NVIDIA Unveils Vera, the CPU for Agents

NVIDIA launches high-performance, energy-efficient NVIDIA Vera CPUs to drive diverse workloads across industries, including agentic ...
IEEE

Reinforcement Learning to Enhance Digital Twin Based EDFA Fault Prediction in Optical Networks

Abstract: This study proposes a novel two-stage framework that integrates Digital Twin (DT) with Reinforcement Learning (RL) for failure prediction in optical communication networks. The framework ...
marktechpost

Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent

In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building reinforcement learning algorithms with JAX. We combine ...
VentureBeat

Databricks built a RAG agent it says can handle every kind of enterprise search

Most enterprise RAG pipelines are optimized for one search behavior. They fail silently on the others. A model trained to synthesize cross-document reports handles constraint-driven entity search ...
Analytics Insight

Top 10 Python Frameworks for Artificial Intelligence Projects

Top Python frameworks streamline the entire lifecycle of artificial intelligence projects from research to production. Modern Python tools enhance model performance, scalability, and deployment ...
GitHub

SCOPE-RL: A Python library for offline reinforcement learning, off-policy evaluation, and selection

SCOPE-RL is an open-source Python Software for implementing the end-to-end procedure regarding offline Reinforcement Learning (offline RL), from data collection to offline policy learning, off-policy ...
VentureBeat

Microsoft’s new AI framework trains powerful reasoning models with a fraction of the cost

Microsoft Research has developed a new reinforcement learning framework that trains large language models for complex reasoning tasks at a fraction of the usual computational cost. The framework, ...
GitHub

AI-Tango's Official Wii Reinforcement Learning Repository

This repository contains code to allow Reinforcement Learning agents to play Wii games. In this repo, we provide an example of: A Mario Kart Wii environment, using Luigi Circuit against Hard CPUs on ...
marktechpost

Optimizing Assembly Code with LLMs: Reinforcement Learning Outperforms Traditional Compilers

LLMs have shown impressive capabilities across various programming tasks, yet their potential for program optimization has not been fully explored. While some recent efforts have used LLMs to enhance ...
LinkedIn

Improving SCOOT with AI reinforcement learning

Fine tuning SCOOT can be a complex challenge, but this proof of concept suggests that AI can be a valuable ally in optimizing its outcomes. By continuously learning from real-time traffic conditions, ...
Nature

Comparison of algorithms using deep reinforcement learning for optimization of hyperbolic metamaterials

A hyperbolic metamaterial absorber has great potential for improving the performance of photo-thermoelectric devices targeting heat sources owing to its broadband absorption. However, optimizing its ...
eeworldonline

How do generative AI, deep reinforcement learning, and large language models optimize EDA?

Artificial intelligence (AI) and machine learning (ML) are playing an increasingly crucial role in optimizing electronic design automation (EDA) across the semiconductor industry. This article ...