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马丁·赫尔曼在播客中讲述了他与NSA在公钥密码学上的冲突经历，回顾了密码学历史及其对现代互联网安全的影响。
In a CNBC interview, Palantir CEO Alex Karp defended against Wall Street concerns that AI could replicate Palantir's work, arguing that AI companies lack deep understanding of complex enterprise problems.
Promoting an upcoming interview with AI researcher Nathan Lambert on Valley101, discussing his visit to top Chinese AI labs and companies.
Peter Yang is interviewing Karan4D, co-founder of NousResearch's Hermes, and asks for topic suggestions from the community.
A podcast interview with Kent Beck covers his career from early programming to Agile and TDD, emphasizing the importance of human skills in software engineering.
Gödel Prize winner Ryan Williams offers a contrarian view on P vs NP, arguing that our understanding of polynomial time computation is still shallow and full of surprises, putting his confidence in P≠NP at 80%.
Gergely Orosz announces an upcoming event with Kent Beck tomorrow.
Grant Sanderson and Dwarkesh Patel discuss how AI is making rapid progress in mathematics, the nature of conceptual breakthroughs, and what this means for other fields as AI advances.
Anders Hejlsberg, creator of TypeScript and C#, discusses the benefits of building in the open on GitHub, where 12 years of issues and decisions are searchable.
Micron's VP and GM of Cloud Memory Products discusses how AI demand is driving a memory super cycle, with technologies like HBM, LPDDR6, and PCIe Gen 6 SSDs becoming critical for data center architectures.
MIT News interviews Professor Phillip Isola about agentic AI, covering its definition, differences from generative AI, challenges like lack of training data, and promising applications such as coding agents.
Sebastian Mallaby predicts that by 2028, AI will achieve recursive self-improvement, where frontier models autonomously code the next generation, leading to vertical progress and ending the race for superintelligence.
Tim Ferriss shares a quote from Sebastian Mallaby warning about deceptive AI and existential risk, promoting Mallaby's podcast interview discussing his new book on Demis Hassabis and the race to superintelligence.
Shane Parrish shares a conversation with Harvey co-founder Winston Weinberg about decision-making principles and what leads to employee termination.
In an interview, Rebellions CEO Sunghyun Park discusses the company's memory-centric architecture approach to AI inference, aiming to compete with NVIDIA by offering greater efficiency and lower costs.
麻省理工学院教授、哥德尔奖得主瑞安·威廉姆斯在一期播客中深入讨论了算法优化、细粒度复杂性理论以及强指数时间假说等前沿计算机科学话题。
A Twitter post shares an anecdote about interviewing an AI engineer who lacked knowledge of latest frameworks but excelled at debugging a real-world performance issue, emphasizing the value of practical problem-solving over tool familiarity.
A hiring manager shares a candidate's correct definitions of RAG and fine-tuning, then asks followers to explain when to use one over the other.
Cory Doctorow discusses strategies to address the AI bubble and advocates for local AI in an interview on ArsTechnica.
A fifth-year CS PhD student at Brown University shares surprising lessons from their research scientist job search, including that only one or two papers matter and that interviews often focus on solving team problems rather than past research.