How 2025 Recalibrated AI Models Race

In 2025, large language models moved beyond benchmarks to efficiency, reliability, and integration, reshaping how AI is ...

How AI coding agents work—and what to remember if you use them

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...
IEEE

Attention-Based Convolutional Neural Network Model for Skin Cancer Classification

Abstract: Early detection of skin cancer (SC) is paramount for effective treatment. Although convolutional neural networks (CNN) have facilitated automated learning of high-level features from ...
Frontiers

FLEM-XAI: Federated learning based real time ensemble model with explainable AI framework for an efficient diagnosis of lung diseases

The computer-aided diagnosis helps medical professionals detect and classify lung diseases from chest X-rays by leveraging medical image processing and central server-based machine learning models.
Forbes

The Four AI Business Models Reshaping The Future Of Enterprise

How are businesses building, leveraging, and embedding AI into their day-to-day? This article discusses key considerations when building AI companies or procuring their services. As artificial ...
VentureBeat

New AI architecture delivers 100x faster reasoning than LLMs with just 1,000 training examples

Singapore-based AI startup Sapient Intelligence has developed a new AI architecture that can match, and in some cases vastly outperform, large language models (LLMs) on complex reasoning tasks, all ...
Semiconductor Engineering

Computer Architecture Extending The Von Neumann Model With A Dedicated Reasoning Unit For Native Artificial General Intelligence (TU Munich, Pace U.)

A new technical paper titled “Augmenting Von Neumann’s Architecture for an Intelligent Future” was published by researchers at TU Munich and Pace University. “This work presents a novel computer ...
Wired

A New Kind of AI Model Lets Data Owners Take Control

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.