A diary entry on Chapter 1 of the AI Safety Atlas, focusing on AI capabilities, the progression toward AGI, and frameworks for measuring AI intelligence.

A diary entry on Unit 1 of the BlueDot AI Alignment course, covering foundational concepts like neural networks, gradient descent, transformers, and the future impacts of AI.

A diary entry summarizing several introductory resources on how AI learns, including machine learning concepts, Large Language Models (LLMs), and the progress of the deep learning revolution.

A diary entry on the ‘AI Triad’ (algorithms, data, compute) and its implications for national security, based on the BlueDot AI Governance course.

A diary entry summarizing chapters 6-10 of the ‘Introduction to AI Safety, Ethics, and Society’ textbook, covering beneficial AI, machine ethics, collective action problems, governance, and utility functions.

A diary entry summarizing chapters 1-5 of the ‘Introduction to AI Safety, Ethics, and Society’ textbook, covering catastrophic AI risks, AI fundamentals, single-agent safety, safety engineering, and complex systems.

A diary entry on exploring the ‘Effectiveness Mindset’ from the Effective Altruism Handbook, in the context of AI safety and governance.

A comprehensive list of the best books and online courses to prepare for coding and system design interviews.

A curated list of helpful resources for preparing for system design interviews, including books, online courses, and practice platforms.

An in-depth guide to the Top K Problem and Heavy Hitters in system design interviews. Explore exact and approximate solutions, distributed system considerations, and real-world applications for finding the most frequent elements in large datasets and data streams.