When a standard large language model (LLM) is confronted with a problem, it tries to solve it by matching it to similar information it has seen before, and then give an answer based on those past ...

As I highlighted in my last article, two decades after the DARPA Grand Challenge, the autonomous vehicle (AV) industry is still waiting for breakthroughs—particularly in addressing the “long tail ...

Looped language model training cannot control hidden-state norm growth because RMSNorm normalizes scale away before the loss sees it. A paper posted today on arXiv identifies this readout blind spot, ...

Bigger has defined AI from day one. New data says task-specific small models beat frontier LLMs on accuracy, cost and speed — ...

Researchers at OpenAI trained a single language model on 175 billion learned numerical weights, each one adjusted during training to predict the next word in a sequence. That model, GPT-3, ...

The proliferation of edge AI will require fundamental changes in language models and chip architectures to make inferencing and learning outside of AI data centers a viable option. The initial goal ...

Anthropic Claude provides open access to their system-wide prompt. I analyze the portions dealing with AI mental health guidance. An AI Insider analysis and scoop.

A new University of Massachusetts Amherst study delivers clear evidence of how large language models (LLMs), such as ChatGPT, are reshaping the landscape of academic research. It applies a new ...