I watched this interview when I first heard about Alexandr Wang. I'd seen he was the youngest self made billionaire, which is a pretty impressive credential to have under your belt, and I wanted to see if I could get a read on what sets him apart.
Unfortunately he doesn't reveal any particular intelligence, insight, or drive in the interview, nor does he in other videos I found. Possibly he hides it, or possibly his genius is beyond me. Or possibly he had good timing on starting a data labelling company and then leveraged his connections in SV (including being roommates with Sam Altman) to massively inflate Scale AI's valuation and snag a Meta acquisition.
I got the impression he's intelligent and hard working but to a large extent got lucky. I mean his idea was to kind of do a better version of Mechanical Turk which is ok as an idea but not amazing or anything. But then all these LLM companies were getting billions thrown at them by investors thinking they'd be AGI soon but they didn't work well without lots of humans doing fine tuning and Wang's company provided an outlet to throw the money at to get humans to try to do that.
I don't know how that will go at Meta. At the moment having lots of humans tweek LLMs still seems to be the main thing at the AI companies but that could change.
Or maybe, just maybe, becoming a billionaire has way more to do with luck than anything else.
I don't know about any billionaire in the history of billionaires who appears to have gotten there solely based on special abilities. Being born into the right circumstances is all it really takes.
They do testing like 'humanities last exam' and they build custom LLMs for some of the largest companies, the defense dept and other US govt stuff - bit here https://youtu.be/5noIKN8t69U?t=2037
Presumably this is all referring to Alexander Wang, who's 28 now. The data-labeling company he co-founded, Scale AI, was acquired by Meta at a valuation of nearly $30 billion.
But I suppose the criticism is that he doesn't have deep AI model research credentials. Which raises the age-old question of how much technical expertise is really needed in executive management.
> how much technical expertise is really needed in executive management.
For running an AI lab? a lot. Put it this way, part of the reason that Meta has squandered its lead is because it decided to fill it's genAI dept (pre wang) with non-ML people.
Now thats fine, if they had decent product design and clear road map as to the products they want to release.
but no, they are just learning ML as they go, coming up with bullshit ideas as they go and seeing what sticks.
But, where it gets worse, is they take the FAIR team and pass them around like a soiled blanket:
"You're a team that is pushing the boundaries in research, but also you need stop doing that and work on this chatbot that pretends to be a black gay single mother"
All the while you have a sister department, RL-L run by Abrash, who lets you actually do real research.
Which means most of FAIR have fucked off to somewhere less stressful, and more concentrated on actually doing research, rather than posting about how you're doing research.
Wangs misteps are numerous, the biggest one is re-platforming the training system. Thats a two year project right there, for no gain. It also force forks you from the rest of the ML teams. Given how long it took to move to MAST from fblearner, its going be a long slog. And thats before you tackle increasing GPU efficiency.
Meta has been itching to kill FBlearner for a while. Its basically an airflow style interface (much better to use as a dev, not sure about admin, I think it might even pre-date airflow)
They are mostly moved to MAST for GPU stuff now I dpn;t think any GPUs are assigned to fblearner anymore. This is a shame because it feels a bit less integrated into python and feels a bit more like "run your exe on n machines" however, it has a more reliable mechanism for doing multi-GPU things, which is key for doing any kind of research at speed.
My old team are not in the super intelligence org, so I don't have much details on the new training system, but there was lots of noise about "just using vercel" which is great apart from all of the steps and hoops you need to go through before you can train on any kind of non-opensource data. (FAIR had/has thier own cluster on AWS, but that meant that they couldn't use it to train on data we collected internally for research (ie paid studies and data from employees that were bribed with swag)
I've not caught up with the drama for the other choices. Either way, its kinda funny to watch "not invented here syndrome" smashing in to "also not invented here syndrome"
> Which raises the age-old question of how much technical expertise is really needed in executive management.
For whomever you choose to set as the core decision maker, you get out whatever their expertise is with minor impact by their guides.
Scaling a business is a skill set. It's not a skill set that captures or expands the frontier of AI, so it's clearly in the realm to label the gentleman's expensive buyout is a product development play instead of a technology play.
They hired a teenager to run one of their departments and thought that meant the teenager was smart instead of realizing that Meta’s department heads aren’t
> They hired a teenager to run one of their departments
Except they didn’t. The person in question was 28 when they hired him.
He was a teenager when he cofounded the company that was acquired for thirty billion dollars. But the taste of those really sour grapes must be hard to deal with.
> The person in question was 28 when they hired him.
Comic hyperbole darling. I know that's hard to understand, especially when you're one of the start up elect, who still believes.
But, FAIR is dead, meta have a huge brain drain, and Alex only has hardware and money to fix it. Worse for him, is he's surrounded by poisonous empire builders, and/or much more effective courtesans who can play zuck much more effectively than him.
Wang needs Zuck, and Zuck needs results. The problem is, people keep on giving zuck ideas, like robotics, and world models and AI sex bots.
Wang has to somehow keep up productivity, and integrate into meta's wider culture. Oh, and if he wants any decent amount of that 30billion, he's gotta stick out for 4 years.
I did my time and got my four years of RSUs from the buyout. my boss didn't neither did the CTO or about 2/3rds of the team. Meta will eat you, and I don't envy him.
noun: exaggerated statements or claims not meant to be taken literally.
but yeah sure, I'm seeing you, as someone who jumps to the defence of someone who wouldn't piss on you if you were on fire, as someone who still believes that startups make you rich.
Wang doesn't need you to protect him, he's got people to do that for him.
I could not imagine being as salty as the original poster seems to be about Alex Wang. To hold that amount of hate for a superior that is more successful than you can’t be good for the soul
sick burn