The industry has a plan for building smarter models. It doesn't have a plan for the evaluators those models depend on.

Imagine trying to teach a child how to solve a tricky math problem. You might start by showing them examples, guiding them step by step, and encouraging them to think critically about their approach.

The Essential Cloud for AI™, today announced CoreWeave Sandboxes, an execution layer that gives AI researchers and platform teams secure, isolated environments for running reinforcement learning (RL), ...

Months-old Ineffable Intelligence announced a record $1.1 billion seed round in April.

Reinforcement Learning does NOT make the base model more intelligent and limits the world of the base model in exchange for early pass performances. Graphs show that after pass 1000 the reasoning ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I will identify and discuss an important AI ...

Nvidia said SpaceX was among the first companies evaluating the Vera CPU. ・SpaceXAI is evaluating Vera for reinforcement learning and simulation workloads for its AI training stack. ・SpaceX is ...

The architecture of FOCUS. Given offline data, FOCUS learns a $p$ value matrix by KCI test and then gets the causal structure by choosing a $p$ threshold. After ...

This work presents an AI-based world model framework that simulates atomic-level reconstructions in catalyst surfaces under dynamic conditions. Focusing on AgPd nanoalloys, it leverages Dreamer-style ...

Precision modeling: A new AI framework acts as a 'coach' for neuromechanical models, guiding refinements to better match real animal motion. Streamlined complexity: The system adds detail only where ...