The degradation is subtle but cumulative. Tools that release frequent updates while training on datasets polluted with ...

Google-spinoff Waymo is in the midst of expanding its self-driving car fleet into new regions. Waymo touts more than 200 million miles of driving that informs how the vehicles navigate roads, but the ...

When extreme weather strikes, the preparations of emergency planners can have life-or-death consequences. In July 2025, ...

SpaceX uses your data to train its machine learning and AI models and might share that with partners who 'help us develop AI-enabled tools that improve your customer experience.' From the laptops on ...

In this tutorial, we explore the Advanced Model Context Protocol (MCP) and demonstrate how to use it to address one of the most unique challenges in modern AI systems: enabling real-time interaction ...

Personal Data Servers are the persistent data stores of the Bluesky network. It houses a user's data, stores credentials, and if a user is kicked off the Bluesky network the Personal Data Server admin ...

. While informative, I noticed it currently lacks a motivating example and some supporting code. In my recent research, I explored warm starting by reusing a few layers from an LLM and retraining a ...

Some cars invite you in with chrome and comfort. The Model T invites you into a time machine, hands you three pedals that mean the wrong things, and politely asks you to learn 1910s. Then it coughs, ...

MUCH OF THE art of medicine involves working out, through detailed questioning and physical examination, which disease a given patient has contracted. Far harder, but no less desirable, would be ...

Modern large language models (LLMs) might write beautiful sonnets and elegant code, but they lack even a rudimentary ability to learn from experience. Researchers at Massachusetts Institute of ...

One of the biggest challenges early-stage startup founders face is predicting and managing revenue growth. In most organizations, this looks like top-down forecasting and starts with determining the ...

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, ...