Agent context layers: Enterprises governing their AI data are catching twice as many bad answers as the ones who aren't

Across 101 enterprises, the context feeding AI agents is failing often and repeatedly. Sixty-eight percent have traced a confident but wrong agent answer to missing or inconsistent business context in [...]

Ask Engadget: How do I answer calls on my iPhone with only my voice?

Last August, my best friend asked me how she could help her neighbor set her iPhone so she could answer it without picking it up. The neighbor had Multiple Sclerosis (MS), and had lost dexterity in bo [...]

One AI module faked 86% of a pipeline's accuracy gains by feeding another the answers

A retrieval-augmented generation (RAG) system is built to answer strictly from the documents it retrieves. But when engineers optimize these AI pipelines end-to-end, the reader module can learn a shor [...]

The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix

Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context sourc [...]

Scientists find lead really can be turned into gold (with help from the Large Hadron Collider)

One of the ultimate goals of medieval alchemy has been realized, but only for a fraction of a second. Scientists with the European Organization for Nuclear Research, better known as CERN, were able to [...]

How I Get Free Traffic from ChatGPT in 2025 (AIO vs SEO)

Three weeks ago, I tested something that completely changed how I think about organic traffic. I opened ChatGPT and asked a simple question: "What's the best course on building SaaS with Wor [...]

Agentic orchestration: Enterprise AI organizations know how to govern agents but still can't meter what they cost

Across 107 enterprises, agentic orchestration is not a choice of a single platform.The typical enterprise runs three orchestration platforms at once, and selects them for flexibility across models rat [...]

An eval harness found what qualitative review couldn't: AI models are most confident when wrong

There is a step in the development process for large language model (LLM)-assisted tooling that most teams skip because it's tedious, time-consuming, and doesn't produce results visible to e [...]

Frontier models can recover up to 65% of facts they can't directly recall — just by thinking longer

When large language models (LLMs) hallucinate, developers typically assume the model lacks the required facts. Engineering teams diagnose the error as missing knowledge. The standard response is to in [...]