Six stories from roughly the last day. Summaries only; follow the links for the full reporting.
Amazon opens TorchNeuron so PyTorch code can run on Trainium
Amazon put TorchNeuron into public beta: a layer that runs existing PyTorch code on Amazon’s Trainium chips after a basic configuration change, instead of rewriting calls for Amazon-specific APIs. It has been in private beta since late last year with more than 30 companies and internal teams; Amazon plans to open-source it Tuesday alongside the PyTorch Conference in San Jose. The move targets Nvidia’s CUDA lock-in. GeekWire also notes Amazon is reportedly in talks to buy Decart, a chip-portability startup, in a deal that could be worth about $7 billion.
Tenstorrent raises $1.5 billion at a $6.2 billion valuation
Jim Keller’s AI chip company closed a Series E led by Trace Capital and Innovation X, more than doubling its late-2024 valuation of about $2.6 billion. Investors include ARK Invest, Fidelity, Morgan Stanley, T. Rowe Price, Sandisk, Tether, and Cadence Ventures. Tenstorrent says it will use the money for volume manufacturing of Galaxy servers, next-gen hardware, and the RISC-V AI and CPU IP it licenses to customers such as Samsung and LG. Bloomberg had earlier reported acquisition interest from Intel and Qualcomm; Keller told Bloomberg the company chose to raise instead of sell.
Microsoft treats AI agents as insider risk and expands Project Perception
In a Security blog post, Microsoft CVP Nadim Abdo argues that workplace agents need access to company systems, which creates insider-style risk even when they are not malicious. Citing Satya Nadella’s line that the most trustworthy agentic system lets you “trust the model least,” Microsoft is extending Project Perception with agent discovery (now 60 local agent types, including Claude Code, OpenAI Codex, and GitHub Copilot), Entra Agent ID, Dynamic Permissions, Dynamic Agent Risk, Dynamic Conditional Access, and Guardian Agents that carry out containment at machine speed inside human-set policy.
ChatGPT’s GPT-6 Astra Pro can now run parallel agents
OpenAI’s Oct 16 release notes say GPT-6 Pro in the Chat tab now responds faster, uses plugins and tools more reliably, and can split one task across multiple agents working in parallel. Pro users can follow each agent’s progress and open completed tasks to review the work. The rollout is for eligible Pro users; managed workspaces depend on admin settings.
OpenAI offers free GPT-Rosalind seats to U.S. university labs
The Rosalind Academic Plan gives approved U.S. academic labs up to 30 complimentary ChatGPT Business Standard seats for 12 months, plus access to GPT-Rosalind (OpenAI’s life-sciences model) after trusted-access review. API access is not included. PIs apply on behalf of their labs; universities with an existing Enterprise agreement should go through that channel instead. OpenAI says research data shared under the plan is not used for training by default.
Meta walks back terms that looked like a green light to scrape and train
After Nieman Lab and others flagged commercial terms that seemed to let Meta use content from a business account’s domains “to provide, develop, improve, research, train, and maintain” its products, Meta removed the disputed language. The company said the crawling terms only applied to ads and business products and that the clarification does not change how Meta’s web crawlers work. Legal experts still warn that remaining wording may leave broad scraping room.