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OpenAI's millennium proof dispute raises the question of whether researchers can trust AI labs
Mathematician Tristan Buckmaster accused OpenAI of pressuring him and possibly training on his drafts amid OpenAI's race to claim a Navier-Stokes millennium proof.
OpenAI published a blog post and Sam Altman defended the team behind its AI-generated proof of the Navier-Stokes Millennium Problem after mathematician Tristan Buckmaster accused the company of academic misconduct. Buckmaster and co-author Levent Alpöge, who works at Anthropic, allege OpenAI pressured Buckmaster, sidelined Alpöge, and may have trained on drafts they entered into OpenAI's systems. OpenAI acknowledges it cannot rule out that de-identified data from their product usage helped improve its models. Mathematician Terence Tao warned the episode could discourage researchers from sharing work, reversing centuries of open science.
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Teaching Everyone to Fish for Tokens
Analysis argues open-source AI now depends heavily on Nvidia's financing, with a reported $26 billion bet shaping the open-weights ecosystem's future.
An Interconnects essay examines whether the open-source model recipe, exemplified by Ai2's Olmo and Nvidia's Nemotron releases, can become economically self-sustaining. It reports Nvidia is spending roughly $26 billion on near-open-source models to drive demand for its chips, and argues the open ecosystem faces an existential financing window over the next few years. The author predicts open models may fork toward efficiency, specialization, and on-prem enterprise agents rather than competing head-on with closed frontier labs.
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Quoting Terence Tao
Terence Tao warns AI agents racing to solve rumored open problems may incentivize researchers to hide directions, damaging open science.
Mathematician Terence Tao argues that fruitful open problems are being depleted non-renewably as AI-assisted effort floods any problem that gains attention. He observes that even rumors of someone working on a problem can trigger massive AI-powered effort to solve it before the original project matures. Tao warns this dynamic may push researchers to stop sharing promising directions, reversing centuries of open-science tradition.
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University of Manchester Uses NVIDIA Earth-2 to Forecast Air Pollution Across the UK
University of Manchester retrained NVIDIA Earth-2 CorrDiff and StormCast on Isambard-AI to forecast UK air pollution at 2-3 km resolution.
University of Manchester researchers led by professor David Topping adapted NVIDIA's Earth-2 generative AI frameworks to forecast air pollution across the UK. Earth-2 CorrDiff was retrained in two days on a single eight-GPU node of Isambard-AI (5,448 GH200 Grace Hopper Superchips, 21 exaflops) using a year of hourly simulated pollution data, producing a UK-wide model at 2-3 square kilometer resolution. The team added Earth-2 StormCast for time-dependent forecasts that ingest real air quality observations, and demonstrated the workflow runs on the DGX Spark desktop AI system. Open-source training data and workflows are planned so other countries and cities can build similar pollution models.
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AI made software development unrecognizable. Is cybersecurity next?
Opinion piece argues AI-driven shifts that transformed software development—agent-run SOCs, autonomous triage—will soon reshape cybersecurity operations and staffing.
A CSO Online analysis notes Google Cloud research found 90% of developers already use AI, while a March 2026 Federal Reserve paper found coder employment growth fell roughly 3% since ChatGPT's arrival. Gartner predicts 80% of organizations will run smaller, AI-augmented engineering teams by 2030. Security leaders from Contrast Security, Menlo Security and the Cloud Security Alliance expect agent-run SOCs, machine-speed containment and abundant vulnerability discovery, but caution that absorption capacity and autonomous production-environment validation remain bottlenecks.
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Week in review: Firmware-level Android backdoor found on tablets, Dell zero-day exploited since 2024
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