5 ms·
> I love that we're still learning the emergent properties of LLMs! TBH, this is (very much my opinion btw) the least surprising thing. LLMs (and especially th
by user_7832 6mo ago
> I love that we're still learning the emergent properties of LLMs!
TBH, this is (very much my opinion btw) the least surprising thing. LLMs (and especially their emergent properties) are still black boxes. Humans have been studying the human brain for millenia, and we are barely better at predicting how humans work (or for eg to what extent free will is a thing). Hell, emergent properties of traffic was not understood or properly given attention to, even when a researcher, as a driver, knows what a driver does. Right now, on the front page, is this post:
> 14. Claude Code Found a Linux Vulnerability Hidden for 23 Years (mtlynch.io)
So it's pretty cool we're learning new things about LLMs, sure, but it's barely surprising that we're still learning it.
(Sorry, mini grumpy man rant over. I just wish we knew more of the world but I know that's not realistic.)
- bensyverson 6mo agoLearning about the emergent properties of these black boxes is not surprising, but it's also not daily. I think every new insight is worth celebrating.
- TeMPOraL 6mo agoIndeed. For me, it's also a good reminder that AI is here to stay as technology, that the hype and investment bubble don't actually matter (well, except to those that care about AI as investment vehicle, of which I'm not one). Even if all funding dried out today, even if all AI companies shut down tomorrow, and there are no more models being trained - we've barely begun exploring how to properly use the ones we have. We have tons of low-hanging fruits across all fields of science and engineering to be picked, in form of different ways to apply and chain the models we have, different ways to interact with them, etc. - enough to fuel a good decade of continued progress in everything.
- bathtub365 6mo agoAI has been here to stay for decades
- TeMPOraL 6mo agoMaybe, but you couldn't tell that these days, casually scrolling this or any other tech-oriented discussion board.
- ethin 6mo agoI mean... You could? AI comes in all kinds of forms. It's been around practically since Eliza. What is (not) here to stay are the techbros who think every problem can be solved with LLMs. I imagine that once the bubble bursts and the LLM hype is gone, AI will go back to exactly what it was before ChatGPT came along. After all, IMO it's quite true that the AIs nobody talks about are the AIs that are actually doing good or interesting things. All of those AIs have been pushed to the backseat because LLMs have taken the driver and passenger seats, but the AIs working on cures for cancer (assuming we don't already have said cure and it just isn't profitable enough to talk about/market) for example are still being advanced.
- darkwater 6mo agoSaying that LLMs will disappear once the financial hype desinflate is like saying that LLMs are the answer to everything.
- 59nadir 6mo agoPersonally I read the GP post with more emphasis on this bit: > What is (not) here to stay are the techbros who think every problem can be solved with LLMs. LLMs are in all likelyhood here to stay, but the scumbags doing business around them right now are hopefully going away eventually.
- darkwater 6mo agoI agree on that part as well, but saying that AI will go back at what it was before ChatGPT came along is false. LLM will still be a standalone product and will be taken for granted. People will (maybe? hopefully?) eventually learn to use them properly and not generate tons of slop for the sake of using AI. Many "AI companies" will disappear from the face of Earth. But our reality has changed.
- user_7832 6mo agoOh I very much agree that it's great to see more research and findings and improvements in this field. I'm just a little puzzled by GP's tone (which suggested that it isn't completely expected to find new things about LLMs, a few years in).
- bensyverson 6mo agoI'm the GP! lol… Not sure how you got that from my tone, but I find these discoveries expected but not routine, and also interesting.
- user_7832 6mo agoSorry lol, to me it felt like you were (pleasantly) surprised by this research. IMO I'd hardly be surprised to see breakthroughs in LLM understanding years or even decades from now. I guess I misunderstood your tone.
- amelius 6mo agoStudies of LLMs belong in their own field of science, just like psychology is not being studied in the physics department.
- zer00eyz 6mo agoThe intersection of physics isnt psychology it is philosophy, and the same is true (at present) with LLM's Much as Diogenes mocked Platos definition of a man with a plucked chicken, LLM's revealed what "real" ai would require: contigous learning. That isnt to diminish the power of LLM's (the are useful) but that limitation is a fairly hard one to over come if true AGI is your goal.
- amelius 6mo agoWhat do you mean by the intersection of physics? The intersection of what with physics?
- zer00eyz 6mo agoThe intersection of disciplines. Sir Roger Penrose, on quantum consciousness (and there is some regret on his part here) -- OR -- Jacob Barandes for a much more current thinking on this sort of intersectional exploratory thinking.
- andai 6mo agoIs it because we haven't invented something better than backpropagation yet? From what I understand, a living neural network learns several orders of magnitude more efficiently than an artificial one. I'm not sure where that difference comes from. But my brain probably isn't doing back propagation, it's probably doing something very different.
- astrange 6mo agoYour brain is doing several different things, because there are different parts of your brain. (eg different kinds of learning for long-term memory, short-term memory, languages, faces and reflexes.)
- Invictus0 6mo agoTo say we've been studying the brain for millennia is an extreme exaggeration. Modern neuroscience is only about 50 years old.
- timcobb 6mo agoI came here to say this :)
- user_7832 6mo agoI hate to "umm, akshually" but apparently we have been studying the brain for thousands of years. I wasn't talking about purely modern neuroscience (which ironically for our topic of emergence, (often till recently/still in most places) treats the brain as the sum of its parts - be them neurons or neurotransmitters). > The earliest reference to the brain occurs in the Edwin Smith Surgical Papyrus, written in the 17th century BC. I was actually thinking of ancient greeks when writing my comment, but I suppose Egyptians have even older records than them. From https://en.wikipedia.org/wiki/History_of_neuroscience https://en.wikipedia.org/wiki/History_of_neuroscience
- Invictus0 6mo agoNone of that counts as studying the brain. It's like saying rubbing sticks together to make fire counts as studying atomic energy. Those early "researchers" were hopelessly far away from even the most tangential understanding of the workings of the brain.
- user_7832 6mo agoBut fundamentally speaking, they were trying to understand the brain, right? IMO that counts as science/study in my books. They understood parts/basics of intracranial pressure so long back. And if we say it's not science if it's not correct, well, (modern) physics isn't a science then, right? ;) As we haven't unified relativity with quantum mechanics?
- AlphaAndOmega0 6mo agoI'm a psychiatry resident who finds LLM research fascinating because of how strongly it reminds me of our efforts to understand the human brain/mind. I dare say that in some ways, we understand LLMs better than humans, or at least the interpretability tools are now superior. Awkward place to be, but an interesting one.
- p1esk 6mo agoLLMs are orders of magnitude simpler than brains, and we literally designed them from scratch. Also, we have full control over their operation and we can trace every signal. Are you surprised we understand them better than brains?
- ctoth 6mo ago> Also, we have full control over their operation and we can trace every signal. Are you surprised we understand them better than brains? Very, monsieur Laplace.
- danielmarkbruce 6mo ago"Designed" is a bit strong. We "literally" couldn't design programs to do the interesting things LLMs can do. So we gave a giant for loop a bunch of data and a bunch of parameterized math functions and just kept updating the parameters until we got something we liked.... even on the architecture (ie, what math functions) people are just trying stuff and seeing if it works.
- JoshTriplett 6mo agohttps://xkcd.com/1838/ https://xkcd.com/1838/
- batshit_beaver 6mo ago> We "literally" couldn't design programs to do the interesting things LLMs can do. That's a bit of an overstatement. The entire field of ML is aimed at problems where deterministic code would work just fine, but the amount of cases it would need to cover is too large to be practical (note, this has nothing to do with the impossibility of its design) AND there's a sufficient corpus of data that allows plausible enough models to be trained. So we accept the occasionally questionable precision of ML models over the huge time and money costs of engineering these kinds of systems the traditional way. LLMs are no different.
- elbear 6mo agoI thought it was determined (slight pun) that free will is not a thing. I'm referring to Sapolsky's book "Determined: A Science of Life Without Free Will)" as an example.