Amazon’s streaming dongle is built for life online, but a patchy connection or a data cap does not automatically turn it into ...

Abstract: This paper mainly develops a data-driven modeling approach for aeroengine systems. To describe how the system behaves dynamically, a state variable model is constructed, and it is further ...

Struggling in that PS5 game? Don't worry, a ghost player who can look like Yoda trained on YouTube, Twitch and social media ...

Learn how to run local AI models with LM Studio's user, power user, and developer modes, keeping data private and saving monthly fees.

Explore Open Notebook and HyperbookLM with mind maps, slide decks, and web scraping, helping you turn raw files into clear ...

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 ...

My name is Bill Burkett, and I am a data modeler. I don’t call myself that often and sometimes have misgivings about doing so. I often get the feeling that being a “data modeler,” when considered in ...