AI/ML are driving a steep ramp in neural processing unit (NPU) design activity for everything from data centers to edge ...

Abstract: Network-on-Chip (NoC) has emerged as the most promising on-chip interconnection framework in Multi-Processor System-on-Chips (MPSoCs) due to its efficiency and scalability. In the deep ...

Introduction: The learning process is characterized by its variability rather than linearity, as individuals differ in how they receive, process, and store information. In traditional learning, taking ...

SAN FRANCISCO, Oct 24 (Reuters) - IBM (IBM.N), opens new tab said on Friday it can run a key quantum computing error correction algorithm on commonly available chips ...

An artificial-intelligence algorithm that discovers its own way to learn achieves state-of-the-art performance, including on some tasks it had never encountered before. Joel Lehman is at Lila Sciences ...

This past spring, Anthropic introduced learning mode, a feature that changed Claude's interaction style. When enabled, the chatbot would, following a question, try to guide the user to their own ...

Reinforcement learning (RL) plays a crucial role in scaling language models, enabling them to solve complex tasks such as competition-level mathematics and programming through deeper reasoning.

This repository provides context to the manuscript "FPGA-Enabled Machine Learning Applications in Earth Observation: A Systematic Review" submitted to ACM CSUR and available on arXiv. The data from ...

Reasoning capabilities represent a fundamental component of AI systems. The introduction of OpenAI o1 sparked significant interest in building reasoning models through large-scale reinforcement ...