Models

The Apache-2.0 model family combines transcription, layout boxes, image descriptions and chart extraction in models small enough to run locally.

A 12,350-call study found no reliable decline in six cognitive-bias measures as models consumed more reasoning tokens. One direct prompt helped with anchoring.

Research preprints, local projects, technical essays, community tests, security incidents and policy changes: the rest of today's AI news with direct sources.

The small Claude model adds adaptive thinking and a two-tier token price. Anthropic positions it for summaries, browser work and narrowly scoped subagents.

The 3.1-billion-parameter d1-3B and experimental 600-million-parameter d1-omni answer structured questions in one forward pass, with weights available for local deployment.

A preprint finds that a few fixed words at the start of an answer can recover much of the reasoning performance usually associated with reinforcement learning.

A preprint traces how models that update their weights from their own generated text can enter a damaging feedback loop over long inference streams.

Open models, research preprints, agent projects, technical essays and community measurements: the rest of today's AI news with direct sources.

Google's 740-million-parameter embedding model maps text, code, images, video and audio into one vector space, with modular encoders designed for local devices.

Mistral has opened API access to its one-trillion-parameter multimodal model and set 27 October for the open-weight release, leaving architecture and benchmark claims provisional.

A preprint finds an early object-matching circuit and a later relation-matching circuit in vision-language models, then links the latter to performance on ARC-AGI-1.

The Apache-licensed project publishes its accelerator design, compiler, simulator and host tools, with measured throughput showing a small, memory-bound system rather than a GPU replacement.