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The Anthropic Economic Index
To buy a Tesla Model 3, only to end up in hell
Surnames from nicknames nobody has any more
Surnames from nicknames nobody has any more
Undergraduate shows that searches within hash tables can be much faster
Undergraduate shows that searches within hash tables can be much faster
Is software abstraction killing civilization? (2021)
21st Century C++
LIMO: Less Is More for Reasoning
Don't "optimize" conditional moves in shaders with mix()+step()
Don't "optimize" conditional moves in shaders with mix()+step()
Why blog if nobody reads it?
Why blog if nobody reads it?
Modern-Day Oracles or Bullshit Machines? How to thrive in a ChatGPT world
Jevin West and I are professors of data science and biology, respectively, at the University of Washington. After talking to literally hundreds of educators, employers, researchers, and policymakers, we have spent the last eight months developing the course on large language models (LLMs) that we think every college freshman needs to take.<p><a href="https://thebullshitmachines.com" rel="nofollow">https://thebullshitmachines.com</a><p>This is not a computer science course; it’s a humanities course about how to learn and work and thrive in an AI world. Neither instructor nor students need a technical background. Our instructor guide provides a choice of activities for each lesson that will easily fill an hour-long class.<p>The entire course is available freely online. Our 18 online lessons each take 5-10 minutes; each illuminates one core principle. They are suitable for self-study, but have been tailored for teaching in a flipped classroom.<p>The course is a sequel of sorts to our course (and book) Calling Bullshit. We hope that like its predecessor, it will be widely adopted worldwide.<p>Large language models are both powerful tools, and mindless—even dangerous—bullshit machines. We want students to explore how to resolve this dialectic. Our viewpoint is cautious, but not deflationary. We marvel at what LLMs can do and how amazing they can seem at times—but we also recognize the huge potential for abuse, we chafe at the excessive hype around their capabilities, and we worry about how they will change society. We don't think lecturing at students about right and wrong works nearly as well as letting students explore these issues for themselves, and the design of our course reflects this.
Modern-Day Oracles or Bullshit Machines? How to thrive in a ChatGPT world
Jevin West and I are professors of data science and biology, respectively, at the University of Washington. After talking to literally hundreds of educators, employers, researchers, and policymakers, we have spent the last eight months developing the course on large language models (LLMs) that we think every college freshman needs to take.<p><a href="https://thebullshitmachines.com" rel="nofollow">https://thebullshitmachines.com</a><p>This is not a computer science course; it’s a humanities course about how to learn and work and thrive in an AI world. Neither instructor nor students need a technical background. Our instructor guide provides a choice of activities for each lesson that will easily fill an hour-long class.<p>The entire course is available freely online. Our 18 online lessons each take 5-10 minutes; each illuminates one core principle. They are suitable for self-study, but have been tailored for teaching in a flipped classroom.<p>The course is a sequel of sorts to our course (and book) Calling Bullshit. We hope that like its predecessor, it will be widely adopted worldwide.<p>Large language models are both powerful tools, and mindless—even dangerous—bullshit machines. We want students to explore how to resolve this dialectic. Our viewpoint is cautious, but not deflationary. We marvel at what LLMs can do and how amazing they can seem at times—but we also recognize the huge potential for abuse, we chafe at the excessive hype around their capabilities, and we worry about how they will change society. We don't think lecturing at students about right and wrong works nearly as well as letting students explore these issues for themselves, and the design of our course reflects this.
Teen on Musk's DOGE team graduated from 'The Com'
Teen on Musk's DOGE team graduated from 'The Com'
Tips for mathematical handwriting (2007)
Are LLMs able to notice the “gorilla in the data”?
Jacksonpollock.org (2003)