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669 articles
This explainer explores agentic AI - autonomous systems capable of planning, executing, and adapting to complex environments. Learn how these multi-agent systems work, why they matter for businesses, and why only 15% of organizations have achieved scaled adoption.
OpenAI is expanding AI agents beyond developer use cases to everyday consumers, but widespread adoption faces significant challenges.
Learn what 'stealth models' in AI mean, how they work, and why their secrecy matters for technology transparency and ethics.
This article explains how AI agents like Luna can make decisions such as firing employees, but still need human guidance to act responsibly.
Learn how Faraday, an AI agent created by DeepMind alumni, can read and replicate scientific research faster than traditional methods, potentially accelerating scientific discovery.
This article explains how AI agents use 'skills' to complete tasks and why having too many skills can actually hurt their performance. It's an important lesson for building better AI systems.
Learn what AI agents are, how they work, and why companies like AWS are using them to automate tasks. Understand how these smart tools work alongside humans rather than replacing them.
A new Coddy Developer Survey found that 80% of developers feel their use of AI has become more like a dependence than an advantage. The findings raise concerns about over-reliance on AI tools in software development.
OpenAI launches AI Futures blog to explore how transformative AI could reshape power, governance, the economy, and individual freedom.
Ramp has launched Router, an AI model routing service that allows businesses to seamlessly switch between various large language models via API. The move positions Ramp in the growing AI middleware market.
Learn what AI training data is, why it's so valuable, and how companies like Micro1 are capitalizing on the growing demand for high-quality examples that teach AI systems to recognize patterns and make decisions.
AI systems are revolutionizing mathematical problem-solving, prompting existential questions among mathematicians about the future of their discipline and the role of human intuition in mathematical discovery.
