Hangzhou, a longtime manufacturing hub in eastern China, is blossoming into a center of AI innovation.
Large language models may have advantages over human recruiters when conducting job interviews, a study shows.
The French AI company Mistral measured the environmental impacts of its flagship large language model.
Google’s latest smartphone sports an AI assistant that anticipates the user’s needs and presents helpful information without prompting.
India, which has limited funding and large numbers of languages and dialects, is redoubling its efforts to build native large language models.
OpenAI launched GPT-5, the highly anticipated successor to its groundbreaking series of large language models, but glitches in the rollout left many early users disappointed and frustrated.
The race is on to develop large language models that can drive agentic interactions. Following the one-two punch of Moonshot’s Kimi K2 and Alibaba’s Qwen3-235B-A22B update, China’s Z.ai aims to one-up the competition.
The “open” is back in play at OpenAI.
People who turn to chatbots for companionship show indications of lower self-reported well-being, researchers found.
Less than two weeks after Moonshot’s Kimi K2 bested other open-weights, non-reasoning models in tests related to agentic behavior, Alibaba raised the bar yet again.
LLMs can struggle with difficult algorithmic or scientific challenges when asked to solve them in a single attempt. An agentic workflow improved one-shot performance on hard problems both theoretical and practical.
An agent’s performance depends not only on an effective workflow but also on a large language model that excels at agentic activities. A new open-weights model focuses on those capabilities.
Researchers addressed weaknesses in existing multi-agent frameworks. Their systems achieved scientific and technical breakthroughs.
xAI updated its Grok vision-language model and published impressive benchmark results. But, like earlier versions, Grok 4 showed questionable behavior right out of the gate.
Developing an agent that navigates the web can involve a lot of human effort spent annotating training examples to fine-tune the agent’s LLM component. Scientists automated the production of data that fine-tuned LLMs effectively for web tasks.
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