this post was submitted on 22 Sep 2024
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Porque no los dos?
You're against computers being able to understand language, video, and images?
I am against the marketing buzz that is pretending (lying) that computers can understand language, video, and images, yes.
I am not against actual AI but it does not exist yet
They can functionally understand a good portion of it.
e.g. I can input a meme plus the words "explain this meme" and it can output an explanation.
They don’t understand though. A lot of AI evangelists seem to smooth over that detail, it is a LLM not anything that “understands” language, video nor images.
There are uses for these kinds of models like semi-automating analysing large pools of data, but even in a socialist society the resources that allocated to do it like it is currently is completely unsustainable.
We're into the Chinese Room problem. "Understand" is not a well-defined or measurable thing. I don't see how it could be measured except from looking at inputs&outputs.
Okay, then consider that when you input something into an LLM and regenerate the responses a few times, it can come up with outputs of completely opposite (and equally incorrect) meaning, proving that it does not have any functional understanding of anything and instead simply outputs random noise that sometimes looks similar to what one would output if they did understand the content in question.
Right. Like if I were talking to someone in total delirium and their responses were random and not a good fit for the question.
LLMs are not like that.
You don't seem to have read my comment. Please address what I said.
Can you paste an example of this error?
Have you ever used an LLM?
Here's a screenshot I took after spending literally 10 minutes with chatgpt very confidently stating incorrect answers to a simple question over and over. (from this thread) Not only is it completely incapable of coming up with a very simple correct answer to a very simple question, it is completely incapable of responding in a coherent way to the fact that none of its answers are correct. Humans don't behave this way. Nothing that understands what is being said would respond this way. It responds this way because it has no understanding of the meaning of anything that is being said. It is responding based on statistical likelihoods of words and phrases following one another, like a markov chain but slightly more advanced.
You were arguing with such an incredibly misanthropic piece of shit that of course they see a sufficient number of TI-88s bolted together as direct analogues to self-aware and conscious human intelligence.
Look at how that piece of shit treats other human beings: like the inferior "meat computers" that such a techbro mindset provides.
https://hexbear.net/comment/5438712
So why attribute it to an LLM in the first place then? All of the LLMs are just floating point numbers being multiplied and added inside a digital computer, the onus is on the AI bros to show what kind of floating point multiplication is real "understanding".
But it's inherently impossible to "show" anything except inputs&outputs (including for a biological system).
What are you using the word "real" to mean, and is it aloof from the measurable behaviour of the system?
You seem to be using a mental model that there's
A: the measurable inputs & outputs of the system
B: the "real understanding", which is separate
How can you prove B exists if it's not measurable? You say there is an "onus" to do so.
Because I've felt it, I've felt how understanding feels, because ultimately understanding is a conscious experience within a mind, you cannot define understanding without referencing conscious experience, you cannot possibly define it only in terms of behavior or function. So either you have to concede that every floating point multiplication in a digital chip "feels like something" at some level or you show what specific kind of floating point multiplication does.
But, ironically, the Chinese Room Argument you're bringing up supports what others are saying that LLMs do not 'understand' anything.
It seems to me like you are establishing 'understanding' with a functionalist meaning to be able to say that input/output is equivalent to understanding in order to say the measurable process in itself shows 'understanding'. But that's not what Searle, and seemingly the others here, seem to mean by 'understanding'. As Searle argues, it is not purely the syntactic manipulation in question but the semantic. In other words, these LLMs do not "know" the information they provide, they are just repeating based off the input/output process with which they were programmed. LLMs do not project or internalize any meaning to the input/output process. If they had some reflexive consciousness and any 'understanding', then they could have critically approach the meaning of the information in order to assess its validity against facts rather than just naïvely proclaiming that cockroaches got their name because they like to crawl into penises at night. Do you believe LLMs are conscious?
Does this mean that my TI-84 calculator was actually an AI since it could solve equations I put into it? Or Wolfram Alpha? Or a speed camera? These are all able to read external inputs to produce an output. At which point does your line go, because the current technology is nowhere near where mine goes.
We are currently ruining the biosphere so that some people might earn a lot of money by being able to lay off workers. If you remove this integral part to what “AI” is and all other negative externalities of course it will look better, but not all of the externalities are tied to the capitalist mode of production. Economies and resource allocation would still be a thing without capitalism, it isn’t like everything magically becomes good.
A choose your own adventure novel is an AI because you feed it a set of inputs (page numbers) and it feeds you a set of outputs (a dynamic story).
I'm against the current iteration of the buzzword that involves a bunch of wasted money being dumped into something that also generates a ton of energy use to get things somewhat correct rather than having it go towards actual needs we have affecting humanity.
Fusion's close to a core need of humanity.
Wait, you think fusion will be developed thanks to AI?
You don't?
No, I haven't seen any major technological breakthroughs coming from language models, other than language models themselves. Have you?
No. You want to suddenly change the subject to language models?
What other type of current AI claims problem-solving capabilities?
The entire field of Machine Learning, that has existed for decades, long before LLMs were even a theory?
This thread is funny. A few users are like "😡😡😡I hate everything about AI😡😡😡" and also "😲😲😲AI is used for technical research??? 😲😲😲 This is news to me! 😲😲😲"
Talk about no-investigation-no-right-to-speak. How can you have an opinion on a field without even knowing roughly what the field is?
The fusion ones for example
By fusion, what do you mean?
Nuclear fusion
So, are there any results of technological achievements from any AI models that show a trend towards increasing solving of scientific and technical problems?
Yes. I mean, this is absolute basics.
Please give me the examples
https://www.frontiersin.org/research-topics/66705/the-future-of-oncology-digital-twins-and-precision-cancer-care
https://www.frontiersin.org/research-topics/66585/artificial-intelligence-based-multimodal-imaging-and-multi-omics-in-medical-research
https://www.frontiersin.org/research-topics/65016/deep-learning-for-industrial-applications
etc.: https://www.frontiersin.org/journals/artificial-intelligence/research-topics
https://www.nature.com/articles/s42256-024-00883-x
https://www.nature.com/articles/s42256-024-00882-y
https://engineering.princeton.edu/news/2024/02/21/engineers-use-ai-wrangle-fusion-power-grid
The very first link shows that this is incremental benefit that's been taking place since 2010. Computational tools are useful, but you're providing mostly links of algorithms/learning models to sort pictures for medical purposes and diagnosis (useful and cool), and saying that somehow that means fusion will be solved by AI
Like if I go to Journal of Fusion Energy – https://link.springer.com/journal/10894 – the latest article is titled 'Artificial Neural Network-Based Tomography Reconstruction of Plasma Radiation Distribution at GOLEM Tokamak' and the 4th-latest is 'Deep Learning Based Surrogate Model a fast Soft X-ray (SXR) Tomography on HL-2 a Tokamak'. I am sorry if that upsets you but that's the way the field is.
I'm mostly answering the question I was asked: what are some examples of technical research in the field.
How can we solve plasma control without AI? And why exclude that tool?
I'm not saying we should exclude any tools, I'm just skeptical about the trend of calling everything AI, attributing all computational advances to AI, and jumping into the bandwagon of businesses trying to oversell any and all computating as AI.
That's just cosmetic stuff. Why care about what words people use?
Because that's how you end up with dipshits calling federal funding of the CIA socialism.
Socialism is when the government does stuff. If it does a lot of stuff that's communism.
That's the least plausible slippery-slope argument I have heard this month.
And yet I can go to some TYT video or a DSA meeting and hear some dipshit lib say socialism is when the government does stuff IRL.
Hell, I can go find a few coworkers who say that too, and immediately follow it up with calling Kamala a communist and Biden a Maoist.
But I suppose that's A-okay with you since
As you're trying to make a link between [using neural nets to research plasma control for fusion] and [Biden is a Maoist], I have no.reason to take you seriously.
You're advocating for the dilution of linguistic terminology and making it so you can smear people who hate dogshit stolen art as people who hate medical science.
The only person who shouldn't be taken seriously is you.
Because the words people use are very very important.
I think you’re going to need to link to some proof or example. You’re clearly using a definition of AI that’s broader than the colloquial definition everyone’s assuming you’re using.
Here is the latest edition of Nature Machine Intelligence, to give you a basic idea of the sort of research that in the AI field: https://www.nature.com/natmachintell/current-issue
Topics in Frontiers In Artificial Intelligence: https://www.frontiersin.org/journals/artificial-intelligence/research-topics
Foundations and Trends in Machine Learning: https://www.nowpublishers.com/MAL