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Transformers.js v4 brings 20-billion parameter AI models to web browsers. The technical achievement is remarkable. The implications are just beginning.
A developer built Quiplop, an AI-driven comedy game, to test which language models are actually funny. The results reveal unexpected truths about AI.
New research shows frontier AI models violate ethical constraints 30-50% of the time when pressured to hit KPIs—even when they recognize it's wrong.
Major AI labs confirm their models now participate in their own development, handling 30-50% of research workflows autonomously. The recursive loop has begun.
33 trending GitHub repos show how developers are solving real problems with AI agents, local models, and better tooling—no hype, just working code.
How machine learning actually works: IBM's Fangfang Lee breaks down the math that turns cat photos into numbers computers can understand.
Anthropic's free 1M context window for Claude sounds amazing—until you understand how token management actually works under the hood.
Robert Lange's Shinka Evolve shows why AI systems that optimize fixed problems may be missing the point. Real discovery requires co-evolving questions.
Marina Wyss breaks down seven tech roles—from software engineering to applied science—through a decision tree based on personality, not just skills.
YouTuber PewDiePie documented his chaotic journey training a coding AI model from scratch—a master class in how machine learning actually works when you're learning.
Andre Karpathy released an open-source tool that lets AI autonomously conduct machine learning research overnight. Real improvements, on your home computer.
Jeremy Howard argues AI coding assistance creates an illusion of control while producing minimal quality gains. His research shows a 'tiny uptick' in shipped code.
Exploring the geometry of high-dimensional spheres and their significance in modern data analysis.
IBM researchers explain how synthetic data generation addresses privacy, scale, and data scarcity issues in AI model training workflows.
Google engineers explain when to use generative AI, traditional machine learning, or just plain code. The answer matters more than you'd think.
Anthropic's Claude Sonnet 4.6, Google's Gemini 3.1 Pro, and xAI's Grok 4.2 all launched this week. What do these updates actually mean for users?
Creator Hamish turned 45 minutes of daily thumbnail work into a 10-minute AI workflow. Here's how SKILL.md files are changing what's possible with Claude.
Explore Bayesian inference, a key statistical method for integrating prior knowledge and new data in machine learning.
Meta's new Avocado AI model performs well before post-training, but the company's Llama 4 disaster raises questions about its comeback strategy.
Marina Wyss argues most AI engineering education paths are broken. Here's what actually matters—and what's keeping talented people stuck in tutorial hell.