2025-10-02
A new study by Shanghai Jiao Tong University and SII Generative AI Research Lab (GAIR) shows that training large language models (LLMs) for complex, autonomous tasks does not require massive datasets.
Their framework, LIMI (Less Is More for Intelligent Agency), builds on similar work in other areas of LLM research and finds that “machine autonomy emerges not from data abundance but from strategic curation of high-quality agentic demonstrations.”
In other words, it's data quality, not quantity, that matters.
In experiments, the researchers found that with a small, but carefully curated, dataset of just 78 examp [...]
2025-11-10
Baseten, the AI infrastructure company recently valued at $2.15 billion, is making its most significant product pivot yet: a full-scale push into model training that could reshape how enterprises wean [...]
2025-11-17
AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology [...]
2025-10-23
A new framework developed by researchers at Google Cloud and DeepMind aims to address one of the key challenges of developing computer use agents (CUAs): Gathering high-quality training examples at sc [...]
2025-11-19
Researchers at Meta, the University of Chicago, and UC Berkeley have developed a new framework that addresses the high costs, infrastructure complexity, and unreliable feedback associated with using r [...]
2025-11-13
Artificial intelligence agents powered by the world's most advanced language models routinely fail to complete even straightforward professional tasks on their own, according to groundbreaking re [...]
2025-05-26
Skullcandy isn’t a name that usually comes to mind when you think of premium headphones. The Utah-based company has primarily made its name in the budget space, selling more on low prices and loud, [...]
2025-11-14
Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning task [...]
2025-10-14
2025 was supposed to be the year of "AI agents," according to Nvidia CEO Jensen Huang, and other AI industry personnel. And it has been, in many ways, with numerous leading AI model provider [...]
2025-11-19
Fetch AI, a startup founded and led by former DeepMind founding investor, Humayun Sheikh, today announced the release of three interconnected products designed to provide the trust, coordination, and [...]