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Large language models often are called upon to gather news. In this task, researchers found, their ability to find relevant reports is the weakest link.
With Llama, Meta marked itself as an open alternative to OpenAI. With its new closed models, Meta now positions itself as a low-cost, high-value competitor.
Providers of large language models stand to benefit by building models that spur user engagement, but users may bear a cost in undue influence on their world views.
ChatGPT’s voice mode now listens and speaks at the same time, passing harder questions posed to the conversational model to a reasoning model in the background.
DeepSeek built a speculative decoding module that speeds up its production models’ text generation by more than 50 percent without sacrificing accuracy, then made its technique open source.
Microsoft, once OpenAI’s exclusive partner and still a major reseller of other companies’ AI models, built its own reasoning model from scratch.
Models that orchestrate the activities of other models and agents achieved state-of-the-art performance on a variety of benchmarks, outperforming the best individual models working alone.
OpenAI announced a preview of its GPT-5.6 family, including a top-tier model comparable to Claude 5 Mythos — but so far it’s available only to users that are selected by the U.S. government.
Google’s AlphaFold models pioneered the task of finding the shapes of biologically active molecules, opening new pathways for drug development.
The third generation of Apple Foundation Models — fruit of Apple’s collaboration with Google — introduces a variation on the mixture-of-experts architecture that runs on local devices.
Z.ai released an open-weights model that rivals proprietary leaders for autonomous agentic tasks.
Reinforcement learning can’t train a model to solve a difficult problem if the model doesn’t discover all the right steps.
Nvidia’s largest-yet model is among the best-performing from a developer based in the U.S. and among the most open developed by anyone.
SWE-bench, a family of benchmarks that focuses on an LLM’s ability to fix software bugs, is giving way to new tests that evaluate agent software-engineering performance in more challenging ways.
Popular large language models have adopted the biases of governments that control the free flow of information, particularly when those models generate output in the languages of countries where such governments are in power, researchers found.
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