Is this just Internet smart contrarianism or a real thing? Are logic gates in a digital circuit just behaving statistically according to their experience?
You know, you might really enjoy consumer behaviour. When you get into the depths of it, you’ll end up running straight into that idea like you’re doing a 100 metre dash in a 90 metre gym. It’s quite interesting how arguably the best funded group under the psychology umbrella runs directly into this. One of my favourite examples is how heuristics will lead otherwise reasonable people to make decisions that are not in their interest.
Communicating is usually about inferring. I dont think token to token. And I don’t think “well statistically I could say ‘and’ next but I will say ‘also’ instead to give my speech some flash”. If I decided on swapping a word I would have made my decision long ago, not in the moment. Thought and logic are not me pouring through my brain finding a statistical path to any answer. Often I stop and say “I dont know”.
> I'm not convinced that "actual logic and thought" aren't just about inferring what comes next statistically based on experience.
Often they are the exact opposite. Entire fields of math and science talk about this. Causation vs correlation, confirmation bias, base rate fallacy, bayesian reasoning, sharp shooter fallacy, etc.
All of those were developed because “inferring from experience” leads you to the wrong conclusion.
Bayesian reasoning is just another algorithm for predicting from experience (aka your prior).
I took the GP to be making a general point about the power of “next x prediction” rather than the algorithm a human would run when you say they are “inferring from experience”. (I may be assuming my own beliefs of course.)
Eg even LeCun’s rejection of LLMs to build world models is still running a predictor, just in latent space (so predicting next world-state, instead of next-token).
And of course, under the Predictive Processing model there is a comprehensive explanation of human cognition as hierarchical predictors. So it’s a plausible general model.
> under the Predictive Processing model there is a comprehensive explanation of human cognition as hierarchical predictors
It’s plausible!
But keep in mind humans have been explaining ourselves in terms of the current most advanced technology for centuries. We used to be kinda like clockwork, then a bit like a steam engine, then a lot like computers, and now we’re just like AI.
That’s why you blow a gasket or fuse, release some steam, reboot your life, do brain dump, feel like a cog in the machine, get your wires crossed, etc
This is my immediate concern as well. Sam said in an interview that he sees "intelligence" as a utility that companies like OpenAI would own and rent out.
The problem is the cat is already out of the bag on the technology. Anyone can go over to Huggingface, follow a cookbook [0], and build their own models from the ground up. He cannot prevent that from taking place or other organizations releasing full open weight/open training data models as well, on permissive licenses, which give individuals access to be able to modify those models as they see fit. Sam wishes he had control over that but he doesn't nor will he ever.
Im thinking mainly if they manage to get some kind of regulations that make open source impractical for commercial use, or hardware gets too expensive for small hobbyists and bootstrapped startups, or if the large data center models wildly out class open source models. I love using open source models but I can't do what I can do with 1m context opus, and that gap could get worse? Or maybe not, it could close, I don't know for sure, and how long will Chinese companies keep giving out their open source models? Lots of unknowns.
I know someone who just spent 10 days of GPU time on a RTX 3060 to build a DSLM [0] which outperforms existing, VC backed (including from Sam himself), frontier model wrappers that runs on sub 500 dollar consumer hardware which provides 100% accurate work product, which those frontier model wrappers cannot do. The fact that a two man team in a backwater flyover town speaks to how out of the badly out of the bag the tech is. Where the money is going to be isn't based off of building the biggest models possible with all of the data, its going to be about building models which specifically solve problems and can run affordably within enterprise environments by building to proprietary data since thats the differentiator for most businesses. Anthropic/OAI just do not have the business model to support this mode of model development to customers who will reliably pay.
Hopefully it continues to get commoditized to the point where no monopoly can get a stranglehold on it, since the end product ("intelligence") can be swapped out with little concern over who is providing it.
> Hopefully it continues to get commoditized to the point where no monopoly can get a stranglehold on it
I believe this is the natural end-state for LLM based AI but the danger of these companies even briefly being worth trillions of dollars is that they are likely to start caring about (and throwing lobbying money around) AI-related intellectual property concerns that they've never shown to anyone else while building their models and I don't think it is far fetched to assume they will attempt all manner of underhanded regulatory capture in the window prior to when commoditization would otherwise occur naturally.
All three of OpenAI, Google and Anthropic have already complained about their LLMs being ripped off.
In other words, it is an existential question for them. And given that some of the people running these companies have no moral convictions, expect a complete shitshow. Regulation. Natural security classifications. Endless lawfare. Outright bribery. Anything and everything to retain their valuations.
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