A new study from Anthropic introduces "persona vectors," a technique for developers to monitor, predict and control unwanted LLM behaviors.

The humble database offers the key to giving AI context and adaptation, accessing data beyond its training cutoff.

Behind Anthropic, you'll find OpenAI, which now has 25%; Google with 20%; and Meta Llama with 9%. All the way in the back, ...

Here in the United States, the rise in antisemitic incidents and questions of how criticism of Israel relates to antisemitism ...

Combining an open source orchestration platform and various LLMs, TritonGPT is a collection of UCSD-specific AI assistants ...

A coding nonprofit turned down a $1.5M NSF grant after new DEI restrictions, highlighting the clash between federal policy ...

The development of a semiconductor system is more complex than just describing functionality in RTL. How ready are AI models ...

My guest today is the founder of a Silicon Valley startup that promises would-be parents, a new level of genetic screening for their embryos, and that looks forward to a future where most embryos, and ...

From concept to execution, City of Dreams pushes the laws of physics, redefines paradigms and smashes limitations. This ...

In another approach, Pradel and Ph.D. researcher Aryaz Eghbali have presented De-Hallucinator, a technique for mitigating LLM ...

The big takeaway from this year's Linux Foundation tech talent report is that despite fears of layoffs, jobs are being ...