hallucinations..

a few failure that was something interesting. For months, I — together with a whole lot of others — have tried to construct a neural network that might learn to detect when AI systems...

“What I cannot create, I don't understand” — attributed to R. Feynman After Vibe Coding, we appear to have entered the (very area of interest, but much cooler) era of Vibe Proving: DeepMind wins gold...

Good morning. It’s Monday, September eighth.On this present day in tech history: In 2012the Google Brain team led by Andrew Ng and Jeff Dean showed that a large-scale neural network could learn to...

Hirundo, the primary startup dedicated to machine unlearning, has raised $8 million in seed funding to handle a few of the most pressing challenges in artificial intelligence: hallucinations, bias, and embedded data vulnerabilities. The...

AI is revolutionizing the best way nearly every industry operates. It’s making us more efficient, more productive, and – when implemented appropriately – higher at our jobs overall. But as our reliance on this...

Recent research from Russia proposes an unconventional method to detect unrealistic AI-generated images – not by improving the accuracy of enormous vision-language models (LVLMs), but by intentionally leveraging their tendency to hallucinate.The novel approach...

Introduction In a YouTube video titled , former Senior Director of AI at Tesla, Andrej Karpathy discusses the psychology of Large Language Models (LLMs) as emergent cognitive effects of the training pipeline. This text is inspired by his...

Although synthetic data is a strong tool, it may well only reduce artificial intelligence hallucinations under specific circumstances. In almost every other case, it's going to amplify them. Why is that this? What does...