Co-founder of Y Combinator and Viaweb; essayist at paulgraham.com.

• Likedrcmnd.app

  The Moon is a Harsh Mistress

  Their words

  AI was in the air in the mid 1980s, but there were two things especially that made me want to work on it: a novel by Heinlein called The Moon is a Harsh Mistress

  paulgraham.com

Founder and CEO of Get Lighthouse, a management-coaching software company, and previously a product lead at KISSmetrics. Writes about leadership, management and product at jasonevanish.com.

• Likedaffiliate linkrcmnd.app

  Work Rules!: Insights from Inside Google

  Their words

  If you're curious how Google built it's culture and the processes thanks to their extremely data & engineering driven nature, this is a great book. What held it back was being ~100 pages too long and Bock didn't always understand where what they did only fit at a $100Bn+, mega-profitable company. Still, the insights on the studies on their 50,000+ employees is well worth the read since so few of us can get similar statistical significance to apply to our teams.

  jasonevanish.com

• Likedaffiliate linkrcmnd.app

  Mastering the VC Game

  Their words

  The interests of a Venture Capitalist are different than those of the entrepreneurs building a company they've invested in. Jeff does an awesome job of helping explain how you can get misaligned in your goals versus your investors. Fortunately, he also covers how to avoid it.

  jasonevanish.com

American senior staff engineer working on developer and user experience and open source; writes at adamdehaven.com.

• Usesrcmnd.app

  Google Keep

  Their words

  Google Keep - I use this primarily as a shared shopping list and "wish list," and for saving web links and lists I want to add to/come back to later.

  adamdehaven.com

Software engineer and writer; former CTO of Wave, now at Anthropic. Blogs at benkuhn.net on attention, engineering management and doing hard things well.

• Usesrcmnd.app

  nativefier

  Their words

  For the rest (e.g., oddly, most Google web apps), I use a command-line tool called nativefier to turn them into desktop apps.

  benkuhn.net

Mathematician and maker of the 3Blue1Brown YouTube channel, which explains mathematics through animation. Creator of the open-source Manim animation library and founder of the Summer of Math Exposition.

• Recommendsrcmnd.app

  Welch Labs

  Their words

  this channel is full of high production quality and well-written videos. There are also several series on machine learning, the topics underlying self-driving cars, so this is certainly one of the more applied math channels out there.

  3blue1brown.com

Co-founder and CEO of Anthropic; previously VP of research at OpenAI.

• Our readingkorrents.com

  Scaling up language models greatly improves task-agnostic few-shot performance, sometimes matching prior fine-tuning approaches.

  Their words

  Here we show that scaling up language models greatly improves task-agnostic, few-shot performance, sometimes even reaching competitiveness with prior state-of-the-art fine-tuning approaches.

  arxiv.org

Writer and novelist. Publishes essays and book notes at nateliason.com; author of the novel Husk and of Crypto Confidential.

• Lovedrcmnd.app

  Gödel Escher Bach

  Their words

  This book stretched my mind more than almost any other book I’ve read. It’s tough at parts, it’s long, but you’ll come out of it thinking about brains, minds, intelligence, and AI in an entirely new way.

  nateliason.com

Medicinal chemist; has written In the Pipeline, the drug-discovery blog, since 2002, and the “Things I Won’t Work With” posts about chemicals that try to kill you.

• Our readingkorrents.com

  A paper reporting an AI-generated molecule must publish the model's entire training set in detail, or the result cannot be judged.

  Their words

  As generative drug analoging grows in importance, it's going to be crucial for people to make the entire training set available in detail when such work is published.

  Arguing on AI Drug Discoveryweb.archive.org

British senior engineering manager at Netlify, previously a team lead at the BBC; writes about JavaScript testing, chatbots and serverless at marclittlemore.com.

• Usesrcmnd.app

  Chrome

  Their words

  My browser of choice is Chrome, mainly because I use Google's tools (Gmail, Docs, Sheets, and so on) on a daily basis.

  marclittlemore.com

Writer and developer; runs Waxy.org, co-organises the XOXO festival, and was the first CTO of Kickstarter.

• Usesrcmnd.app

  Google Colab

  Their words

  spending an increasing amount of my free time working with tools like Google Colab, Runway ML, TensorFlow, and Hugging Face to play around with machine-generated text, audio, imagery, and video.

  usesthis.com

Creator of the Keras deep-learning library and the ARC-AGI benchmark.

• Our readingkorrents.com

  The Abstraction and Reasoning Corpus can measure human-like general fluid intelligence and enable fair comparisons between AI systems and humans.

  Their words

  We argue that ARC can be used to measure a human-like form of general fluid intelligence and that it enables fair general intelligence comparisons between AI systems and humans.

  On the Measure of Intelligencearxiv.org

Writer and education-technology critic; published Hack Education for a decade and wrote Teaching Machines.

• Dislikedrcmnd.app

  Microsoft Word

  Their words

  When I'm writing articles etc that need to be shared with an editor, I typically write in Microsoft Word. I hate all word processing software, and anyone who insists that Google Docs is so much better than Word is a liar.

  usesthis.com

Theoretical computer scientist, Schlumberger Centennial Chair of Computer Science at the University of Texas at Austin and director of its Quantum Information Center. Writes the blog Shtetl-Optimized.

• Lovedrcmnd.app

  The AI Does Not Hate You: Superintelligence, Rationality, and the Race to Save the World

  Their words

  Briefly, I think the book is a triumph.

  scottaaronson.blog

Mathematical biologist; Senior Lecturer in the Department of Mathematical Sciences at the University of Bath and author of The Maths of Life and Death and How to Expect the Unexpected.

• Recommendsrcmnd.app

  The Creativity Code: Art and Innovation in the Age of AI

  Their words

  It's increasingly coming to the fore and Marcus deals with it in a really interesting way. He takes us through lots of different areas where AI is being used to mimic creativity, which some people would argue is the essence of being human. It's interesting to see how close to being human AI is getting.

  fivebooks.com

Writer and programmer; co-founder of the software studio Postlight and author of the Bloomberg Businessweek essay What Is Code?

• Lovedrcmnd.app

  Google Meet speakermic

  Their words

  so we use Google Meet speakermics, which allow for full-duplex conversations, which makes conversation far more organic. That device turned Google Meet from something exhausting to something really good.

  usesthis.com

• Usesrcmnd.app

  Google Pixel 3

  Their words

  My phone is a maxed-out Google Pixel 3, which I use for phone things: Email, reading, web browsing, messaging, music, and taking pictures

  usesthis.com

Professor of cognitive science at UC San Diego working on human-computer interaction and programming tools; creator of Python Tutor, the online code visualizer.

• Likedrcmnd.app

  PDF Expert

  Their words

  In terms of iOS apps, I use PDF Expert, which is a great PDF reader and annotator (using Apple Pencil), Notability as a virtual whiteboard (again with Apple Pencil), Google Docs for document editing, Google Calendar, and Gmail.

  usesthis.com

Co-founder, chairman and chief investment officer of Ritholtz Wealth Management. Hosts the Masters in Business podcast for Bloomberg and wrote How NOT to Invest.

• Recommendsaffiliate linkrcmnd.app

  Trillion Dollar Coach: The Leadership Playbook of Silicon Valley's Bill Campbell

  Their words

  Eric Schmidt, Jonathan Rosenberg and Alan Eagle, Trillion Dollar Coach: The Leadership Playbook of Silicon Valley’s Bill Campbell: I understood Bill Campbell was a behind-the-scenes guy in Silicon Valley, but I had no idea just how influential he was. Bill Gurley of Benchmark noted “I would argue that Bill has had a bigger impact on Silicon Valley than any other single person simply because his reach was so amazingly wide.” That’s a story I want to read.

  ritholtz.com

Independent game developer, creator of the colony simulation RimWorld and author of Designing Games: A Guide to Engineering Experiences. Previously worked on BioShock Infinite.

• Usesrcmnd.app

  Visual Studio Code

  Their words

  For coding, I use Visual Studio Code. I use Git for source control, Photoshop for 2D art, Audition for audio editing, Premiere for video editing, and our team coordinates on Google Docs and Skype.

  usesthis.com

Musician and writer; answers readers' questions weekly at The Red Hand Files, and fronts Nick Cave and the Bad Seeds.

• Our readingkorrents.com

  What moves a listener is not the song alone but a human being straining against their own limits, which is why a machine can write a good song and never a great one.

  Their words

  What we are actually listening to is human limitation and the audacity to transcend it. Artificial Intelligence, for all its unlimited potential, simply doesn’t have this capacity.

  theredhandfiles.com

Financial journalist; chief financial correspondent at Axios and host of the Slate Money podcast, previously a blogger at Reuters and author of The Phoenix Economy.

• Likedrcmnd.app

  Google Docs

  Their words

  Now, almost everything happens in Google Docs, except for when I write straight into the Axios or Substack CMS. (Both of which are lovely, WYSIWYG, very simple and easy to use.)

  usesthis.com

One of the four authors of the 2018 paper "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding", at Google AI Language, the affiliation printed on the paper.

From one piece BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 2 beliefs, in the piece's order there

• Our readingkorrents.com

  Unidirectional restrictions are sub-optimal for sentence-level tasks and harmful for token-level tasks that need bidirectional context.

  Their words

  Such restrictions are sub-optimal for sentence-level tasks, and could be very harmful when applying fine-tuning based approaches to token-level tasks such as question answering, where it is crucial to incorporate context from both directions.

  arxiv.org

• Our readingkorrents.com

  Current techniques restrict pre-trained representation power because standard language models are unidirectional.

  Their words

  We argue that current techniques restrict the power of the pre-trained representations, especially for the fine-tuning approaches. The major limitation is that standard language models are unidirectional, and this limits the choice of architectures that can be used during pre-training.

  arxiv.org

One of the four authors of the 2018 paper "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding", at Google AI Language, the affiliation printed on the paper.

From one piece BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 2 beliefs, in the piece's order there

• Our readingkorrents.com

  Current techniques restrict pre-trained representation power because standard language models are unidirectional.

  Their words

  We argue that current techniques restrict the power of the pre-trained representations, especially for the fine-tuning approaches. The major limitation is that standard language models are unidirectional, and this limits the choice of architectures that can be used during pre-training.

  arxiv.org

• Our readingkorrents.com

  Unidirectional restrictions are sub-optimal for sentence-level tasks and harmful for token-level tasks that need bidirectional context.

  Their words

  Such restrictions are sub-optimal for sentence-level tasks, and could be very harmful when applying fine-tuning based approaches to token-level tasks such as question answering, where it is crucial to incorporate context from both directions.

  arxiv.org

One of the four authors of the 2018 paper "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding", at Google AI Language, the affiliation printed on the paper.

From one piece BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 2 beliefs, in the piece's order there

• Our readingkorrents.com

  Unidirectional restrictions are sub-optimal for sentence-level tasks and harmful for token-level tasks that need bidirectional context.

  Their words

  Such restrictions are sub-optimal for sentence-level tasks, and could be very harmful when applying fine-tuning based approaches to token-level tasks such as question answering, where it is crucial to incorporate context from both directions.

  arxiv.org

• Our readingkorrents.com

  Current techniques restrict pre-trained representation power because standard language models are unidirectional.

  Their words

  We argue that current techniques restrict the power of the pre-trained representations, especially for the fine-tuning approaches. The major limitation is that standard language models are unidirectional, and this limits the choice of architectures that can be used during pre-training.

  arxiv.org

One of the four authors of the 2018 paper "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding", at Google AI Language, the affiliation printed on the paper.

From one piece BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 2 beliefs, in the piece's order there

• Our readingkorrents.com

  Current techniques restrict pre-trained representation power because standard language models are unidirectional.

  Their words

  We argue that current techniques restrict the power of the pre-trained representations, especially for the fine-tuning approaches. The major limitation is that standard language models are unidirectional, and this limits the choice of architectures that can be used during pre-training.

  arxiv.org

• Our readingkorrents.com

  Unidirectional restrictions are sub-optimal for sentence-level tasks and harmful for token-level tasks that need bidirectional context.

  Their words

  Such restrictions are sub-optimal for sentence-level tasks, and could be very harmful when applying fine-tuning based approaches to token-level tasks such as question answering, where it is crucial to incorporate context from both directions.

  arxiv.org

Statistician and Chief Scientist at Posit (RStudio). Author of the ggplot2, dplyr and tidyverse R packages and of books on R programming and data science.

• Recommendsrcmnd.app

  The Algorithm Design Manual

  Their words

  To me, this book is an illustration of the power of names. Today, in the era of Google, if you know the name of something, you can find out about it with a simple search. But if you don't know of what you're looking for, it suddenly becomes much harder to find it. Having in the back of your head the names of common algorithms that help you solve problems is really powerful.

  fivebooks.com

London-based front-end architect, web developer evangelist and cloud consultant; Microsoft MVP. Writes at praveen.science and answers on Stack Overflow.

• Usesrcmnd.app

  Google Chrome

  Their words

  Google Chrome: What's a Web Developer without Google Chrome browser? The first thing I do with Safari is to get Google Chrome and install the latest version.

  blog.praveen.science

Associate Professor at MIT CSAIL, leading the Programming Systems Group; works on programming systems that manipulate uncertainty, from neural networks to unreliable hardware.

• Our readingkorrents.com

  Pruning cuts the parameters of a trained network by over 90% without costing accuracy, so inference gets smaller and faster for free.

  Their words

  Neural network pruning techniques can reduce the parameter counts of trained networks by over 90%, decreasing storage requirements and improving computational performance of inference without compromising accuracy.

  arxiv.org

Chief AI Scientist at Databricks, after its acquisition of MosaicML, where he was a founding team member; known for the Lottery Ticket Hypothesis from his MIT PhD (ICLR 2019 Best Paper).

• Our readingkorrents.com

  Pruning cuts the parameters of a trained network by over 90% without costing accuracy, so inference gets smaller and faster for free.

  Their words

  Neural network pruning techniques can reduce the parameter counts of trained networks by over 90%, decreasing storage requirements and improving computational performance of inference without compromising accuracy.

  arxiv.org

Alignment researcher; developed reinforcement learning from human feedback at OpenAI, founded the Alignment Research Center, and now works at the US AI Safety Institute.

From one piece Takeoff speeds 4 beliefs, in the piece's order there

• Our readingkorrents.com

  A slow takeoff is significantly more likely than a fast one: AI that is nearly as powerful will have transformed the world before the incredibly powerful kind arrives.

  Their words

  I currently think a slow takeoff is significantly more likely.

  Takeoff speedssideways-view.com

• Our readingkorrents.com

  Technologies are almost always preceded by slightly worse versions of themselves, and there is no reason for AI to be the exception.

  Their words

  Things are usually preceded by worse versions, even in cases where there are weak reasons to expect a discontinuous jump.

  Takeoff speedssideways-view.com

• Our readingkorrents.com

  Incredibly powerful AI will arrive into a world that is already being transformed and already alarmed, not into a world like today's.

  Their words

  In particular, this means that incredibly powerful AI will emerge in a world where crazy stuff is already happening (and probably everyone is already freaking out).

  Takeoff speedssideways-view.com

Philosopher and historian of existential risk; wrote Human Extinction, and coined "TESCREAL" with Timnit Gebru for the cluster of ideologies they argue underpins the AI industry.

From one piece Why superintelligence is a threat that should be taken seriously 2 beliefs, in the piece's order there

• Our readingkorrents.com

  Never project human mental properties onto an artificial intelligence; the difference between the two architectures is the reason to worry, not a reason not to.

  AI alignment

  Their words

  One of the most commonly emphasized points in the AI safety literature is that one must never anthropomorphize AI—that is, don’t project human mental properties onto artificially intelligent systems.

  thebulletin.org

• Our readingkorrents.com

  A superintelligence needs no consciousness, emotions or malice to be dangerous; a goal system slightly misaligned with ours is enough.

  AI alignment

  Their words

  A superintelligence whose goal system is even slightly misaligned with ours could, being far more powerful than any human or human institution, bring about human extinction for the very same reason that construction workers routinely slaughter large populations of ants.

  thebulletin.org

Game designer and programmer, co-founder of id Software and co-creator of Doom, Quake and Wolfenstein 3D. Now runs Romero Games in Galway, Ireland.

• Usesrcmnd.app

  REAPER

  Their words

  I use a ton of software. Here's a list: Xcode, Pages, Numbers, Keynote, Sublime Text, Corona SDK, Unity, Final Cut Pro, Versions, Perforce, VMWare Fusion, Messages, REAPER, Transmit, Coda, Dropbox, Skype, Dashlane, Slack, Terminal, Assembla, Airmail, Spark Mail, Google Docs, Pixelmator, Pixen, TexturePacker, Particle Designer, Tiled, iTunes + Music + Match, Screenium, Steam, Twitter, Facebook.

  usesthis.com

• Usesrcmnd.app

  Unity

  Their words

  I use a ton of software. Here's a list: Xcode, Pages, Numbers, Keynote, Sublime Text, Corona SDK, Unity, Final Cut Pro, Versions, Perforce, VMWare Fusion, Messages, REAPER, Transmit, Coda, Dropbox, Skype, Dashlane, Slack, Terminal, Assembla, Airmail, Spark Mail, Google Docs, Pixelmator, Pixen, TexturePacker, Particle Designer, Tiled, iTunes + Music + Match, Screenium, Steam, Twitter, Facebook.

  usesthis.com

Chief Scientist at Google DeepMind and Google Research, at Google since 1999, where he co-created MapReduce, Bigtable, TensorFlow and the TPU.

• Usesrcmnd.app

  emacs

  Their words

  For writing code, I use emacs and Google's internal distributed build system (a version of which was open sourced as Bazel) and our version control system

  usesthis.com

• Usesrcmnd.app

  LaTeX

  Their words

  For technical papers, I and my coauthors usually use LaTeX. For giving presentations, I almost exclusively use Google Slides.

  usesthis.com

• Usestheir ownrcmnd.app

  Google Slides

  Their words

  For giving presentations, I almost exclusively use Google Slides.

  usesthis.com

Founder and chief executive of Replit. Previously an engineer at Facebook and Codecademy. Writes essays on programming, philosophy and entrepreneurship at amasad.me.

• Recommendsrcmnd.app

  Rationality: From AI to Zombies

  Their words

  luckily I was aided by a few books that I recommend to anyone who wants to come to terms with this

  amasad.me

Programmer and writer on computer architecture, performance, and software reliability. He has worked on CPU design at Centaur Technology and on software at Google and Microsoft, and writes long-form technical essays at danluu.com.

• Mixed onaffiliate linkrcmnd.app

  Site Reliability Engineering

  Their words

  A description of how Google handles operations.

  danluu.com

Associate Professor at MIT EECS and Distinguished Scientist at Google DeepMind; first author of the Deep Residual Learning (ResNet) paper, among the most-cited papers of the century.

• Our readingkorrents.com

  Depth is not free: past a point, deeper neural networks are harder to train rather than simply better.

  Their words

  Deeper neural networks are more difficult to train.

  arxiv.org

Computer vision researcher and former Chief Scientist of Megvii, previously at Microsoft Research Asia; co-author of ResNet and Faster R-CNN. Died in 2022; this page reflects his complete public record.

• Our readingkorrents.com

  Depth is not free: past a point, deeper neural networks are harder to train rather than simply better.

  Their words

  Deeper neural networks are more difficult to train.

  arxiv.org

Interpretability researcher at Anthropic, which he co-founded; before that at OpenAI and Google Brain, where he wrote the explanations of neural networks most people learned them from.

• Our readingkorrents.com

  Standard recurrent neural networks are theoretically capable of representing long-term dependencies but fail to learn them from data in practice.

  Their words

  In theory, RNNs are absolutely capable of handling such "long-term dependencies." A human could carefully pick parameters for them to solve toy problems of this form. Sadly, in practice, RNNs don't seem to be able to learn them.

  Understanding LSTM Networkscolah.github.io