6 ms·
The thrill of AI is fading – and Wall Street is getting clear-eyed about value
- aurareturn 2y agoUntil next-gen models show a drastic improvement in intelligence again. Then the hype will go through the roof once more.
- gonzo41 2y agoIts not intelligence, is probabilistic prediction. Ie fancy autocomplete.
- rockemsockem 2y agoHow 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.
- jayski 2y agoI can't go back to coding without copilot. I agree it's a real efficiency booster.
- stackskipton 2y agoI can't go back to using it. I spent too much time reviewing the code it spit out and noticed when it absolutely wouldn't do what I needed it to, I was absolute slog since it was some else code.
- voidfunc 2y agoWho cares? Solve problem, write test case, move on. It's a huge efficency boon for those of us who realize our jobs are just mechanisms to make money. It sucks if you're into artisinal coding or whatever..
- namaria 2y agoYes it's all about that next paycheck. Churn out whatever drivel you need right? Btw have you noticed how the world is full of crap lately? I wonder why.
- lolinder 2y ago> into artisinal coding Is this the new phrase for "writing code that isn't going to blow up in my face in six months"?
- kranner 2y agoThere seem to be two different camps here: Copilot-users that use it largely for autocomplete and Cursor/Sonnet-users that use it for generating larger blocks of code. Personally I'm in the former camp; the efficiency gains are substantial and hallucinations are easy to control. Larger blocks are fine if one wants to sit down and review the whole thing, and also as a writer's-block-breaker. It's the folks generating whole codebases with no ability to review or debug that are in deep Monkey's Paw territory.
- GaggiX 2y agoLarger blocks are also perfect for scripts and tools for personal use, in this case you can just check if it works or not, Claude 3.5 Sonnet usually does not disappoint.
- rockemsockem 2y agoI tried copilot like 8 months ago for supercharged auto complete only, but I wasn't a fan because it was too high latency. I usually liked what it would write, but the second or so it took would really break my flow and had the overall effect of slowing me down. Makes me wonder if a local LLM could be superior here.
- kranner 2y agoIt seems to have gotten much faster recently so it might be worth another look. I also found it much slower while working on remote folders (with VS Code at least).
- rockemsockem 2y agoThat's good to know, the first time I tried it I was working on remote folders (just the way things are setup at work). Maybe I'll have to try it on my own computer and see.
- JTyQZSnP3cQGa8B 2y agoI try LLMs once a month with variations of the same question on a specific library that I use. It hallucinates all the time. I can't use those tools as long as they don't give me the answers I need.
- ggm 2y agoStill, the hype was to 10x and the incremental benefit is less, which means the capex won't return the hype value beyond the profit already made. Time to go back to predicting war and making huge profits on that game.
- rockemsockem 2y agoI'm really curious how much valuations, especially for big companies, have been based on things like "anyone can create a website with no technical knowledge", "programming will just be natural language in a few years", and "you are now the manager for an infinite number of junior developers". I think wall street is a bit smarter than that, but I'm not totally sure. I'm thinking that there are expectations of efficiency gains across a really broad range of tasks, i.e. programming, support, copy-editing, graphic design, etc, which will lead to significant increases in economic value. But it's impossible to know what the broad market is thinking, so IDK
- aurareturn 2y agoDoes the brain also do some sort of probabilistic prediction?
- ggm 2y agoIrrelevant because if the brain does it will be from a different model of reasoning and neuronal activity, which is not described or predicted by LLM.
- jsemrau 2y agoA fancy autocomplete is my Markov-chain-based Twitter bot I built in 2016.
- dboreham 2y agoSome day the penny will drop that this is what your brain is doing too.
- pizza 2y agoThere'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 https://x.com/colbertlateshow/status/691851573031505920
- Animats 2y agoIs 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-detection-for-llms/ https://www.kolena.com/blog/how-to-perform-hallucination-det... [2] https://www.nature.com/articles/s41586-024-07421-0 https://www.nature.com/articles/s41586-024-07421-0
- aurareturn 2y agoI 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.
- lolinder 2y agoThat we haven't yet seen the successor is why I'm suspicious we're leveling out. OpenAI teased their new model for months and willingly let the media assume it was GPT-5, then released it as 4o because it was faster and cheaper but no better. They intentionally burned a lot of the hype for GPT-5 on a different, less exciting product—that's not a move you make if you have a clear path towards the next generation.
- Animats 2y ago> That we haven't yet seen the successor is why I'm suspicious we're leveling out. Not clear if we're leveling out on what's possible, but price/performance may be increasing with model size. There's an economic limit. If the main way to fix hallucinations is to run the same query many times and look for consensus, that's going to be expensive.
- deleted 2y ago[deleted]
- ramshanker 2y agoAI 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 2y agoWall 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.
- lolinder 2y 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#GellMannAmnesiaEffect https://en.m.wikipedia.org/wiki/Michael_Crichton#GellMannAmn...
- slavboj 2y agoThe 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 2y agoWall 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 2y agoIt'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 2y agoNothing 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 2y agoAI 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