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artificial-intelligence

A collection of 110 issues

TrueForge cuts agent costs, but open source is not governance

TrueForge is an open-source AI agent harness that TrueFoundry says completed the same enterprise tasks at 30%-75% lower cost than Anthropic's Claude Managed Agents. The useful distinction is not simply that the runtime is free. TrueForge separates the agent execution loop from the enterprise governance layer

MIT's AI solvent search shows sodium battery promise but scaling is unproven

MIT researchers report a new electrolyte solvent for sodium-metal batteries, identified through an AI-driven search that prioritized smaller molecules to speed up ion transport while maintaining chemical stability. The work, published in Joule, introduces a design principle where solvent size is the primary tuning knob, rather than relying

Skin disease AI study shows explainable methods can mislead non-experts

Skin disease AI assistance lands differently depending on who is using it. A study published today in Nature Medicine from MIT, Stanford, and Columbia finds that explanations designed to help users interpret an AI prediction can backfire on the very people they are meant to serve, while giving clinicians little

GeoPT's physics pretraining cuts simulation data needs with narrow tests

GeoPT, a pretraining approach presented by MIT CSAIL and Tsinghua University researchers at ICML in July, uses synthetic particle-on-shape interactions to teach neural networks physics before they train on labeled data. According to the team, the resulting model reaches peak accuracy twice as fast as leading baselines, requires

Fitzgerald's framework names the innovation stream no funder targets

MIT professor Eugene Fitzgerald's new book 'The Invisible Engine: Why Innovation Evades Control' argues that research investment splits into three streams and that one of them has no dedicated funder. According to Fitzgerald, the Merton C. Flemings SMA Professor in MIT's Department of Materials

Attribution decay means AI images may have no responsible training source

A new study from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) introduces a measurable phenomenon the researchers call attribution decay. As the number of training images grows, the influence of any single example on a generated output shrinks, often to the point of being unmeasurable. The finding, published

Qwen3.8-27B lands as a local model with frontier-sized agentic claims

Alibaba released Qwen3.8-27B on Hugging Face under an Apache 2.0 license, framing a 27-billion-parameter dense multimodal model as a frontier-class coding and agent system that can be downloaded and run on consumer hardware. The release drew unusually strong reaction from developers and AI power

Snowflake's Cortex AI Gateway bets routing alone is not the differentiator

Snowflake's Cortex AI Gateway now offers dynamic model routing, with the company claiming up to 3x token-cost reductions from internal testing on workloads where simple questions were previously handled by its most expensive model. Databricks, AWS, Google Cloud, and Nvidia have all shipped some form of model

Rezolve Ai's post frames a unifying layer as commerce AI's missing core

VentureBeat published a sponsored post under Rezolve Ai's byline arguing that enterprise commerce AI is failing because brands keep stacking point solutions on top of one another instead of building a unifying execution layer. The architectural prescription arrives in the shape of a paid placement, and the three

Enterprises burned by AI agents still race to remove human approval

VentureBeat's latest Pulse data show an inversion at the center of enterprise agent rollout: companies that have already watched an AI feature pass internal testing only to disappoint customers are moving most aggressively to remove humans from the release decision. Among 108 enterprises surveyed in July, 49% reported