Use your stack on whichever hardware you happen to be using at the time ...

Alibaba's SkillWeaver framework routes AI agents through massive tool libraries with 99% less token consumption. Here's how ...

NVIDIA diffusion language model Nemotron TwoTower achieves 2.42x LLM inference throughput without a full retraining run, ...

Tom Fenton moves from local AI concepts to hands-on tools for matching LLMs to hardware, running local chatbots with Ollama and benchmarking AI performance.

To improve an AI agent’s performance, the typical approach is to fine-tune the model, which requires training data and resources. Microsoft’s SkillOpt offers a different approach by enhancing a ...

Abstract: This paper presents LogiCode, a novel framework that leverages Large Language Models (LLMs) for identifying logical anomalies in industrial settings, moving beyond the traditional focus on ...

Look to these key metrics and benchmarks to evaluate the performance, capability, reliability, and safety of your AI models and agents. We’ve all heard the mantra from the quants in the business ...

Security professionals have spent two decades defending against human attackers who use automation as a force multiplier. That model is obsolete. The adversary now fielding against every ...

In 2026, organizations are tackling the “semantic gap” in AI outputs by embedding LLM-as-judge evaluations, multi-prompt chains, and human oversight directly into CI/CD pipelines. Tools like Vellum, ...

Tests of how well 19 large language models (LLMs) complete and perform complicated multi-step tasks has shown that they are both error-prone and, in many cases, unreliable. They said that the ...

To understand what makes TokenSpeed’s design choices meaningful, it helps to understand what makes agentic inference hard. Coding agents don’t behave like a typical chatbot turn. Contexts routinely ...