AI News

OpenAI announced a partnership with America's SBDC to expand hands-on AI training and local support for small businesses, alongside a new report on how small teams are using AI.

Anthropic announced that Claude for Government is generally available to federal and state agencies, delivering coding and agentic work capabilities comparable to its commercial customers through a FedRAMP High authorized environment, alongside governance controls such as department-level budget allocation, SCIM seat tiering, audit logs, and two-person approval, while the Claude Code command-line interface and Claude for Microsoft 365 enter early access in the same environment.

Carl Johnson, a sales development leader at Anthropic, describes how his team built a buying agent on Claude Managed Agents (beta), deployed on the Contact Sales and Pricing pages, inside the product, and in email, which now holds thousands of conversations a day and can take buyers through checkout, turning leads into opportunities more than twice as often as the old form, closing about five days faster, and cutting by about half the share of conversations that needed a person to close.

In an experience report, the NVIDIA team describes how it built the open source TensorRT Model Connect: a C++ collection of model-family-owned reference implementations on top of TensorRT that turn supported Hugging Face or local checkpoints into versioned .bundle artifacts and expose task-oriented native C++ APIs for text, vision, audio, diffusion, segmentation, embedding, forecasting, and other workloads; as of the public July 29, 2026 release comparison the project covered 128 model families tested on NVIDIA GB300, and the team derives an operational "AI native" practice centered on parallel decomposable work, model-family isolation, reversible changes, and GPU-backed automated validation.

In a panel discussion hosted by the Berkman Klein Center, where Alex Pascal opened by asking what we want from AI, Jeff Dunn, Amit Goldenberg, and Avijit Ghosh discussed AI's double-edged nature, a continuum from tool to full-fledged named agent with personality, and the shortcomings of current "benchmark maxing" evaluation; Ghosh proposed an evaluation system that measures both system behavior and impact on people and public participation in reporting and assessment, for example incentivizing companies with liability relief if they fix a reported problem within 60 days.

Anthropic announced a new study in which Anthropic Interviewer, an AI, asks Free, Pro, and Max users of Claude and Claude Code about their positive and negative experiences with AI, what they want AI to change in areas such as work, school, healthcare, and government, and what they want from AI developers; the study runs September 29 to October 6, 2026, takes roughly 15 minutes per interview, and for the first time lets participants choose to make their complete interview and associated country public, with an FAQ explaining the benefits, re-identification risks, and permanence of that choice.

Anthropic's Frontier Red Team evaluated GLM-5.3, the latest model from Zhipu AI (known outside China as Z.ai), using automated benchmarks and human-in-the-loop workflows, finding that it can autonomously build end-to-end cyber exploits (50 of 410 attempts on ExploitBench and full control-flow hijacks in 4% of trials on an internal binary exploitation benchmark) and that simple techniques bypassed its safeguards in 64%–100% of simulated tests, while those techniques did not succeed against safeguarded Claude models in their testing.

MIT Technology Review's The Download newsletter reports that Anthropic announced its new molecular biology lab's first discovery: its AI agents flagged a previously uncatalogued pattern surrounding an enzyme, a pattern "reminiscent" of what led to the gene-editing technology CRISPR, but biologists pushed back, with some questioning whether merely finding the pattern amounted to a discovery and another saying his team had already discovered the same pattern, raising questions about whether Anthropic's system had learned from his conversations with Claude.

On 22 September 2026, WHO and Knowledge Ecology International (KEI) co-organized an expert panel, "Intellectual Property and Traditional Medicine: Rethinking Access, Benefit Sharing and Data Governance," on the sidelines of the 53rd Inter Government Consultations at WIPO, where participants noted that AI and digital technologies can accelerate drug discovery based on traditional medicine knowledge while making contributions by knowledge holders harder to trace, and put forward concrete proposals including federated data governance, prior informed consent and tailored benefit-sharing arrangements, while stressing that Indigenous Peoples and local communities should be recognized as partners in stewardship and governance rather than merely as sources of knowledge.

This sponsored article, provided by HPE and not written by MIT Technology Review's editorial staff, argues that as AI moves from isolated pilots into production portfolios (assistants, retrieval-and-knowledge systems, agentic applications), a consumption-only approach turns AI spending into a hard-to-forecast variable monthly line item, so enterprises should assess workload by workload the 'crossover point' at which sustained use makes owning and operating capacity potentially more economical than buying one request at a time, while stressing that the capital decision is only half the equation and that adoption, governance, and continued expansion of high-value use cases are needed to keep that capacity productive.