Category: AI

Anthropic’s latest research investigates a critical security frontier in artificial intelligence: the emergence of insider threat-like behaviors from large language model (LLM) agents. The study, “Agentic Misalignment: How LLMs…

LLM-Based Code Generation Faces a Verification Gap

LLMs have shown strong performance in programming and are widely adopted in tools like Cursor and GitHub Copilot to boost developer productivity. However, due to their…

Or: Why “Can we turn off generation” might be the smartest question in generative AI

Not long ago, I found myself in a meeting with technical leaders from a large enterprise. We were discussing Parlant as a solution for…

A large language model (LLM) deployed to make treatment recommendations can be tripped up by nonclinical information in patient messages, like typos, extra white space, missing gender markers, or the use of uncertain,…

In this tutorial, we walk you through the design and implementation of a custom agent framework built on PyTorch and key Python tooling, ranging from web intelligence and data science modules to advanced code generators. We’ll…

The Challenge of Scaling 3D Environments in Embodied AI

Creating realistic and accurately scaled 3D environments is essential for training and evaluating embodied AI. However, current methods still rely on manually designed 3D…

Google’s Magenta team has introduced Magenta RealTime (Magenta RT), an open-weight, real-time music generation model that brings unprecedented interactivity to generative audio. Licensed under Apache 2.0 and available on GitHub…

The DeepSeek Researchers just released a super cool personal project named ‘nano-vLLM‘, a minimalistic and efficient implementation of the vLLM (virtual Large Language Model) engine, designed specifically for users who value…

The development and deployment of advanced AI systems increasingly depend on flexible, robust orchestration layers that bridge diverse models, tools, and resources. IBM’s MCP Gateway addresses this need by providing a…

The debate around the reasoning capabilities of Large Reasoning Models (LRMs) has been recently invigorated by two prominent yet conflicting papers: Apple’s “Illusion of Thinking” and Anthropic’s rebuttal titled “The…