The more accurate we try to make AI models, the bigger their carbon footprint — with some prompts producing up to 50 times more carbon dioxide emissions than others, a new study has revealed.

Progress will come from systems that can combine language understanding with explicit spatial and structural reasoning.

SAN FRANCISCO, May 24, 2024 — Predibase recently launched the Fine-Tuning Index to showcase how fine-tuning open source LLMs dramatically improves their performance for production applications, ...

The advent of LLMs has reopened a debate about the limits of machine intelligence — and requires new benchmarks of what reasoning consists of. Since their public release less than two years ago, large ...

Artificial intelligence is increasingly used as a tool in many health care settings, from writing physicians' notes to making ...

Recalling our discussion in Part 1 on data security and cost management, this second installment focuses on the critical element of transparency in using LLMs. Understanding how AI tools derive their ...

The explosive adoption of large language models (LLMs) within all types and sizes of businesses is well-documented and is only accelerating as corporations build their own LLMs based on local LLMs ...

Large language models (LLMs) can provide generally accurate and patient-appropriate information for common postoperative Mohs surgery questions, particularly when guidance is straightforward and ...

Ollama AI devs have released a native GUI for MacOS and Windows. The new GUI greatly simplifies using AI locally. The app is easy to install, and allows you to pull different LLMs. If you use AI, ...