Print Join the Discussion View in the ACM Digital Library The mathematical reasoning performed by LLMs is fundamentally different from the rule-based symbolic methods in traditional formal reasoning.

Microchip’s products are long-time embedded-design workhorses, and the new solutions turn its MCUs and MPUs into complete platforms for bringing secure, efficient and scalable intelligence to the edge ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

TinyML sensors detect chainsaws, gunshots, and animal calls offline, offering a new way to protect wildlife in remote ...

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...

Another machine unlearning method recently was developed specifically for AI-generated voices. Jong Hwan Ko, an associate ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

The reason for this shift is simple: data gravity. The core holds the most complete, consistent and authoritative dataset available to the institution. Moving AI decisioning closer to this data ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Many small businesses use AI tools every day, but how do they actually work? And where does all that “knowledge” come from?imageAI models may seem incredibly smart, but there’s no magic involved.

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with projects that support AI development.