Microsoft researchers have developed On-Policy Context Distillation (OPCD), a training method that permanently embeds ...

Reasoning large language models (LLMs) are designed to solve complex problems by breaking them down into a series of smaller ...

If mHC scales the way early benchmarks suggest, it could reshape how we think about model capacity, compute budgets and the ...

The company open-sourced an 8 billion parameter LLM, Steerling-8B, trained with a new architecture designed to make its ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

Pretraining a modern large language model (LLM), often with ~100B parameters or more, typically involves thousands of ...

Running large language models at the enterprise level often means sending prompts and data to a managed service in the cloud, much like with consumer use cases. This has worked in the past because ...

Explore how Indian firms are training Large Language Models, overcoming challenges with data, capital, and innovative ...

PALO ALTO, Calif.--(BUSINESS WIRE)--TensorOpera, the company providing “Your Generative AI Platform at Scale,” has partnered with Aethir, a distributed cloud infrastructure provider, to accelerate its ...

ByteDance's Doubao AI team has open-sourced COMET, a Mixture of Experts (MoE) optimization framework that improves large language model (LLM) training efficiency while reducing costs. Already ...

Enter large language model (LLM) evaluation. The purpose of LLM evaluation is to analyze and refine GenAI outputs to improve their accuracy and reliability while avoiding bias. The evaluation process ...

Claude-creator Anthropic has found that it's actually easier to 'poison' Large Language Models than previously thought. In a recent blog post, Anthropic explains that as few as "250 malicious ...