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ML promises to be profoundly weird

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Re: ML promises to be profoundly weird

#111

Post by simianwords »

xandrius wrote: post #107
simianwords wrote: post #80

Earlier quoted context omitted.

If it were not "just a statistical next token machine", how different would it behave? Can you find an example and test it out?

Wait, you're asking to find and produce a example of a feasible and better alternative to LLMs when they are the current forefront of AI technology? Anyway, just to play along, if it weren't just a statistical next token machine, the same question would have always the same answer and not be affected by a "temperature" value.

Thats also how humans behave.. I don't see how non determinism tells me anything.

My question was a bit different: if were not just a statistical next token predictor would you expect it to answer hard questions? Or something like that. What's the threshold of questions you want it to answer accurately.

Re: ML promises to be profoundly weird

#112

Post by busterarm »

nisegami wrote: post #104

Here's the opening paragraph of chapter 2 with "people" subbed out for terms referring AI/models/etc. "People are chaotic, both in isolation and when working with other people or with systems. Their outputs are difficult to predict, and they exhibit surprising sensitivity to initial conditions. This sensitivity makes them vulnerable to covert attacks. Chaos does not mean people are completely unstable; most people be…

Aren't you also making a large part of the author's point for him by effectively equating LLMs with people here and comparing on outputs?

Plausibly your text looks equivalent but we all (should) have the context to know better.

Re: ML promises to be profoundly weird

#113

Post by gbgarbeb »

nine_k wrote: post #72
_dwt wrote: post #58

I have a question for all the "humans make those mistakes too" people in this thread, and elsewhere: have you ever read, or at least skimmed a summary of, "The Origin of Consciousness in the Breakdown of the Bicameral Mind"? Did you say "yeah, that sounds right"? Do you feel that your consciousness is primarily a linguistic phenomenon? I am not trying to be snarky; I used to think that intelligence was intrinsically…

If you look at different ancient traditions, you will notice how they struggle with the limitations of language, with its inability to represent certain things that are not just crucial for understanding the world, but also are even somehow communicable. Buddhists dug into that in a very analytical, articulate way, for instance. Another perspective: cetaceans are considered to be as conscious as humans, but any attem…

You're a little out of date. Cetaceans communicate images to each other in the form of ultrasonic chirps. They chirp, they hear a reflection, and they repeat the reflection.

Re: ML promises to be profoundly weird

#114

Post by htrp »

drob518 wrote: post #94

> It remains unclear whether continuing to throw vast quantities of silicon and ever-bigger corpuses at the current generation of models will lead to human-equivalent capabilities. Massive increases in training costs and parameter count seem to be yielding diminishing returns. Or maybe this effect is illusory. Mysteries! I’m not even sure whether this is possible. The current corpus used for training includes virtual…

We pay people to create more high quality tokens (mercor, turing) which are then fed into data generating processes (synthetic data) to create even more tokens to train on

Re: ML promises to be profoundly weird

#115

Post by slopinthebag »

AStrangeMorrow wrote: post #17
josefritzishere wrote: post #11

I appreciate the directness of calling LLMs "Bullshit machines." This terminology for LLMs is well established in academic circles and is much easier for laypeople to understand than terms like "non-deterministic." I personally don't like the excessive hype on the capabilities of AI. Setting realistic expectations will better drive better product adoption than carpet bombing users with marketing.

I have still mixed feelings about LLMs. If I take the example of code, but that extends to many domains, it can sometimes produce near perfect architecture and implementation if I give it enough details about the technical details and fallpits. Turning a 8h coding job into a 1h review work. On the other hand, it can be very wrong while acting certain it is right. Just yesterday Claude tried gaslighting me into accept…

I think over time we will find better usage patterns for these machines. Even putting a model in a position to gaslight the user seems like a complete failure in the usage model. Not critiquing you at all on this, it's how these models are marketed and what all the tooling is built around. But they are incredibly useful and I think once we figure out how to use them better we can minimise these downsides and make ourselves much more productive without all the failures.

Of course that won't happen until the bubble pops - companies are racing to make themselves indispensable and to completely corner certain markets and to do so they need autonomous agents to replace people.

Re: ML promises to be profoundly weird

#116

Post by nyeah »

ajross wrote: post #81
nyeah wrote: post #20

Earlier quoted context omitted.

"Lies are all we have." If so, how do we distinguish between code that works and code that doesn't work? Why should we even care?

> If so, how do we distinguish between code that works and code that doesn't work? Hilariously, not by using our brains , that's for sure. You have to have an external machine. We all understand that "testing" and "code review" are different processes, and that's why.

Good point. We choose certain tests to perform. We choose certain test results to pay attention to. We don't just keep chatting about (reviewing) the code. We do something else.

If lies are all we have, then how is this behavior possible?

Re: ML promises to be profoundly weird

#117

Post by xmprt »

drob518 wrote: post #94

> It remains unclear whether continuing to throw vast quantities of silicon and ever-bigger corpuses at the current generation of models will lead to human-equivalent capabilities. Massive increases in training costs and parameter count seem to be yielding diminishing returns. Or maybe this effect is illusory. Mysteries! I’m not even sure whether this is possible. The current corpus used for training includes virtual…

I see a lot of researchers working on newer ideas so I wouldn't be surprised if we get a breakthrough in 5-10 years. After all, the gap between AlexNet and Attention is All You Need was only 6 years. And then Scaling Laws was about 3-4 years after that. It might seem like not much progress is being made but I think that's in part because AI labs are extremely secretive now when ideas are worth billions (and in the right hands, potentially more).

Of course 5-10 years is a long time to bang our heads against the wall with untenable costs but I don't know if we can solve our way out of that problem.

Re: ML promises to be profoundly weird

#118

Post by qsera »

simianwords wrote: post #103
qsera wrote: post #101

Earlier quoted context omitted.

But why do you need an example? Isn't it pretty well understood that LLMS will have trouble responding to stuff that is under represented in the training data? You will just won't have any clue what that could be.

fair so it must be easy to give an example? I have ChatGPT open with 5.4-thinking. I'm honestly curious about what you can suggest since I have not been able to get it to bullshit easily.

I am not the OP, an I have only used ChatGPT free version. Last day I asked it something. It answered. Then I asked it to provide sources. Then it provided sources, and also changed its original answer. When I checked the new answers it was wrong, and when I checked sources, it didn't actually contain the information that I asked for, and thus it hallucinated the answers as well as the sources...

Re: ML promises to be profoundly weird

#119

Post by erichocean »

beders wrote: post #79

Thank you for putting it so succinctly. I keep explaining to my peers, friends and family that what actually is happening inside an LLM has nothing to do with conscience or agency and that the term AI is just completely overloaded right now.

AI is exactly the right term: the machines can do "intelligence", and they do so artificially.

Just like we have machines that can do "math", and they do so artificially.

Or "logic", and they do so artificially.

I assume we'll drop the "artificial" part in my lifetime, since there's nothing truly artificial about it (just like math and logic), since it's really just mechanical.

No one cares that transistors can do math or logic, and it shouldn't bother people that transistors can predict next tokens either.

Re: ML promises to be profoundly weird

#120

Post by rudhdb773b »

beders wrote: post #79

Thank you for putting it so succinctly. I keep explaining to my peers, friends and family that what actually is happening inside an LLM has nothing to do with conscience or agency and that the term AI is just completely overloaded right now.

> what actually is happening inside an LLM has nothing to do with conscience or agency

What makes you think natural brains are doing something so different from LLMs?

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