Human ai collaboration

How a reasoning model cracked an 80-year-old math problem — the OpenAI Podcast Ep. 20

How a reasoning model cracked an 80-year-old math problem — the OpenAI Podcast Ep. 20

OpenAI's reasoning researchers discuss how a general-purpose AI model disproved an 80-year-old conjecture from mathematician Paul Erdős. They detail the journey from initial IMO/IOI breakthroughs to the verification of the proof, highlighting the model's creative application of advanced number theory. The episode explores the profound implications for the future of mathematics, AI-human collaboration, and the broader scientific landscape, offering advice for researchers seeking to leverage AI for groundbreaking discoveries.

Ideas: Steering AI toward the work future we want

Ideas: Steering AI toward the work future we want

Microsoft researchers unpack the New Future of Work Report 2025, exploring AI's real-world impact. They discuss adoption trends, the shift in job tasks, and the crucial distinction between viewing AI as a simple tool versus a collaborator. The conversation emphasizes moving beyond pure efficiency to consciously design a future where AI supports human flourishing and meaningful work.

What a $42B Software Co. Really Spends on AI Tools | Mike Cannon-Brookes

What a $42B Software Co. Really Spends on AI Tools | Mike Cannon-Brookes

Atlassian Co-Founder & CEO Mike Cannon-Brookes shares insights from a massive internal study of over 10,000 engineers using AI coding tools. He discusses the true measures of developer productivity, the future of developer roles, and why human-AI collaboration, powered by organizational context, is the key to the future.

The Limits of AI: Generative AI, NLP, AGI, & What’s Next?

The Limits of AI: Generative AI, NLP, AGI, & What’s Next?

Exploring the evolution of AI, this summary breaks down the Data-Information-Knowledge-Wisdom hierarchy, revisits past predictions about AI's limits that have since been surpassed—such as reasoning and creativity—and delves into current challenges like hallucinations, AGI, and sustainability. It concludes by framing a collaborative future where humans define the 'what' and 'why,' while AI executes the 'how'.