Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...

Maximize Market Research's Smart Factory Market Global Outlook (2025–2032) highlights rapid adoption of Industry 4.0 principles, ...

MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, continuously learning agent.

AI agents help businesses stop guessing — linking predictions to actions so teams can move from “what might happen” to ...

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to probabilistic, generative, and self-learning systems. AI-driven DQ frameworks ...

For a minimal example of how to use the environment framework, refer to examples/simple-calculator. For the environment and training data used in our paper, see AgentBench FC. For reproducing the ...

Last week Nvidia finally got permission to sell one of its most advanced semiconductor chips to China. The catch: The federal government will take 25% of the revenue from those sales. The Nvidia deal ...

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...

The Eagles guitarist previewed his auction items at The Troubadour in Los Angeles on Monday, Dec. 8 Ilana Kaplan is a Staff Editor at PEOPLE. She has been working at PEOPLE since 2023. Her work has ...

Reinforcement learning (RL) is machine learning (ML) in which the learning system adjusts its behavior to maximize the amount of reward and minimize the amount of punishment it receives over time ...

Download PDF Join the Discussion View in the ACM Digital Library Deep reinforcement learning (DRL) has elevated RL to complex environments by employing neural network representations of policies. 1 It ...