The thrill of AI is fading – and Wall Street is getting clear-eyed about value

https://www.cnn.com/2024/08/30/business/nvidia-wall-street-ai-bubble-nightcap/index.html

by breadwinner • 2 years ago

40 52 2 years ago

aurareturn3• 2 years ago

Until next-gen models show a drastic improvement in intelligence again. Then the hype will go through the roof once more.

gonzo41• 2 years ago

Its not intelligence, is probabilistic prediction. Ie fancy autocomplete.

rockemsockem6• 2 years ago

How you describe it is irrelevant, the results are what's relevant and LLMs have made it possible to significantly improve efficiency in a really broad range of tasks. And not just in BS tasks like blog spam copy, SEO sites, etc.

aurareturn3• 2 years ago

Does the brain also do some sort of probabilistic prediction?

jsemrau• 2 years ago

A fancy autocomplete is my Markov-chain-based Twitter bot I built in 2016.

dboreham2• 2 years ago

Some day the penny will drop that this is what your brain is doing too.

pizza• 2 years ago

There's a quote I read somewhere once that I have struggled since to find the original source: "if something is 100% correct, it can't be called intelligence"

edit: hope the source is not this one and thus originally from Rumsfeld, lol https://x.com/colbertlateshow/status/691851573031505920

Animats2• 2 years ago

Is that going to happen? Or are the limits of LLM technology being reached?

There are basic techniques for hallucination detection being developed.[1] But they're for "closed domain question answering", which seems to be what a general search engine could find. Techniques for open-ended question answering seem to mostly involve asking the same question multiple times, perhaps in different ways, and comparing the results.[2] This sort of works, but fails when the question legitimately has multiple equally good answers.

Most of these are black-box approaches - they're not going inside the LLM.

(I'm not saying that better AI is impossible. Merely that this particular approach may be hitting its limit.)

[1] https://www.kolena.com/blog/how-to-perform-hallucination-det...

[2] https://www.nature.com/articles/s41586-024-07421-0

aurareturn3• 2 years ago

I expect it to happen. If GPT5 bombs, then I’ll reset my expectations.

I consider models like Claude Sonnet 3.5 and LLama 405b as GPT4 class models.

I don’t think we’ve seen a true successor to GPT4 yet with all the technique learnings and 100x the compute.

ramshanker• 2 years ago

AI shoot to fame with Generative images and Text generation. Found many use cases. For me personally, I have to read a lot less documentation now to Code stuffs.

Apparently emergence of new use-cases is pretty thin. I see many domain specific opportunities, where AI can help. It will take some time to develop software where AI can be purchased and activated for niche company-internal use cases. Till that happens, AI (Neural Network training etc.) are hard core software development problem. Not usable by most of the companies.

7thpower• 2 years ago

Wall Street is not a reliable proxy for ‘value’.

For the people who judge these innovations by how well they can read their minds and how well it stands up to what people feel they were promised by Star Trek, the last 24 months have been a disappointment.

For those who are becoming far more productive than they previously were, learning new skills, and building the next generation of companies.. that same time has been life changing.

I don’t spend too much time worrying about wall street and I also don’t deny the bottom could fall out, but I have no doubts about the ability of these technologies to dramatically improve lives and be foundational for future improvements.

lolinder6• 2 years ago

For those who are becoming far more productive than they previously were, learning new skills, and building the next generation of companies.. that same time has been life changing.

As someone who is very much in this camp, I feel that life changing is a bit of an exaggeration for my own experience.

GitHub Copilot is a really good autocomplete. Stable Diffusion and company were a fun toy for a while. Perplexity.ai is pretty good at doing what Google could do before the enormous wave of AI junk made search completely intractible. But otherwise... life goes on. I got a few better tools out of it, but the chat models have been reliably useless for my professional work and I therefore don't trust them much for learning something new (see Gell-Mann amnesia [0]).

And I'm not someone with my head in the sand—I fine tuned GPT-2 back before anything LLM-based had hit the tech mainstream, much less the general public. I was one of the first to sign up for the Copilot Beta, and I run Ollama locally with a bunch of different models that I've tried out on several side projects. I have access to both Anthropic and OpenAI models at work and regularly break them out to try again... it just never actually helps.

People have all these amazing stories of all the productivity they gain by using these models, but at their best I always come away feeling like I spent a few minutes coaching a junior developer through a problem without actually having taught anyone anything. I'm left wondering if I'm somehow doing it wrong or if all the stories of amazing results are coming from juniors who don't realize the model isn't very much better at this than they are.

[0] https://en.m.wikipedia.org/wiki/Michael_Crichton#GellMannAmn...

roenxi• 2 years ago

Life changing seems fair, I'm making changes to my life assuming that programming jobs are about to get cutthroat competitive and then disappear. We've got something that is about as good as a junior developer in ChatGPT, much cheaper to employ for a month and it's competence is improving. It may not learn anything in a single session but at a higher level the rate of improvement of these models seems to be much faster than a human can manage. A human couldn't possibly learn as much as ChatGPT has in the time it has taken from founding OpenAI to now, and hardware improvement doesn't look like it'll cap out any time soon.

We've got all these people in a state of delusion that somehow the job of a developer isn't glorified autocomplete of what someone else prompts them with. We can't be sure what the speed is that it will happen, but the writing is on the wall that AI will obsolete software development roles as they currently exist.

r2_pilot• 2 years ago

I'm left wondering if I'm somehow doing it wrong or if all the stories of amazing results are coming from juniors who don't realize the model isn't very much better at this than they are.

And here I am, being impressed that SOTA AI passes the Turing programming test for a human junior programmer(using your own interpretation of the skill levels involved). Let's at least appreciate that 10 years ago this level of computer intellect was science fiction. And while I'm very much a "junior developer" (not my day job and I do have a BSCS), I can still use AI productively for my personal backlog of things I'd like to accomplish, and it's been pretty helpful for me notwithstanding its limitations.

olvy0• 2 years ago

My experience is very somilar. In my own narrow domain chatgpt, Claude, copilot et al has been a toy, as in, mostly useless answers to my very specific questions.

rockemsockem6• 2 years ago

The big way I think about how much value AI is providing me is by thinking about how much of my Google search traffic has shifted to chat GPT.

It's not just that it's a bit better, it's that it can answer queries I had that Google never could answer, especially really vague stuff.

JTyQZSnP3cQGa8B3• 2 years ago

I had to scold and mentor juniors who tried to push their crappy ChatGPT code in our codebase. They believe it gives them amazing powers because they don't have the experience to know whether a solution is good, bad, or completely buggy. Most of the time it's inefficient and full of bugs.

I do believe you learn from your own mistakes, but that requires thinking for yourself, not generating random answers.

orwin• 2 years ago

I think it's strictly inferior to a junior dev because it has no domain-specific knowledge, and even training it on your org repo does not really help it seems (ironically, a junior is doing it at my org as upper management want us to use GenAI, so maybe he fudged something)

osigurdson2• 2 years ago

> coaching a junior developer

I have honestly never gotten GPT to work like a junior developer as it can't seem to get details right so the actual coding usually ends up being done by me.

What it is great for is being a general teacher (sometimes wrong) and something to bounce ideas off of. It is enormously useful but not quite in the same way that people think it should. I am not the "manager" with the LLM being a direct report. At least I have never gotten it to work like that.

slavboj• 2 years ago

The piece itself mostly discusses Nvidia, which is an interesting company from an "AI hype" perspective in that they can only physically produce so many chips, and they are riding a very thin line where their margins are very high and FLOPS (or the equivalent) are in many ways already a commodity, so everyone wants to be set up to compete with them at the first misstep.

tomjen3• 2 years ago

Wall Streets idea of value is that the stock price changes within a few months at most, and that is if they are very patient.

Meanwhile getting value from AI means adapting new processes and changing organizations, something that big companies do extremely slowly.

thruway516• 2 years ago

It's the dotcom boom all over again. Right now the webvans and pets.com of the world are getting insane valuations just by using a .ai tld. When the hubbub dies and the froufrou wash away, the googles, amazons, facebooks that know what they're doing will quietly emerge. Too many hyper-funded startups that are little more than a thin wrapper over foundational LLMs, with dubious usefulness.

Veedrac• 2 years ago

Nothing excites and excuses a journalist with opinions more than a volatile stock. Doesn't matter what your opinion is, there's always a change that proves it. Even better: any rapidly changing stock value has to be volatile, so if something is in the news it's probably supporting your position! When you see these claims, ask yourself: How many times has the stock changed in this manner over the last year? How is its current static valuation relative to its long run history? Is the stock in a period of rapid change where higher volatility is expected? Those won't tell you where the stock is headed but they should at least help remind you not to trust horoscopes.

bschmidt1• 2 years ago

AI that already has obvious value:

- ChatGPT: The OG, most used AI chat. GPT-4/4o/multi-modal is already the prosumer LLM use case - excellent as an office/tech/language/creative assistant. Apparently Open AI's revenue is already in the billions and there's no denying people are using ChatGPT. There are also countless open-source libraries requiring `OPENAI_API_KEY` and many companies allocating budgets for spending there.

- LLM summarization: Amazon is already using LLMs to summarize reviews at the top of their product pages, search engines are using LLMs to summarize results at the top. GitHub has an LLM bot that you used to have to wait days for support to reply for - these are popping up everywhere. These will only improve to save people time and surface the exact information you're looking for. It's changing the way people access information and accomplish basic self-serve customer tasks.

- Customer service: The text-to-speech AI is getting very very good, to the point you can't tell it's not a human anymore. This alone is hugely disruptive as customer service touches so many verticals. It's already happening and will obviously only continue - especially when you talk to a service agent on the phone, increasingly it will be an LLM text-to-speech agent.

- llama.cpp/Ollama/HF & cloud services like Replicate: Infra for companies to run their own models instead of using Open AI due to cost/limitations. Obvious benefit for companies is you just want to pay for the compute you use, not for a consumer product like ChatGPT that abstracts away the usage - Open AI gets very expensive very quickly if using it on behalf of an application with many users. Also for niche use cases it might not be possible to accomplish what you want as an Open AI customer, you might need more control over models.

- Midjourney/Stable Diffusion type models: Totally separate from LLMs and language, there are diffusion models on image generation sites like LeonardoAI for creating concept art, illustrations, photography, and other visuals. There is a lot of obvious value here for creative work - it could displace a lot of conventional services and change the way we think about and pay for applied art. It's controversial in the way mp3s were, which itself will spawn some innovation in the legal space and in the way we interact with creative content.

- Self-driving cars: People are already taking the rides. AI modeling will continue to play a huge role in automating personal transit, and also for fleets. There will be self-delivering food, mail, and freight.

Particularly promising areas considering other modalities and fine-tunes:

- Music generation - Film (imagine prompt-2-film) - Extremely accurate/good legal advice where there are no flaws in your case - Medical diagnoses/analyses that are highly specific to your body and full of info and visuals particular to your condition - Negotiation AI for buying/selling, signing contracts for jobs or legal settlements, and general payments/invoicing - General automation ("Call the DMV and ask about my license", "Call the auto shop, don't let them upsell any services") - All the tech needed to integrate this stuff in the best ways

The thrill of AI is fading – and Wall Street is getting clear-eyed about value

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