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PaperclipPerfector  17d ago (text post)   32894 thread views

Culture War Roundup for the week of November 4, 2024

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AI is still limited to text boxes and text manipulation or content generation; it has failed to live up the hype otherwise, like life extension, replacing workers, or treating disease, imho. The point of diminishing returns has been reached. it will take a whole new paradigm for AI to make the next leap. As far as transforming writing papers for college students, yeah, it has totally crushed that, and even then teachers are wising up. [If AI is able to produce a fiction novel that is a best-seller and or critically acclaimed either with text prompts or feeding it samples of other novels, I will be sold]

AI is still limited to text boxes and text manipulation or content generation

What? Of course it isn't.

AI is used all the time in a whole bunch of "invisible" applications that have nothing to do with text or content generation. Take a photo with a phone camera? You're using AI. Use Nvidia RTX voice? AI. Deal with pharmaceutical molecule research? Fair chance of AI being used. Play guitar and use the newest generation of amp modelers? That's AI again.

This is mostly because "AI" is a nonsense term. There are many different machine learning techniques being used in each of those applications and the fact that transformers have become somewhat general purpose doesn't change this.

But saying it's all AI is like saying it's all computers. It's missing the trees for the forest.

The tradeoffs and composability of these techniques are not uniform.

It's like saying that word processor spreadsheets can replace doing it by hand. It does not solve the spreadsheet problem, only makes it more efficient. Maybe the problem is me, but I am not seeing a big difference. I think the closest thing to truly transformational technology with direct, tangible real-world applications is printed buildings ( those cheap amazon.com homes that can be erected quickly), but this is not directly AI.

life extension, replacing workers, treating disease

But all of these problems are reducible to text generation. In some sense every conceivable problem is, because solving the problem means writing out the solution, in language.

For “solving” medicine, just have the LLM print a formula for the drug you want. A lot of remote work just is text generation in a sense, but for physical labor, a sufficiently intelligent LLM would be able to accelerate progress in robotics significantly.

Whether LLMs can actually achieve these things though is an open question.

In some sense every conceivable problem is, because solving the problem means writing out the solution, in language.

Too bad LLMs also only have access to solutions that were also previously written out, in languatge.

I mean, they are capable of "solving" novel problems not in their initial data. The problems just have to have the same "shape" as problems already in their training data.

And certain kinds of "language" type problems can be solved purely on the basis of the LLM's "knowledge" of English. Those problems aren't necessarily super hard for a human to do, but could save time on tasks like that.

Kinda sorta I guess?

For the examples given, if you ask an LLM to "print a formula for a drug you want", it will print something that looks like a formula for drugs that it's seen -- not super useful, other than by 'infinite monkeys' means?

Not sure what he's getting at on robotics, but the 'talking about awesome robots' role does not seem to have any shortage of applicants. To be frank, it's bullshit other than for people with bullshit jobs who feel they should continue to be paid but not have to sully themselves by personally generating the bullshit.

(the PR people at my work are super interested in LLMs, for example -- like, your life is not meaningless enough banging out 500 word communiques, you need a machine to do that for you? I really don't know what else to say)

The big problem with medicine has always been testing. Human trials will always be expensive and time consuming

it has failed to live up the hype otherwise, like life extension, replacing workers, or treating disease, imho.

Tesla is all-in on reinforcement learning for their next generation of Optimus robots, but they only spun that team up this summer. When I heard this news the stock price was at like 180 and I bought some calls for 230/250/270 for next June. After some movement I pushed these up to 300. Yet this still looks way too pessimistic. I think some exposure to $500c by the end of next year might be warranted.

The TSLA call options so expensive though. I like the 2x leveraged TSLA ETF instead. if TSLA doubles the ETF in theory will gain 3.5-4x, maybe offset decay by selling a long-dated ATM put + call

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