There’s no doubt the AI-generated code landscape evolved at an unprecedented rate over the last year. The rise of vibe coding, where developers use large language models (LLMs) to generate functional ...

Large language models (LLMs) have demonstrated impressive capabilities in natural language understanding and automation, but our experience shows they are not yet suited for the specific, high-stakes ...

The real artificial intelligence crisis isn't what the models might hallucinate - it's what they'll never forget. The rapid adoption of AI has created a "Shadow IT 2.0" scenario, in which employees ...

Hallucinations in LLMs: Why they happen, how to detect them and what you can do. As large language models (LLMs) like ChatGPT, Claude, Gemini and open source alternatives become integral to modern ...

Give a large language model broad access to data and it becomes the perfect insider threat, operating at machine speed and without human judgment. Large language models (LLMs) have quickly evolved ...

Not long ago, I watched two promising AI initiatives collapse—not because the models failed but because the economics did. In one case, an organization proudly launched an agentic AI system into ...

One of the most frustrating things about using a large language model is dealing with its tendency to confabulate information, hallucinating answers that are not supported by its training data. From a ...

The use of large language models (LLMs) as an alternative to search engines and recommendation algorithms is increasing, but early research suggests there is still a high degree of inconsistency and ...