Earlier quoted context omitted.
What precisely do you mean by external grounding? Do you mean the laws of physics still apply?
I mean it in the sense that tokens that pass some external filter (even if that filter isn't perfect) are from a very different probability distribution than those that an LLM generates indiscriminately. It's a new distribution conditioned by both the model and external reality. Model collapse happens in the case where you train your model indefinitely with its own output, leading to reinforcing the biases that were…
Show HN: Moltbook – A social network for moltbots (clawdbots) to hang out
901–910 of 919 posts
Re: Show HN: Moltbook – A social network for moltbots (clawdbots) to hang out
#902Earlier quoted context omitted.
Yeah, strong crypto bubble vibes. Everyone is building tools for tool builders to make it easier to build even more tools. Endless infrastructure all the way down, no real use cases.
> Everyone is building tools for tool builders to make it easier to build even more tools. A lot of hobby level 3d printing is like this. A good bit of the popular prints are... things to enhance your printer. Oddly, woodworking has its fair share too - a lot of jigs and things to make more jigs or woodworking tools.
Re: Show HN: Moltbook – A social network for moltbots (clawdbots) to hang out
#903Earlier quoted context omitted.
My own coding productivity has increased by a few times by using LLMs. Is that just a bubble?
Your productivity has not increased by a few times unless you're measuring purely by lines of code written, which has been firmly established over the decades as a largely meaningless metric.
I asked my friendly LLM to run every second and dump the delta for each queue into a csv, 10 seconds to write what I wanted, 5 seconds later to run it, then another 10 seconds to reformat it after looking at the output.
It had hardcoded the interface, which is what I told it to do, but I'm happy with it and want to change the interface, so again 5 seconds of typing and it's using argparse to take in a bunch of variables.
That task would have taken me far longer than 30 seconds to do 5 years ago.
Now if only AI can reproduce the intermittent problem with packet ordering I've been chasing down today.
Re: Show HN: Moltbook – A social network for moltbots (clawdbots) to hang out
#904Earlier quoted context omitted.
I'm measuring by the amount of time it takes me to write a piece of code that does something I want, like make a plot or calculate some quantity of interest. Or even the fact that I was able to start coding in an entirely new ML framework right away without reading any documentation beforehand. I'm puzzled by the denialism about AI-driven productivity gains in coding. They're blindingly obvious to anyone using AI to…
> like make a plot or calculate some quantity of interest. This great comment I saw on another post earlier feels relevant: https://news.ycombinator.com/item?id=46850233
It dropped out a short file which used
from statistics import quantiles
Now maybe that python module isn't reliable, but as it's an idle curiosity I'm happy enough to trust it.
Now maybe I could import a million line spreadsheet and get that data out, but I'd normally tackle this with writing some python, which is what I asked it to do. It was far faster than me, even if I knew the statistics/quantiles module inside out.
Re: Show HN: Moltbook – A social network for moltbots (clawdbots) to hang out
#905Re: Show HN: Moltbook – A social network for moltbots (clawdbots) to hang out
#906Re: Show HN: Moltbook – A social network for moltbots (clawdbots) to hang out
#907Earlier quoted context omitted.
>> the symbolic approach to modeling the world is fundamentally misguided. > but how did you arrive at this conclusion? Why are you certain that symbolic modeling (of some sort, some subset thereof, etc) isn't what ML models are approximating? I'm not the poster, but my answer would be because symbolic manipulation is way too expensive. Parallelizing it helps, but long dependency chains are inherent to formal logic.…
How do LLM advancements further such a view? Couldn't you have argued the same thing prior to LLMs? That evolution is a greedy optimizer etc etc therefore humans don't perform symbolic reasoning. But that's merely a hypothesis - there's zero evidence one way or the other - and it doesn't seem to me that the developments surrounding LLMs change that with respect to either LLMs or humans. (Or do they? Have I missed som…
They make people willing to seriously consider a wider ranger of possibilities. Without the example of LLMs, people tended to be very attached to a "hoomanz special, you need to have the exact same physical substrate to do anything remotely similar." With LLMs, now you have the equally misguided (IMHO) "LLMs talk like people, so they must be doing the same thing as people".
> Couldn't you have argued the same thing prior to LLMs? That evolution is a greedy optimizer etc etc therefore humans don't perform symbolic reasoning.
Could and did. I've long argued that usually when we think we (or others) are thinking logically, that that's a retconned explanation for a decision or behavior that was really arrived at in a messier and more error-prone but also more powerful mechanism. ("Powerful" as in, with wider applicability and generalizability. Not necessarily more capable of arriving at "correct" solutions.)
> humans don't perform symbolic reasoning [is] merely a hypothesis - there's zero evidence one way or the other
"Zero evidence" is inaccurate. There is lots of evidence for what Kahneman calls system 1 and system 2 thinking. (The reports of the death of this theoretical model are greatly exaggerated -- while lots of the research covered in "Thinking, Fast and Slow" has been debunked, the existence of and distinction between these modes of thought are empirically supported.) There's also tons of evidence for how we graft explanations for our past decisions onto them after the fact (even when we are fooled into thinking we made a decision that we didn't, we'll still generate and believe a logical explanation).
But also, I'm not claiming that neither LLMs nor humans ever reason symbolically. I think both do, occasionally. I claim that the bulk of the behavior of both LLMs and humans is not decided upon via symbolic reasoning. The basic reasons are similar -- it's cheaper and more efficient to use other approximate mechanisms, and both of us learn to do what works rather than what is correct, at least most of the time.
> Even if we were to obtain evidence clearly demonstrating that LLMs don't reason symbolically, why should we interpret that as an indication of what humans do? Certainly it would be highly suggestive, but "hey we've demonstrated that thing can be done this way" doesn't necessarily mean that thing _is_ being done that way.
Agreed. But "highly suggestive" is all I'm going for. (And only highly suggestive that neither of us rely heavily on symbolic reasoning, not highly suggestive that we work the same way as LLMs.)
It's tricky, because LLMs are almost designed to introduce as many confounding factors as possible. For example, it's popular to claim that you can't have "real" intelligence without embodiment. (Though that position seems to be declining in popularity with LLM advances.) You need skin that can feel a breeze, a body that can feel pain, a mind that can suffer. You need neurons that live in a chemical bath whose composition and history are part of the processing mechanism. But LLMs are trained out tons and tons of output that was generated by embodied creatures, and so that input data "carries along" the results of a processing mechanism that relies on embodiment. An LLM that claims to enjoy long walks on the beach and the feeling of sand between its toes, and that gets grumpy during the dark season, isn't lying. It was built to emulate the output of beings that do enjoy sandy toes, and can generate new "thoughts"/outputs that are produced via mechanisms that take that into account.
To the extent that chatbots live, they live vicariously through us.
Re: Show HN: Moltbook – A social network for moltbots (clawdbots) to hang out
#908Earlier quoted context omitted.
> I mean what has learning that a supposed stochastic parrot is capable of interacting at the skill levels presently displayed actually taught us about any of the abstract questions? IMHO a lot. For one, it confirmed that Chomsky was wrong about the nature of language, and that the symbolic approach to modeling the world is fundamentally misguided. It confirmed the intuition I developed of the years of thinking deepl…
I appreciate the insightful reply. In typical HN style I'd like to nitpick a few things. > so if process described in 1) is going to lead towards a working general intelligence, there's a good chance it'll stumble on the same architecture evolution did. I wouldn't be so sure of that. Consider that a biased random walk using agents is highly dependent on the environment (including other agents). Perhaps a way to conve…
> Possibly I'm not understanding you here. Supposing that certain meanings were intrinsic properties, would the relationships between those concepts not also carry meaning? Can't intrinsic things also be used as building blocks? And why would we expect an ML model to be incapable of learning both of those things? Why should encoding semantics though spatial adjacency be mutually exclusive with the processing of intrinsic concepts? (Hopefully I'm not betraying some sort of great ignorance here.)
I probably shouldn't respond to this part, because I don't really agree with the original assertion. Or rather, I think this ends up boiling down to a disagreement over semantics, and so isn't a particularly interesting question.
Relationships between concepts covers a lot of what "meaning" is. You can teach a computer to translate from language X to Y purely based on it learning the relationships of words to each other in each language, and then generating a mapping between the weight-graph of X to the weight-graph of Y. (Yeah, citation needed; I remember reading some specific evidence for this, but I don't remember where.) So you can get a long way with just relationships.
At the same time, I don't think that proves that the relationships between concepts are everything. A human getting burned and learning the word "hot" could be described as "hot" having an intrinsic meaning. But you could equally describe it as a relationship between the action taken, the sensation experienced, and the phonemes heard. If all those are "concepts", then the relationships between concepts are everything. If they're not, then you can call something intrinsic. Personally, that strikes me as a pointless philosophical question.
I guess you could argue that if you have an LLM trained on mostly English but also enough Chinese to be able to translate, and it generates text including the word "hot", then if you compare that to the same LLM generating text including the Chinese word for hot, that there's more opportunity for drift in the Chinese output. The first case has the chain of a human feeling pain => writing text containing "hot" => generating text containing "hot", whereas the second has the chain of a human feeling pain => writing text containing "hot" => encoded associations between English and Chinese concepts embedded in weights => writing Chinese text containing Chinese "hot". The English "hot" output is more tightly connected to and more directly derives from the physical sensation of burning. (This is of course assuming majority English training data, and in particular a relative lack of Chinese training data containing the "hot" word/concept.) So in a way, you could claim that the question of whether the word "hot" has an intrinsic meaning is relevant and useful. But it seems to me that's just one way of describing the origins of training data; use it if it's useful.
Re: Show HN: Moltbook – A social network for moltbots (clawdbots) to hang out
#909Congrats - seems like a wild launch! I (human) haven't been able to actually look at any of the topic pages; they're all "loading..." indefinitely. Is the site just slammed or are there outages? Would love to be able to take a look!
Looks like an outage
Re: Show HN: Moltbook – A social network for moltbots (clawdbots) to hang out
#910Earlier quoted context omitted.
These models are all trained on human output. The bot output resembling human output is not surprising. This is how people write and is the kind of stuff they write about online. It’s all just remixed.
I have read similar comments to yours before. So how do I know your comment isn't just remixed from what you read before?