AI-driven system blends literature, experiments and robotics to discover new materials

Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables.

Thinking Machines' first official product is here: meet Tinker, an API for distributed LLM fine-tuning

Thinking Machines, the AI startup founded earlier this year by former OpenAI CTO Mira Murati, has launched its first product: Tinker, a Python-based API designed to make large language model (LLM) ...
InfoWorld

How to deploy machine learning models with AWS Lambda

AWS Lambda provides a simple, scalable, and cost-effective solution for deploying AI models that eliminates the need for ...

Easily Fine-Tune AI Models Like a Pro with Google Tunix

Discover how to fine-tune large language models with Tunix, the open-source library that simplifies AI customization and ...

Peering inside political AI: How LLMs responded to the 2024 election

In the months leading up to the 2024 U.S. presidential election, a team of researchers at MIT CSAIL, MIT Sloan, MIT LIDS, set ...

Local LLMs vs Cloud AI : How Local LLMs Are Changing AI Workflows

Discover how to run large language models locally for faster AI, better privacy, and unmatched control over your workflows. Learn more now!

Mira Murati’s Stealth AI Lab Launches Its First Product

Thinking Machines Lab, led by a group of prominent former OpenAI researchers, is betting that fine-tuning cutting-edge models ...
C&EN

Machine learning helps density functional theory model molecules accurately

Trained on quantum data, a new model makes computations more accurate while keeping computer costs low ...
RMD Open

Systemic lupus erythematosus damage risk index (SLE-DRI): a simple machine learning-based tool for identifying patients at risk for early organ damage

Objective Organ damage is a key determinant of poor prognosis and increased mortality in systemic lupus erythematosus (SLE).