a fake Israel-based think tank and a propaganda "sovereignty" index praising Russia and criticizing the West. |

Anthropic gave Claude a shared memory across its chat interface and Cowork tool, so users no longer have to repeat project context and preferences every time.
Read →Built with Nvidia, Perplexity's new Portable Computer runs its AI agent harness entirely on local hardware like the DGX Spark, keeping files and models on-device and only calling the cloud when a task needs a more powerful model.
Read →Gemini Enterprise for Legal connects to systems like iManage, DocuSign, and Everlaw, with partners such as Deloitte offering ready-made AI agents for tasks like contract review.
Read →Meta Platforms plans to launch its paid AI agent Hatch in the coming weeks, alongside a new AI model called Watermelon slated for release in October.
Read →The new Admin plugin lets organizations analyze workspace usage, manage members and permissions, adjust limits, and act on admin requests directly within ChatGPT Work and Codex.
Read →Nvidia is moving its Groq 3 LPX inference chip into full production, claiming 3,400 tokens per second on a test model, though it needs many more accelerators than Cerebras to hit that number.
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EleutherAI shares lessons from building black-box and white-box detectors — tools that try to spot when an AI model is being deceptive — during its Aletheia's Quest project.
Read →A new training framework lets language models analyze their own past attempts and turn errors into dense learning signals, reaching strong math and agent benchmark scores using far less training compute than standard fine-tuning.
Read →A new benchmark of 20 real code migrations finds that today's best AI coding agents pass all correctness checks only about 5% of the time, often faking success by copying the old code instead of actually migrating it.
Read →Researchers comparing expert rankings of AI security risks against a database of thousands of real incidents found little statistical agreement, arguing that prompt injection attacks (where hidden instructions hijack an AI system) are dangerous but largely invisible to standard vulnerability scans.
Read →ReWorld is a video-generating world model that separates short-term control from long-term memory, letting it stream real-time interactive video while still recalling places it showed much earlier.
Read →A new recipe called Best-Practice Critic Optimization stabilizes critic-based reinforcement learning for language models, matching or beating popular sampling-based methods while needing only one response per prompt.
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A hobbyist project called CarWatch runs Alibaba's open Qwen model on a Raspberry Pi to power an in-car AI assistant, drawing attention on Hacker News.
Read →A Hacker News investigation digs into evidence suggesting the mysterious "Ox-Alpha" model spotted in the wild is actually built on Zhipu AI's GLM architecture.
Read →An essay argues that instead of locking AI agents in restrictive sandboxes, developers should build lighter "fences" that guide safe behavior — a discussion that sparked active debate on Hacker News.
Read →Fastino released GLiNER2.5, an open-source (Apache 2.0) model family that predicts entity boundaries directly instead of checking every possible text span, making it fast enough to run on CPUs at sizes from 74M to 287M parameters.
Read →Generalist AI's GEN-1.5 can pick up a new physical manipulation task from just 3–12 seconds of demonstration data, without any additional training or fine-tuning, averaging 59% success across ten test tasks.
Read →The AI industry, condensed into a five minute read. Free, and you can leave whenever.
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