The article "AI Harms and Their Technical Causes" discusses how specific technical decisions in AI development can result in safety failures. It examines the underlying causes of these harms and offers guidance on alternative approaches to mitigate risks. The piece highlights the importance of thoughtful design choices in preventing unintended negative outcomes from AI systems.
By Stephanie Kirmer
The article titled "The AI That Learned to Understand Long After It Stopped Trying" discusses a small, strange discovery in machine learning known as grokking. It highlights how this phenomenon involves an AI developing understanding after ceasing to actively try. The piece was originally published on Towards Data Science.
By Utkarsh Mangal
Research Manager Mike Walker discusses his career across hacker culture, cybersecurity, and AI, offering insights into trust, teamwork, leadership, and the importance of curiosity, judgment, and agility for tackling tough problems. He emphasizes that understanding the rules is essential for effective problem‑solving in these fields.
By Weishung Liu, Mike Walker
How to set the rules that keep agents effective and out of trouble The post What AI Agents Should Never Do on Their Own appeared first on Towards Data Science .
By Sara Nobrega
Microsoft Research Focus – Edition #97 features host Sowbhagya Suresh discussing recent developments across Microsoft. Topics include challenges faced by coding agents, insights into how people use AI at work, and advancements in extended‑range weather forecasting. The episode highlights cutting‑edge research and practical applications within the company.
By Sowbhagya Suresh
The article discusses how computer programming fundamentally involves problem‑solving with computers and managing complexity. It argues that these skills will remain valuable and sustain a viable career even as AI tools become more prevalent.