VentureBeat

This new framework lets LLM agents learn from experience, no fine-tuning required

A new learning paradigm developed by University College London (UCL) and Huawei Noah’s Ark Lab enables large language model (LLM) agents to dynamically adapt to their environment without fine-tuning ...
Search Engine Land

LLM optimization in 2026: Tracking, visibility, and what’s next for AI discovery

Marketing, technology, and business leaders today are asking an important question: how do you optimize for large language models (LLMs) like ChatGPT, Gemini, and Claude? LLM optimization is taking ...
Search Engine Land

LLM perception match: The hurdle before fanout and why it matters

If LLMs don’t see you as a fit, your content gets ignored. Learn why perception is the new gatekeeper in AI-driven discovery. Before an LLM matches your brand to a query, it builds a persistent ...
Nature

‘Fighting fire with fire’ — using LLMs to combat LLM hallucinations

Text-generation systems powered by large language models (LLMs) have been enthusiastically embraced by busy executives and programmers alike, because they provide easy access to extensive knowledge ...

Why your LLM bill is exploding — and how semantic caching can cut it by 73%

Semantic caching is a practical pattern for LLM cost control that captures redundancy exact-match caching misses. The key ...
DMR News

LLM.co Releases Report Warning Most Companies Will Regret Public LLM Adoption

LLM.co today announced the release of a new industry report, Why Most Companies Will Regret Public LLM Adoption, offering a counter-consensus view on the ...