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Hey everyone, I just wanted to chime in and say that GPT-J is incredibly legit. Every aspect of GPT-J is production grade — no difference in process, quality, o

Hey everyone, I just wanted to chime in and say that GPT-J is incredibly legit. Every aspect of GPT-J is production grade — no difference in process, quality, or results, compared to any other big name research lab. I also want to apologize to Eleuther for giving them a hard time in the past. My earlier concerns were unjustified. To be completely honest, I was jealous they achieved everything I tried to achieve with my own open source research lab attempt. It took a long time to even recognize that jealousy in myself, let alone set it aside. Sorry. The credit for this work goes almost entirely to kindiana, aka Ben Wang. Remember that name; you’ll be seeing a lot of it in the coming decade. It’s clear to me that whichever lab he ends up at (he’s an undergrad! Google let him slip away because he didn’t have a degree!), he’s gonna be changing the world. Don’t know what, don’t know how, know he will. Every aspect of that codebase is immaculate. Most research code is not pretty; this looks carved out of marble and placed in a museum. Without Eleuther’s TPU resources, this work wouldn’t have happened. Tensorfork (my lab) didn’t get access to the TPU VM alpha. And TPU VMs were an absolute necessity here. (TPU VMs are a new thing; they’ve been in alpha since December, but only recently launched. If curious see https://github.com/shawwn/website/blob/master/jaxtpu.md https://github.com/shawwn/website/blob/master/jaxtpu.md and https://github.com/shawwn/website/blob/master/mlmind.md https://github.com/shawwn/website/blob/master/mlmind.md for why it’s the future of ML.) Eleuther also helped test the model thoroughly. Leo Gao (go follow him: https://twitter.com/nabla_theta?s=21 https://twitter.com/nabla_theta?s=21) ran GPT-J through the gauntlet. He was the primary person behind The Pile, the training data that makes any of this possible. I can say with absolute certainty and no hesitation that there are no “gotchas” here. Eleuther’s https://6b.eleuther.ai https://6b.eleuther.ai page looks wonderful too. It’s like a free OpenAI API playground that everyone can try. Keeping it running for months is no small achievement. (Set top_p to 1.0 and temp to 0.8; the defaults are pretty bad.) Congratulations, and thank you everyone for all your hard work. The world is so much better for having access to this level of quality.

GraffitiTim 5y ago
This was a very nice thing to say.
- sillysaurusx 5y ago
  They super earned it. From day one, everyone showed up with a level of drive and determination I haven't seen elsewhere. My name is on The Pile paper https://arxiv.org/abs/2101.00027 https://arxiv.org/abs/2101.00027 but I didn't do anything except make the books3 dataset. Stella, Leo, and everyone else did the hard work. You know, the work that's "actually useful to the scientific community." I didn't even help them hunt for typos, even though Stella asked me to. I was just like, sorry, no time, I have to focus on my own research. Imagine saying "nah" to helping shape one of the most important open source AI research projects of the coming years. Training data quality is becoming more and more of a focus. Lemme tell you a quick story. When https://venturebeat.com/2021/06/09/eleutherai-claims-new-nlp-model-approaches-gpt-3-level-performance/ https://venturebeat.com/2021/06/09/eleutherai-claims-new-nlp... come out, this quote caught my eye: > But EleutherAI claims to have performed “extensive bias analysis” on The Pile and made “tough editorial decisions” to exclude datasets they felt were “unacceptably negatively biased” toward certain groups or views. When I read this, I felt astonished that Eleuther was yet again trying to pose as the cool super-progressive AI lab. To my knowledge, no such thing ever happened. And I was involved with The Pile back when it was just me and Leo memeing in Discord DMs about how the world needed some quality training data once and for all. I went to Stella in DMs (you should follow her too! https://twitter.com/BlancheMinerva/status/1394089508723900422 https://twitter.com/BlancheMinerva/status/139408950872390042...) and was like, what the hell? I don't understand how this could possibly be true. What are these supposed "tough editorial decisions"? Stella calmly explained to me that the US Congressional Record had been considered and rejected for inclusion in The Pile. I thought "Big deal, who the hell cares?" while saying "Okay, but I don't know what that is." It’s a written record of all statements made in the US legislature. It was also somewhere between 1GB and 15GB, which would have been a significant portion of The Pile's total size. I'm going to quote from her private DMs with me, which I haven't asked for permission to do. So this is technically another bad move by me. But she put it so perfectly, I was stunned: > For half the history of the US, black people were slaves. For something like 75% of it, black people didn’t have the right to vote. A modern reader didn’t think there wasn’t a high proportion of extremely racist content, that would primarily be an inditement of modern people lol. > The reason we first looked at it was that we included a similar document for the EU Parlement It took me a few minutes to come to my senses, but I finally realized: (a) this dataset likely contained a huge proportion of content that, politics aside, would be a Very Bad Idea to include in your ML models by default; (b) Eleuther had just been trying to do good work this whole time So you know, when you're in that situation, you can choose to either keep believing your own false ideas, or you can pay attention to empirical evidence and change your behavior. And empirically, I had been a massive asshole to everyone since pretty much the beginning. The only thing I helped with was books3 and arranging The Eye to get them some reliable hosting. (Shoutout to The Eye, by the way. Help 'em out if you can: https://the-eye.eu/public/AI/ https://the-eye.eu/public/AI/) And there's my name, right there on the paper. It's even worse than I described. I put the paper in jeopardy, because they were submitting it to a conference with strict anonymity rules. I had no idea about it (no one told me). I ended up so happy to see my name on a real arxiv paper that I tweeted out some self-congratulatory bullshit, and quote-tweeted something linking to The Pile. It was a few days into the anonymity period, but nonetheless, it was a violation of the anonymity rules. A lot of people saw that tweet, and the whole point of the rules is to ensure that people don't get unfair advantages by advertising on social media. When they came to me in DMs apologizing profusely for not talking with me about it, and asking me to delete the tweet, I basically told them to go shove a spoon up their.... because I didn't agree to any rules, and the idea that The Pile should go radio silent for five months on social media struck me as completely crazy. In hindsight, I was... just awful. So I mean, me posting this is like, the absolute minimum I can do. They've been the ones working for like a year to make all of this happen. Ended up feeling like a fraud, since everyone thinks highly of my ML work, and here I'd been nothing but problematic for a group of people who are just trying to ship good scientific work. Fast forward to today, and the results are clear. Go help Eleuther: https://www.eleuther.ai/ https://www.eleuther.ai/ They're cool, and you'll get a shot at changing the world. I'm not sure you even have to be particularly skilled; some of the most valuable work was done by people who just showed up and started doing things, e.g. making the website look a little nicer, or making a cool logo.
reed1234 5y ago
It takes a lot to be able to find something in yourself like that and admit it to yourself and everyone. I always appreciate people like that. I also tried the playground and was impressed that it was free! It must be a sizable chunk of money to run that.
- sillysaurusx 5y ago
  Believe it or not, it's completely free. It's thanks to TFRC. It's the most world-changing program I know of. It's why I go door to door like the proverbial religious fanatic, singing TFRC's praises, whether people want to listen or not. Because for the first time in history, any capable ML hacker now has the resources they need to do something like this. Imagine it. This is a legit OpenAI-style model inference API. It's now survived two HN front page floods. (I saw it go down about an hour ago, so I was like "Nooo! Prove you're production grade! I believe in you!" and I think my anime-style energy must've brought it back up, since the API works fine now. Yep, it was all me. Keyboard goes clackclackclack, world changes, what can I say? Just another day at the ML office oh god this joke has gone on for like centuries too long.) And it's all thanks to TFRC. I'm intentionally not linking anything about TFRC, because in typical google fashion, every single thing you can find online is the most corporate, soulless-looking "We try to help you do research at scale" generic boilerplate imaginable. So I decided to write something about TFRC that wasn't: https://blog.gpt4.org/jaxtpu https://blog.gpt4.org/jaxtpu (It was pretty hard to write a medieval fantasy-style TPU fanfic, but someone had to. Well, maybe no one had to. But I just couldn't let such a wonderful project go unnoticed, so I had to try as much stupid shit as possible to get the entire world to notice how goddamn cool it is.) To put things into perspective, a TPU v2-8 is the "worst possible TPU you could get access to." They give you access to 100. On day one. This is what originally hooked me in. My face, that first day in 2019 when TFRC's email showed up saying "You can use 100 v2-8's in us-central1-f!": https://i.imgur.com/EznLvlb.png https://i.imgur.com/EznLvlb.png The idea of using 100 theoretically high-performance nodes of anything, in creative ways, greatly appealed to my gamedev background. It wasn't till later that I discovered, to my delight, that these weren't "nodes of anything." These are 96 CPU, 330GB RAM, Ubuntu servers. That blog post I just linked to is running off of a TPU right now. Because it's literally just an ubuntu server. This is like the world's best kept secret. It's so fucking incredible that I have no idea why people aren't beating down the doors, using every TPU that they can get their hands on, for as many harebrained ideas as possible. God, I can't even list how much cool shit there is to discover. You'll find out that you get 100Gbit/s between two separate TPUs. In fact, I'm pretty sure it's even higher than this. That means you don't even need a TPU pod anymore. At least, theoretically. I tried getting Tensorflow to do this, for over a year. kindiana (Ben Wang), the guy who wrote this GPT-J codebase we're all talking about, casually proved that this was not merely theoretical: https://twitter.com/theshawwn/status/1406171487988498433 https://twitter.com/theshawwn/status/1406171487988498433 He tried to show me https://github.com/kingoflolz/swarm-jax/ https://github.com/kingoflolz/swarm-jax/ once, long ago. I didn't understand at the time what I was looking at, or why it was such a big deal. But basically, when you put each GPT layer on a separate TPU, it means you can string together as many TPUs as you want, to make however large of a model you want. You should be immediately skeptical of that claim. It shouldn't be obvious that the bandwidth is high enough to train a GPT-3 sized model in any reasonable time frame. It's still not obvious to me. But at this point, I've been amazed by so many things related to TPUs, JAX, and TFRC, that I feel like I'm dancing around in willy wonka's factory while the door's wide open. The oompa loompas are singing about "that's just what the world will do, oompa-loompa they'll ignore you" while I keep trying to get everybody to stop what they're doing and step into the factory. The more people using TPUs, the more google is going to build TPUs. They can fill three small countries entirely with buildings devoted to TPUs. The more people want these things, the more we'll all have. Because I think Google's gonna utterly annihilate Facebook in ML mindshare wars: https://blog.gpt4.org/mlmind https://blog.gpt4.org/mlmind TPU VMs just launched a month ago. No one realizes yet that JAX is the React of ML. Facebook left themselves wide open by betting on GPUs. GPUs fucking suck at large-scale ML training. Why the hell would you pay $1M when you can get the same thing for orders of magnitude less? And no one's noticed that TPUs don't suck anymore. Forget everything you've ever heard about them. JAX on TPU VMs changes everything. In five years, you'll all look like you've been writing websites in assembly. But hey, I'm just a fanatic TPU zealot. It's better to just write me off and keep betting on that reliable GPU pipeline. After all, everyone has millions of VC dollars to pour into the cloud furnace, right? TFRC changed my life. I tried to do some "research" https://www.docdroid.net/faDq8Bu/swarm-training-v01a-pdf https://www.docdroid.net/faDq8Bu/swarm-training-v01a-pdf back when Tensorflow's horrible problems were your only option on TPUs. Nowadays, you can think of JAX as "approximately every single thing you could possibly hope for." GPT-J is proof. What more can I say? No TFRC, no GPT-J. The world is nuts for not noticing how impactful TFRC has been. Especially TFRC support. Jonathan from the support team is just ... such a wonderful person. I was blown away at how much he cares about taking care of new TFRC members. They all do. (He was only ever late answering my emails one time. And it was because he was on vacation!) If you happen to be an ambitious low-level hacker, I tried to make it easier for you to get your feet wet with JAX: 1. Head to https://github.com/shawwn/jaxnotes/blob/master/notebooks/001_jax.ipynb https://github.com/shawwn/jaxnotes/blob/master/notebooks/001... 2. Click "Open in Collaboratory" 3. Scroll to the first JAX section; start reading, linearly, all the way to the bottom. I'd like to think I'm a fairly capable hacker. And that notebook is how I learned JAX, from zero knowledge. Because I had zero knowledge, a week or two ago. Then I went from tutorial to tutorial, and copied down verbatim the things that I learned along the way. (It's still somewhat amazing to me how effective it is to literally re-type what a tutorial is trying to teach you. I'd copy each sentence, then fix up the markdown, and in the process of fixing up the markdown, unconsciously osmose the idea that they were trying to get across.) The best part was, I was connected remotely to a TPU VM the whole time I was writing that notebook, via a jupyter server running on the TPU. Because, like I said, you can run whatever the hell you want on TPUs now, so you can certainly run a jupyter server without breaking a sweat. It's so friggin' nice to have a TPU repl. I know I'm just wall-of-text'ing at this point, but I've literally waited two years for this to come true. (There's a fellow from the TPU team who DMs with me occasionally. I call him TPU Jesus now, because it's nothing short of a miracle that they were able to launch all of this infrastructure -- imagine how much effort, from so many teams, were involved in making all of this possible.) Anyway. Go read https://github.com/shawwn/website/blob/master/mlmind.md https://github.com/shawwn/website/blob/master/mlmind.md to get hyped, then read https://github.com/shawwn/website/blob/master/jaxtpu.md https://github.com/shawwn/website/blob/master/jaxtpu.md to get started, and then read https://github.com/shawwn/jaxnotes/blob/master/notebooks/001_jax.ipynb https://github.com/shawwn/jaxnotes/blob/master/notebooks/001... to get effective, and you'll have all my knowledge. In exchange for this, I expect you to build an NES emulator powered by TPUs. Do as many crazy ideas as you can possibly think of. This point in history will never come again; it feels to me like watching the internet itself come alive back in the 80's, if only briefly. It's like having a hundred raspberry pis to play with, except every raspberry pi is actually an ubuntu server with 96 CPUs and 330GB of RAM, and it happens to have 8 GPUs, along with a 100Gbit/s link to every other raspberry pi.
EMM_386 5y ago
> Google let him slip away because he didn’t have a degree! If this is the really the only reason he wasn't hired, that's ridiculous. I have a degree in a field totally unrelated to computer science and I've been a developer for 20+ years. Very "senior" at the moment.
- tpxl 5y ago
  Best devs I ever worked with never completed high school.
  - deleted 5y ago
    [deleted]
- est31 5y ago
  Likely this was for a position for which yearly total comp is in the single digit millions. I'd guess they are highly sought after and quite many people apply. So such filtering, while sad, is something to be expected.
- stellaathena 5y ago
  In Google’s defense, it’s not that Ben didn’t go to college it’s that he’s still a college student. This is less “experienced ML dev iced out over lack of degree” and more “college kid does something amazing and some people aren’t sold to hire him on the spot.” That said, I wouldn’t feel bad for Ben. The world is his oyster.
allenleein 5y ago
Thank you for being so honest, and thank for for sharing the links :)

GraffitiTim 5y ago

This was a very nice thing to say.

sillysaurusx 5y ago
They super earned it. From day one, everyone showed up with a level of drive and determination I haven't seen elsewhere. My name is on The Pile paper https://arxiv.org/abs/2101.00027 https://arxiv.org/abs/2101.00027 but I didn't do anything except make the books3 dataset. Stella, Leo, and everyone else did the hard work. You know, the work that's "actually useful to the scientific community." I didn't even help them hunt for typos, even though Stella asked me to. I was just like, sorry, no time, I have to focus on my own research. Imagine saying "nah" to helping shape one of the most important open source AI research projects of the coming years. Training data quality is becoming more and more of a focus. Lemme tell you a quick story. When https://venturebeat.com/2021/06/09/eleutherai-claims-new-nlp-model-approaches-gpt-3-level-performance/ https://venturebeat.com/2021/06/09/eleutherai-claims-new-nlp... come out, this quote caught my eye: > But EleutherAI claims to have performed “extensive bias analysis” on The Pile and made “tough editorial decisions” to exclude datasets they felt were “unacceptably negatively biased” toward certain groups or views. When I read this, I felt astonished that Eleuther was yet again trying to pose as the cool super-progressive AI lab. To my knowledge, no such thing ever happened. And I was involved with The Pile back when it was just me and Leo memeing in Discord DMs about how the world needed some quality training data once and for all. I went to Stella in DMs (you should follow her too! https://twitter.com/BlancheMinerva/status/1394089508723900422 https://twitter.com/BlancheMinerva/status/139408950872390042...) and was like, what the hell? I don't understand how this could possibly be true. What are these supposed "tough editorial decisions"? Stella calmly explained to me that the US Congressional Record had been considered and rejected for inclusion in The Pile. I thought "Big deal, who the hell cares?" while saying "Okay, but I don't know what that is." It’s a written record of all statements made in the US legislature. It was also somewhere between 1GB and 15GB, which would have been a significant portion of The Pile's total size. I'm going to quote from her private DMs with me, which I haven't asked for permission to do. So this is technically another bad move by me. But she put it so perfectly, I was stunned: > For half the history of the US, black people were slaves. For something like 75% of it, black people didn’t have the right to vote. A modern reader didn’t think there wasn’t a high proportion of extremely racist content, that would primarily be an inditement of modern people lol. > The reason we first looked at it was that we included a similar document for the EU Parlement It took me a few minutes to come to my senses, but I finally realized: (a) this dataset likely contained a huge proportion of content that, politics aside, would be a Very Bad Idea to include in your ML models by default; (b) Eleuther had just been trying to do good work this whole time So you know, when you're in that situation, you can choose to either keep believing your own false ideas, or you can pay attention to empirical evidence and change your behavior. And empirically, I had been a massive asshole to everyone since pretty much the beginning. The only thing I helped with was books3 and arranging The Eye to get them some reliable hosting. (Shoutout to The Eye, by the way. Help 'em out if you can: https://the-eye.eu/public/AI/ https://the-eye.eu/public/AI/) And there's my name, right there on the paper. It's even worse than I described. I put the paper in jeopardy, because they were submitting it to a conference with strict anonymity rules. I had no idea about it (no one told me). I ended up so happy to see my name on a real arxiv paper that I tweeted out some self-congratulatory bullshit, and quote-tweeted something linking to The Pile. It was a few days into the anonymity period, but nonetheless, it was a violation of the anonymity rules. A lot of people saw that tweet, and the whole point of the rules is to ensure that people don't get unfair advantages by advertising on social media. When they came to me in DMs apologizing profusely for not talking with me about it, and asking me to delete the tweet, I basically told them to go shove a spoon up their.... because I didn't agree to any rules, and the idea that The Pile should go radio silent for five months on social media struck me as completely crazy. In hindsight, I was... just awful. So I mean, me posting this is like, the absolute minimum I can do. They've been the ones working for like a year to make all of this happen. Ended up feeling like a fraud, since everyone thinks highly of my ML work, and here I'd been nothing but problematic for a group of people who are just trying to ship good scientific work. Fast forward to today, and the results are clear. Go help Eleuther: https://www.eleuther.ai/ https://www.eleuther.ai/ They're cool, and you'll get a shot at changing the world. I'm not sure you even have to be particularly skilled; some of the most valuable work was done by people who just showed up and started doing things, e.g. making the website look a little nicer, or making a cool logo.

reed1234 5y ago

It takes a lot to be able to find something in yourself like that and admit it to yourself and everyone. I always appreciate people like that. I also tried the playground and was impressed that it was free! It must be a sizable chunk of money to run that.

sillysaurusx 5y ago
Believe it or not, it's completely free. It's thanks to TFRC. It's the most world-changing program I know of. It's why I go door to door like the proverbial religious fanatic, singing TFRC's praises, whether people want to listen or not. Because for the first time in history, any capable ML hacker now has the resources they need to do something like this. Imagine it. This is a legit OpenAI-style model inference API. It's now survived two HN front page floods. (I saw it go down about an hour ago, so I was like "Nooo! Prove you're production grade! I believe in you!" and I think my anime-style energy must've brought it back up, since the API works fine now. Yep, it was all me. Keyboard goes clackclackclack, world changes, what can I say? Just another day at the ML office oh god this joke has gone on for like centuries too long.) And it's all thanks to TFRC. I'm intentionally not linking anything about TFRC, because in typical google fashion, every single thing you can find online is the most corporate, soulless-looking "We try to help you do research at scale" generic boilerplate imaginable. So I decided to write something about TFRC that wasn't: https://blog.gpt4.org/jaxtpu https://blog.gpt4.org/jaxtpu (It was pretty hard to write a medieval fantasy-style TPU fanfic, but someone had to. Well, maybe no one had to. But I just couldn't let such a wonderful project go unnoticed, so I had to try as much stupid shit as possible to get the entire world to notice how goddamn cool it is.) To put things into perspective, a TPU v2-8 is the "worst possible TPU you could get access to." They give you access to 100. On day one. This is what originally hooked me in. My face, that first day in 2019 when TFRC's email showed up saying "You can use 100 v2-8's in us-central1-f!": https://i.imgur.com/EznLvlb.png https://i.imgur.com/EznLvlb.png The idea of using 100 theoretically high-performance nodes of anything, in creative ways, greatly appealed to my gamedev background. It wasn't till later that I discovered, to my delight, that these weren't "nodes of anything." These are 96 CPU, 330GB RAM, Ubuntu servers. That blog post I just linked to is running off of a TPU right now. Because it's literally just an ubuntu server. This is like the world's best kept secret. It's so fucking incredible that I have no idea why people aren't beating down the doors, using every TPU that they can get their hands on, for as many harebrained ideas as possible. God, I can't even list how much cool shit there is to discover. You'll find out that you get 100Gbit/s between two separate TPUs. In fact, I'm pretty sure it's even higher than this. That means you don't even need a TPU pod anymore. At least, theoretically. I tried getting Tensorflow to do this, for over a year. kindiana (Ben Wang), the guy who wrote this GPT-J codebase we're all talking about, casually proved that this was not merely theoretical: https://twitter.com/theshawwn/status/1406171487988498433 https://twitter.com/theshawwn/status/1406171487988498433 He tried to show me https://github.com/kingoflolz/swarm-jax/ https://github.com/kingoflolz/swarm-jax/ once, long ago. I didn't understand at the time what I was looking at, or why it was such a big deal. But basically, when you put each GPT layer on a separate TPU, it means you can string together as many TPUs as you want, to make however large of a model you want. You should be immediately skeptical of that claim. It shouldn't be obvious that the bandwidth is high enough to train a GPT-3 sized model in any reasonable time frame. It's still not obvious to me. But at this point, I've been amazed by so many things related to TPUs, JAX, and TFRC, that I feel like I'm dancing around in willy wonka's factory while the door's wide open. The oompa loompas are singing about "that's just what the world will do, oompa-loompa they'll ignore you" while I keep trying to get everybody to stop what they're doing and step into the factory. The more people using TPUs, the more google is going to build TPUs. They can fill three small countries entirely with buildings devoted to TPUs. The more people want these things, the more we'll all have. Because I think Google's gonna utterly annihilate Facebook in ML mindshare wars: https://blog.gpt4.org/mlmind https://blog.gpt4.org/mlmind TPU VMs just launched a month ago. No one realizes yet that JAX is the React of ML. Facebook left themselves wide open by betting on GPUs. GPUs fucking suck at large-scale ML training. Why the hell would you pay $1M when you can get the same thing for orders of magnitude less? And no one's noticed that TPUs don't suck anymore. Forget everything you've ever heard about them. JAX on TPU VMs changes everything. In five years, you'll all look like you've been writing websites in assembly. But hey, I'm just a fanatic TPU zealot. It's better to just write me off and keep betting on that reliable GPU pipeline. After all, everyone has millions of VC dollars to pour into the cloud furnace, right? TFRC changed my life. I tried to do some "research" https://www.docdroid.net/faDq8Bu/swarm-training-v01a-pdf https://www.docdroid.net/faDq8Bu/swarm-training-v01a-pdf back when Tensorflow's horrible problems were your only option on TPUs. Nowadays, you can think of JAX as "approximately every single thing you could possibly hope for." GPT-J is proof. What more can I say? No TFRC, no GPT-J. The world is nuts for not noticing how impactful TFRC has been. Especially TFRC support. Jonathan from the support team is just ... such a wonderful person. I was blown away at how much he cares about taking care of new TFRC members. They all do. (He was only ever late answering my emails one time. And it was because he was on vacation!) If you happen to be an ambitious low-level hacker, I tried to make it easier for you to get your feet wet with JAX: 1. Head to https://github.com/shawwn/jaxnotes/blob/master/notebooks/001_jax.ipynb https://github.com/shawwn/jaxnotes/blob/master/notebooks/001... 2. Click "Open in Collaboratory" 3. Scroll to the first JAX section; start reading, linearly, all the way to the bottom. I'd like to think I'm a fairly capable hacker. And that notebook is how I learned JAX, from zero knowledge. Because I had zero knowledge, a week or two ago. Then I went from tutorial to tutorial, and copied down verbatim the things that I learned along the way. (It's still somewhat amazing to me how effective it is to literally re-type what a tutorial is trying to teach you. I'd copy each sentence, then fix up the markdown, and in the process of fixing up the markdown, unconsciously osmose the idea that they were trying to get across.) The best part was, I was connected remotely to a TPU VM the whole time I was writing that notebook, via a jupyter server running on the TPU. Because, like I said, you can run whatever the hell you want on TPUs now, so you can certainly run a jupyter server without breaking a sweat. It's so friggin' nice to have a TPU repl. I know I'm just wall-of-text'ing at this point, but I've literally waited two years for this to come true. (There's a fellow from the TPU team who DMs with me occasionally. I call him TPU Jesus now, because it's nothing short of a miracle that they were able to launch all of this infrastructure -- imagine how much effort, from so many teams, were involved in making all of this possible.) Anyway. Go read https://github.com/shawwn/website/blob/master/mlmind.md https://github.com/shawwn/website/blob/master/mlmind.md to get hyped, then read https://github.com/shawwn/website/blob/master/jaxtpu.md https://github.com/shawwn/website/blob/master/jaxtpu.md to get started, and then read https://github.com/shawwn/jaxnotes/blob/master/notebooks/001_jax.ipynb https://github.com/shawwn/jaxnotes/blob/master/notebooks/001... to get effective, and you'll have all my knowledge. In exchange for this, I expect you to build an NES emulator powered by TPUs. Do as many crazy ideas as you can possibly think of. This point in history will never come again; it feels to me like watching the internet itself come alive back in the 80's, if only briefly. It's like having a hundred raspberry pis to play with, except every raspberry pi is actually an ubuntu server with 96 CPUs and 330GB of RAM, and it happens to have 8 GPUs, along with a 100Gbit/s link to every other raspberry pi.

EMM_386 5y ago

> Google let him slip away because he didn’t have a degree! If this is the really the only reason he wasn't hired, that's ridiculous. I have a degree in a field totally unrelated to computer science and I've been a developer for 20+ years. Very "senior" at the moment.

tpxl 5y ago
Best devs I ever worked with never completed high school.
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est31 5y ago
Likely this was for a position for which yearly total comp is in the single digit millions. I'd guess they are highly sought after and quite many people apply. So such filtering, while sad, is something to be expected.
stellaathena 5y ago
In Google’s defense, it’s not that Ben didn’t go to college it’s that he’s still a college student. This is less “experienced ML dev iced out over lack of degree” and more “college kid does something amazing and some people aren’t sold to hire him on the spot.” That said, I wouldn’t feel bad for Ben. The world is his oyster.

allenleein 5y ago

Thank you for being so honest, and thank for for sharing the links :)