AI data trainer roles have moved from obscure contractor gigs to a visible career path with clear pay bands and defined ...

Decode the AI buzzwords you see daily. Learn 10 essential terms, such as model, tokens, prompt, context window, and ...

Using Shad CN and an open source helper, the model produced pages and components, helping you decide when to trust it for UI work.

First, institutions must ensure that synthetic datasets are continuously recalibrated against fresh, real-world evidence. The ...

Step aside, LLMs. The next big step for AI is learning, reconstructing and simulating the dynamics of the real world.

Oracle Corp. today announced the general availability of Oracle AI Database 26ai and Oracle Autonomous AI Lakehouse, both aimed at supporting artificial intelligence training and inference across ...

Abstract: The widespread adoption of laser powder bed fusion (LPBF) additive manufacturing is hampered by process unreliability problems. Modeling the melt pool behavior in LPBF is crucial to develop ...

Abstract: The widespread adoption of Transformers in deep learning, serving as the core framework for numerous large-scale language models, has sparked significant interest in understanding their ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Model Context Protocol, or MCP, is arguably the most powerful innovation in AI integration to date, but sadly, its purpose and potential are largely misunderstood. So what's the best way to really ...