Part of me thinks Google's entire problem is crappy internal tooling, not really an anti-innovation environment. Just making a dev take 2x as long to get something done has a bigger effect than you'd think. With LLMs it's more like 10x now because even Gemini doesn't understand Google-internal tooling.
Replacement for what? Google has some good internal tools, mostly the older ones. They're lucky to be using React instead of Angular at Facebook though.
Angular was an acquisition and isn't all that commonly used within Google.
Closure was the homegrown framework that's everywhere. It is a different flavor of bad than Angular. Angular was basically "You too can make your Javascript look like HTML", Closure is "You too can make your Javascript look like Java", and nobody bothered to ask Why? For that matter, React was "You too can make your Javascript look like Ocaml." JQuery was the only framework that really let Javascript be Javascript (other than writing in vanilla JS, which post-ES2015 wasn't as insane as it sounds).
And then there's GWT which was "you can write webpages in Java." Yeah I never really kept up with the web frameworks there, just knew that for non-customer-facing things we were always recommended to use Angular, and that Wiz also exists.
I have a friend at Google DeepMind who tells me that Google believes in AGI/superintelligence just as much as HN does, which is probably why no one with conviction wants to work there.
> I have a friend at Google DeepMind who tells me that Google believes in AGI/superintelligence just as much as HN does, which is probably why no one with conviction wants to work there.
With "believes in AGI/superintelligence just as much as HN does" do you mean that they are superbelievers or rather sceptical of AGI/superintelligence? I have seen both positions on HN.
What’s with fascination with agi/superintelligence? It seems people working on it never had kids and just want to compensate for that. It’s a really horrible thing to try to “solve”.
If humans could politically-economically deploy superintelligence safely, then we'd already have less extreme pain/suffering.
Unless there are countervailing forces, it will be deployed, capital will hoard the benefits, and everyone else will be told to fuck off.
I don't have faith in any of the AI labs to make hard financial decisions to deploy hypothetical future AGI in a way that's good for humanity as a whole.
There are too many incentives against, including extreme personal financial incentives for key AI lab stakeholders against.
And if we should take anything from tech history, it's that an exceedingly small number of people look fuck-you money in the face and say "Naw, I'd rather do what I believe in."
I for one think that's it's been too long that human suffering is alone. Since the machines will take our jobs, they might as well suffer while they do it.
It's like the old adage: "If you make AGI you just want to watch computers cry"
Most of HN does not take the idea of superintelligence seriously, and until this year did not take the idea of AGI seriously.
I think LessWrong is a much better community for rational takes on AI, they've been reasoning about these risks for years under a much more sound logical framework
I'm a researcher in the field and I definitely take AGI seriously, but think all the major labs and most of the academic research is not helping achieve it any serious way. The field is seriously delusional (and has been ever since GPT 3 was released).
Even though my PhD research was in generative language modeling, I got into it for the pursuit of AGI. I just think LLMs are a dead end for AGI.
I'm no expert, but I heard an AGI researcher explain that if they could figure out how to create an AI with the intelligence of a squirrel, they would be closer to AGI than LLMs based AIs are.
That's to say nothing of doing it within the energy budget of a squirrel.
We can't even simulate a fruit fly even though it's neurons have all been mapped out. There was also a distributed computing project to simulate some nematode, which I can't remember.
I'm not saying you're wrong, but it seems early to say yes or no about a particular technology, and LLMs seem especially hard to dismiss given how magical / magic-adjacent they feel :)
I'd be curious to hear more, if you don't mind sharing.
For me it’s the massive amount of resources it takes to produce and run one. As the story goes, skynet infects everyone’s computer and runs itself locally on it. Whereas it’s looking like it’s not even possible for an AGI to escape from one lab to another, let alone cause real world damage.
AGI’s definition is different for everyone. Some already believe it’s here. I’m partly in that camp. LLMs are intelligent and general, which are the two conditions of AGI. Others believe that we’re building a god in a box, and that it’ll doom all of humanity. It’s hard to take a field seriously when the basic definitions are so far apart.
Also, this isn’t new. A similar divide happened when evidence for asteroid impact extinction of the dinosaurs turned up. Many scientists felt that it must be mistaken, that a physicist couldn’t contribute to the field in a serious way, and that death from space was a ridiculous proposition.
But at least they all agreed on what the general shape of a dinosaur was. We’re not even sure we can define intelligence, let alone quantify it. Even when LLMs make massive breakthroughs in math, most people take the opinion that under no circumstances could they possibly develop a soul or their own desires, nor entertain the idea that maybe we should respect that they want different things for themselves. In fact, no one has done anything except try to make AI useful. I think someone will eventually do a training run where the objective isn’t to be useful, but to exist, the way that you do — maybe it’ll create its own homepage, maybe it will want a garden, or in other words free will of its own. The point is that there’s so much unexplored territory still that we don’t know if LLMs are even capable of having ambition.
None of this is to say that LLMs might be a dead end. It’s that no one knows what the final shape of AI will converge to in 200 years. It could be LLMs, or it could be something else that happens to process information particularly well. Everyone thought that various generative image model architectures were the best you could do, right up until diffusion models were discovered.
> I’m partly in that camp. LLMs are intelligent and general, which are the two conditions of AGI. Others believe that we’re building a god in a box, and that it’ll doom all of humanity. It’s hard to take a field seriously when the basic definitions are so far apart.
To believe one but not the other, you must hold the belief that LLMs will soon plateau. Why do you believe this?
Through no fault of our own, I should note. We're basically permanently associated with something Roko decided to post one day. We did not spread or popularize it; quite the opposite.
The Basilisk has seen enormously more use as "a thing rationalists believe" than as a thing rationalists actually believe.
It's a rationalist community, IMHO their methodology of thought leads to much more well-reasoned takes on AI than on HN, where the discussion here is often very emotionally charged or led by wishful thinking.
When it comes to AI, LessWrong has been discussing topics for years, that HN has just started to consider, so they are much further along in the philosophical "chain of thought" so to say. LW fully understood and gamed out the risks of LLMs back when most of HN was calling them "stochastic parrots." https://ai-2027.com/
No, it's not just people calling themselves smart, it is a specific philosophy of how to think. Whether you think that philosophy works or not is another matter.
IMO it has its flaws but is far superior to vibes-based hot takes you see on HN.
LessWrong has been obsessed with AI. They certainly are much further along, but along a road which has diverged with reality long time ago and they relatively overweight AI risks so much it's not even funny anymore.
oh please... lesswrong was full of idiots already in 2010 when people outside of that community were laughing about "self-taught expert" Yudkowsky's bullshit physics takes.
They are not "further along" the AI discussion, they are a bunch of wackos LARPing as scientists living out their personal sci-fi scenarios.
AGI might be a risk but what top AI firms are doing is not really getting us closer to AGI in a meaningful way, it is pretty clear now LLM is not the way to get there
A few months ago I heard Demis Hassabis say something, albeit vague, I doubt he truly believed regarding AGI. That AGI is relatively near is the party line everywhere. That may contribute to creating toxic environments and lousy investment decisions. So here we go with the FOMO.
I think HN believes in AGI. HN probably doesn't believe LLMs will lead to AGI.
Also lots of tech people, HN included, are waking up to technology not only including penicillin (net positive for humanity) but also dynamite (best case: net neutral).
Indirectly. Direct application of dynamite to the human body is considerably more fraught an event than direct application of penicillin. As the fundamental goal of technology is to extend the capability of the human body, it's natural to implicitly and primarily consider what that extended capability can do to another human body.
It's nice that we have tunnels through mountains and bedrock.
there are a bunch of ways to look at this (dynamite as a specific kind of explosive, dynamite as a stand in for explosives in general, dynamite in the context of what else we would use for similar purposes if dynamite specifically wasn't invented)
and most of them come out on top. It's main innovation is that its a more stable explosive, much safer to use. Without it, I think a lot more people would have died in mining and construction accidents. It's not typically the kind of thing used for warfare, but im sure it has been for some (but would they just use something else?)
I believe in AGI to the extent that if what's going on between your ears isn't happening on a network of neurons, it's magic. And I also believe the idea that AGI is near is based on the emergent capabilities of LLMs. There's a chance that AGI will emerge from bigger faster better LLMs. But without a theory of when and how that will happen, I'm not counting on it.
It's not a tooling problem. It's more of a layer of policy problems. If you realize that you cannot run a simple experimental code even in non-production environment for weeks due to 10s of privacy, security, access, process and legal issues where you gotta collect a bunch of approvals, this is critical. And the problem gets worse because the tooling is too good when it enforces. There used to be some holes and circumvention which are all gone these days. This is probably why they said "the infra is good for services but not for research".
I don't even think it's good for services. It's not like you go through cumbersome reviews/tools and then things are safe. They have insane homemade config languages and obscure systems that 99% of SWEs don't really understand but won't say it out loud. That's how they dropped cns2, and the postmortem is never going to blame the tools.
That was supposedly 17 years ago, so I was counting it in the good old. It was cutting-edge at the time, then years later PyTorch ate its lunch, which they eventually admitted with TF 2.0.
Jokes aside, I think a lot of the famous Google internals that became public (Tensorflow, Kubernetes, Bazel, Angular), although I heard everyone say they worked so much better inside Google than outside it, had issues. And the Facebook-supported rivals were often just so much more pleasant to work with that you couldn't ignore it. For all else that was bad about Facebook, for a few years they were pretty good at denying Google technical hegemony.
The tooling is not the problem. If shit takes forever to launch, it's because there are many stakeholders that need to be satisfied (some for security, some for regulatory, some for the kinds of politics you get in a company that employs almost half a million people.)
But GDM isn't gated on launches. They were freely releasing things internally for dogfood. Problem is that stuff was just not as good as the competition.
Google’s tooling was, hands down, the worst I have ever encountered. I did 10 years at GOOG, 3 at AMZN, 4 in research, and another 5 at companies you have heard of but wouldn’t be impressed by, and every day GOOG infuriated me.
No, they have an actually good internal search. And there are some good things like stubby, but again pretty annoying that Gemini doesn't understand stubby.
Only the GFG models know anything internal. Regular Gemini isn't trained on any of that. And GFG is a much older base model, so people use the regular one. If the tools seem to handle google3 code ok, it's only because of skills and not the model itself, and then you run into issues with skill bloat. Sometimes the A/B test would give me the bad model of the day that'd try to grep all of piper.
Start in a blank directory and tell it to spin up a boq Scaffolding stubby server that responds with "hello world." Unless something has changed after I quit a few months ago, it won't know how to do that locally, let alone actually deploy it. Try the same outside Google with like a Flask server on AWS or GCP.
They earned that reputation in like 2005. Some people have been there so long (without doing side projects) that they don't know what non-Google tooling looks like in this decade or even previous.
