DeepSeek, the Chinese developer of outstanding open-weights models, has withheld an upcoming update of its flagship model from U.S. chip makers, a move that intensifies the AI rivalry between the U.S. and China.
The Qwen3.5 family of open-weights vision-language models includes impressive larger models as well as a smaller one that outperforms an OpenAI open-weights model 10 times its size.
Research shows that diffusion image generators can train somewhat faster if they learn to reconstruct embeddings from a pretrained encoder that’s built for vision tasks like classification, segmentation, and retrieval — not image generation.
OpenAI updated its flagship models, extending the ability to use tools and setting the state of the art on a handful of benchmarks, and priced them at the top of the market. Its coding and agentic abilities have enabled Codex, OpenAI’s competitor to Anthropic’s Claude Code, to leap ahead.
LLMs have achieved gold-medal performance in math competitions. An agentic system showed strength in mathematical research as well.
Managers need to understand how their subordinates get work done, what resources they require, and what they accomplish. OpenAI’s latest product aims to fulfill this need when the teammates are AI agents.
Google launched a cheaper, faster successor to its flagship image generator, delivering greater interactivity at roughly half the price.
Projected demand for output from large language models is spurring a massive buildout of data centers. Researchers asked whether smaller models running on local devices could meaningfully lighten that load.
The fourth global AI summit marked a decisive shift from focusing on theoretical hazards to spreading AI’s benefits throughout the world.
Google updated its flagship Gemini model, topping several benchmarks while undercutting competitors on performance per dollar.
Difficulty sleeping often precedes heart disease, psychiatric disorders, and many other illnesses. Researchers used data gathered during sleep studies to detect such conditions.
Reasoning models in the 1 to 2 billion-parameter range typically require more than 1 gigabyte of RAM to run. Liquid AI released one that runs in less than 900 megabytes, and does it with exceptional speed and efficiency.
Z.ai more than doubled the size of its flagship large language model to deliver outstanding performance among open-weights competitors.
Anthropic updated its flagship large language model to handle longer, more complex agentic tasks.
AI is becoming ubiquitous, yet no standards exist for auditing its safety and security to make sure AI systems don’t assist, say, hackers or terrorists. A new organization aims to change that.
Stay updated with weekly AI News and Insights delivered to your inbox