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Research#llm📝 BlogAnalyzed: Dec 25, 2025 13:10

MicroQuickJS: Fabrice Bellard's New Javascript Engine for Embedded Systems

Published:Dec 23, 2025 20:53
1 min read
Simon Willison

Analysis

This article introduces MicroQuickJS, a new Javascript engine by Fabrice Bellard, known for his work on ffmpeg, QEMU, and QuickJS. Designed for embedded systems, it boasts a small footprint, requiring only 10kB of RAM and 100kB of ROM. Despite supporting a subset of JavaScript, it appears to be feature-rich. The author explores its potential for sandboxing untrusted code, particularly code generated by LLMs, focusing on restricting memory usage, time limits, and access to files or networks. The author initiated an asynchronous research project using Claude Code to investigate this possibility, highlighting the engine's potential in secure code execution environments.
Reference

“MicroQuickJS (aka. MQuickJS) is a Javascript engine targetted at embedded systems. It compiles and runs Javascript programs with as low as 10 kB of RAM. The whole engine requires about 100 kB of ROM (ARM Thumb-2 code) including the C library. The speed is comparable to QuickJS.”

PermalinkSimon Willison
Research#Neuroscience📝 BlogAnalyzed: Dec 29, 2025 17:37

Karl Friston: Neuroscience and the Free Energy Principle

Published:May 28, 2020 12:42
1 min read
Lex Fridman Podcast

Analysis

This article summarizes a podcast episode featuring Karl Friston, a prominent neuroscientist known for his work on brain imaging and the free energy principle. The episode, part of the Artificial Intelligence podcast, delves into Friston's influential ideas, including his free energy principle for action and perception. The article provides links to the podcast, Friston's website, and his Wikipedia page. It also includes a detailed outline of the episode's topics, ranging from brain imaging and Neuralink to the meaning of life. The focus is on making complex scientific concepts accessible to a broader audience.
Reference

“Karl Friston is one of the greatest neuroscientists in history, cited over 245,000 times, known for many influential ideas in brain imaging, neuroscience, and theoretical neurobiology, including the fascinating idea of the free-energy principle for action and perception.”

PermalinkLex Fridman Podcast
Philosophy#Artificial Intelligence📝 BlogAnalyzed: Dec 29, 2025 17:39

Nick Bostrom: Simulation and Superintelligence

Published:Mar 26, 2020 00:19
1 min read
Lex Fridman Podcast

Analysis

This podcast episode features Nick Bostrom, a prominent philosopher known for his work on existential risks, the simulation hypothesis, and the dangers of superintelligent AI. The episode, part of the Artificial Intelligence podcast, covers Bostrom's key ideas, including the simulation argument. The provided outline suggests a discussion of the simulation hypothesis and related concepts. The episode aims to explore complex topics in AI and philosophy, offering insights into potential future risks and ethical considerations. The inclusion of links to Bostrom's website, Twitter, and other resources provides listeners with avenues for further exploration of the subject matter.
Reference

“Nick Bostrom is a philosopher at University of Oxford and the director of the Future of Humanity Institute. He has worked on fascinating and important ideas in existential risks, simulation hypothesis, human enhancement ethics, and the risks of superintelligent AI systems, including in his book Superintelligence.”

PermalinkLex Fridman Podcast
Podcast#Artificial Intelligence📝 BlogAnalyzed: Dec 29, 2025 17:42

Daniel Kahneman on Thinking, Fast and Slow, Deep Learning, and AI

Published:Jan 14, 2020 18:04
1 min read
Lex Fridman Podcast

Analysis

This article summarizes a podcast episode featuring Daniel Kahneman, a Nobel laureate known for his work on behavioral economics and cognitive biases. The core of the discussion revolves around Kahneman's "Thinking, Fast and Slow" framework, which distinguishes between intuitive (System 1) and deliberative (System 2) thinking. The podcast also touches upon deep learning and the challenges of autonomous driving, indicating a broader exploration of AI-related topics. The episode is presented by Lex Fridman and includes timestamps for different segments, along with promotional information for the podcast and its sponsors.
Reference

“The central thesis of this work is a dichotomy between two modes of thought: “System 1” is fast, instinctive and emotional; “System 2” is slower, more deliberative, and more logical.”

PermalinkLex Fridman Podcast
Research#deep learning📝 BlogAnalyzed: Dec 29, 2025 17:45

Yann LeCun on Deep Learning, CNNs, and Self-Supervised Learning

Published:Aug 31, 2019 15:43
1 min read
Lex Fridman Podcast

Analysis

This article summarizes a podcast conversation with Yann LeCun, a prominent figure in the field of deep learning. It highlights his contributions, including the development of convolutional neural networks (CNNs) and his work on self-supervised learning. The article emphasizes LeCun's role as a pioneer in AI, mentioning his Turing Award and his positions at NYU and Facebook. It also provides information on how to access the podcast and support it. The focus is on LeCun's expertise and the importance of his work in the advancement of AI.

Key Takeaways

Reference

“N/A (Podcast summary, no direct quote)”

PermalinkLex Fridman Podcast