AI agents can handle physics-based modeling complexity while engineers focus on design judgment and tradeoffs.

When AI can pass the tests that we once defined as intelligence, working harder to beat it isn’t a smart approach. The solution is to rethink what those tests were really measuring.

OpenAI’s latest coding-focused AI model is being promoted as a major leap forward for software development—faster prototyping ...

After 5 years of work and over 2700 commits against the reference software, the Alliance for Open Media (AOMedia) has ...

By Karyna Naminas, CEO of Label Your Data Choosing the right AI assistant can save you hours of debugging, documentation, and boilerplate coding. But when it comes to Gemini vs […] ...

Software developers have spent the past two years watching AI coding tools evolve from advanced autocomplete into something that can, in some cases, build entire applications from a text prompt. Tools ...

Kanata, a Rust tool for keyboard mapping, supports every keyboard including laptops, so you get smoother on-letter modifiers ...

As companies move to more AI code writing, humans may not have the necessary skills to validate and debug the AI-written code if their skill formation was inhibited by using AI in the first place, ...

Struggling to debug your physics simulations in Python? This video uncovers common mistakes that cause errors in physics code and shows how to identify and fix them efficiently. Perfect for students, ...

"I’ve learned a lot from being an escort, and one of the biggest lessons has been that cheating is common but divorce doesn’t have to be." ...

Large language models (LLMs), such as Codex, hold great promise in enhancing programming education by automatically generating feedback for students. We investigate using LLMs to generate feedback for ...