LLMs Outperform Compilers: Reinforcement Learning Unlocks AI-Powered Assembly Optimization
The compiler wars just got interesting
For decades, software engineers have relied on compilers like GCC to translate high-level code
NVIDIA's HelpSteer3-Preference Dataset: A Game-Changer for Training Reward Models
NVIDIA has unveiled HelpSteer3-Preference, a groundbreaking open dataset designed to revolutionize the training of reward models for large language models
MOSAAIC: A New Framework for Balancing Human-AI Control in Creative Collaboration
The rise of generative AI tools like ChatGPT, Midjourney, and Runway has transformed how humans and machines collaborate creatively. But
MathCoder-VL: How Code is Revolutionizing Multimodal Math AI
The Problem with Math and AI Today
Large multimodal models (LMMs) have gotten scarily good at describing photos of cats
FORTRESS: How AI is Making Robots Safer in Unpredictable Environments
Autonomous robots are increasingly operating in unstructured, open-world environments—from delivery drones navigating urban landscapes to quadruped robots inspecting construction
Does Feasibility Matter? How Synthetic Training Data Impacts AI Performance
With the rise of photorealistic diffusion models, synthetic data is increasingly used to train AI systems. But these models often
Neural Thermodynamic Laws: A New Framework for Understanding LLM Training Dynamics
Large language models (LLMs) are often described as black boxes, with their training dynamics governed by empirical observations rather than
How IBM is training AI to explain VHDL code for high-performance chip design
IBM’s quest to make AI understand VHDL
Designing high-performance microprocessors is a notoriously complex task, requiring deep expertise in
CodePDE: How LLMs Are Revolutionizing PDE Solving Without Specialized Training
The Challenge of PDE Solving
Partial Differential Equations (PDEs) are the backbone of modeling physical systems, from fluid dynamics to
AI Agents Inherit Human Biases in Causal Reasoning—Here’s How to Fix It
Language model (LM) agents are increasingly being deployed as autonomous decision-makers, tasked with gathering information and inferring causal relationships in
