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Why OpenAI's $157B valuation misreads AI's future (Oct 2024)
- andrewmcwatters 2y agoOh! It's "Open"AI because there's no moat! /s
- alephnerd 2y agoGlad to finally see Ashu Garg's writings on HN.
- Stokley 2y agoWhether you love or hate OpenAI, the CapEx involved with this company will be viewed as historic in the future, and will change (has already changed) the paradigm of how tech startups/projects are funded
- manquer 2y agoI think it will have an adverse affect to funding ecosystem. The inevitable haircut all the funds are going to take in OpenAI and other AI startups when revenue fails to materialize[1] will herald a bust cycle and lot more circumspection in large investments like it happened few years back when a large number of Soft Bank investments did not pan out, notably most of them relied on big funding rounds to muscle out other players, not all of them have failed but all of them lost of enterprise value for investors. --- [1] This is inevitable regardless of success of the space, either because cost of inference keeps dropping in combination with competing with high quality open weight models as DeepSeek, Stable Diffusion and others have shown. It will have strong downward pressure on pricing impacting both revenue and profit.
- piva00 2y agoIt changed the paradigm negatively so far, it vacuumed so much money that anything non-AI is not getting much funding, it locked CapEx and now it's looking like there won't be a massive RoI for the capital spent. The AI hype might have as well setback a lot of other products that never got the necessary funding to get up from the ground, it's not looking pretty.
- dralley 2y agoA year ago Sam Altman was going around trying to convince people we all needed to drop 7 trillion dollars to build hundreds of fabs and nuclear power plants to fuel his AI ambitions. Only a week ago he was triumphantly announcing 500 billion dollar deals with our new President. The (regrettably temporary) ousting of Sam Altman looks like the right call, in hindsight. Of course some amount of showmanship is expected, but the extreme nature of this self-serving BS is just laughable. 6 months from now we may be looking at Sam Altman the way we look at Adam Neumann.
- anotherhue 2y agoReality can rarely compete with good showmanship. Weren't we discussing HyperNormalisation just yesterday?
- romanovcode 2y agoThe timing with the 500b deal is just perfect
- deegles 2y agoOr Elizabeth Holmes....
- Animats 2y agoLatest word from The Leader: "Even as some U.S. tech stocks plunged on Monday after it appeared that DeepSeek could produce similar results as rival models with a system that was cheaper to build, Trump projected confidence, calling it “very much a positive development.” He reasoned that American companies would be able to adapt and evolve based on DeepSeek’s demonstration that effective systems can be developed more easily than some assumed."
- trhway 2y ago> But while Facebook’s costs decreased as it scaled, OpenAI’s costs are growing in lockstep with its revenue, and sometimes faster And here comes DeepSeek and takes the steam out of this and the cost arguments that follow it.
- croes 2y agoUntil now we know only what the they claim what that costs are.
- trhway 2y agoWhat DS did is in line with my expectations as I see a lot of performance optimizations possible at algorithmic level. So, even if the DS numbers are BS somebody else will tomorrow reach and even beat it.
- diego_sandoval 2y agoInference costs can't be faked though, since the model can be run locally by anyone with capable hardware. Even if the whole story about the training cost was fake, R1 and the distilled models are still very efficient at inference.
- nextworddev 2y agounless OAI has all the optimization tricks already, which they probably do
- croes 2y agoThe shock for the industry was the claimed training costs and used hardware.
- creato 2y agoIs the model architecture actually that different from anything else? Or are you just saying that you can get away with smaller models now?
- deleted 2y ago[deleted]
- coldpepper 2y agoAI is still a fad.
- anothermathbozo 2y agoHow so?
- jack_pp 2y agoI'd write a script that crawls all these AI topics and use an LLM to count how many times this conversation has been had but I'm too tired to do so lol. Just don't feed the troll / dumb person. If they're too stupid to see how revolutionary LLMs are by this point.. just let them be stupid. Just downvote and move on with your life
- SlightlyLeftPad 2y agoWe’ll know when it can park a car in an everyday parking spot without messing up your Grandma’s Camry I suppose.
- handfuloflight 2y agoOh yeah, let's all wait till then to get the value out of models today.
- SlightlyLeftPad 2y agoI’m not saying it doesn’t have value, but it’s not worth my time to spend 20 minutes to prompt engineer a tool to write me a plagiarized document I could write myself in 20 minutes? Why would I invest my time into using a tool that undermines my own value? What’s the value prop for me?
- handfuloflight 2y agoYour inability to find value propositions and use cases is your issue.
- nextworddev 2y agoJust playing devil's advocate: VCs (esp those who missed out on OAI) are heavily incentivized to root for OAI to fail, and commoditize the biggest COGs item (AI models). This guy is just talking his book.
- krainboltgreene 2y agoThat doesn't make any sense. A lack of investment is not an investment against by any means, unless this VC invested in the concept of less spam or more workers.
- ALittleLight 2y agoVC's raise money from investors. Investors want to put their money with good VCs. If OpenAI is huge, and you missed it, that seems bad. If OpenAI flops and you strategically held off - that seems good.
- swyx 2y agowise man once said: "the devil doesnt need advocates, hell is full of them". you can both talk your book and also sincerely believe what you say. ad hominem (or whatever the latin equivalent is of ad bookinem) is not as substantive a criticism as you make it out to be. he can be both biased and correct.
- NhanH 2y agoAnd you can even turn the viewpoint around and say that he is putting his money where his mouth is.
- dralley 2y agoVCs with deep pocketbooks, their startups, and the hardware vendors they purchased from (not to mention politicians) are heavily incentivised to believe that their value-add can't be commoditized. If your grand dream is to dominate the market through sheer massive scale and that's what you're selling to capital, you're not exactly looking for reasons to buy less hardware and your vendor is hardly going to talk you out of it. "It's hard to get a man to understand something when his fat valuation depends on his not understanding it"
- tonyhart7 2y agoand microsoft literally spent 80 billions on top of its, like bro imagine 80 billions dollar company is like top 0,01 percent and that valuation would crumble because of deepseek
- coffeebeqn 2y agoWhat did they spend it on? I’m sure the next gen models will still be better to train on that new infra
- tonyhart7 2y agothat total investment (so far), I believe Microsoft has back deal as well with open ai outside series funding investment well since most of that money comeback anyway to MS since OAI use Azure heavily but it still a lot of money and stock value of OAI would tank sooner or later when competitor like deepseek come
- halfcat 2y agoIt’s the year 2000. We have the internet, a technology that will change the world. Yahoo is the most valuable company on earth. Among the coolest things people do is go to CompUSA and pay money for a web browser, Netscape Navigator, because it supports the <blink> tag so you can make your geocities page even more awesome. Google is still operating out of a garage somewhere, and won’t be household name until after the bubble bursts. That’s where we are in the AI journey in 2025. The year 2000.
- great_psy 2y agoBefore or after the bubble popped ?
- meiraleal 2y agoDuring
- krainboltgreene 2y agoEveryone thinks their bet is the next Ford, Wright bros, Netscape, etc.
- blackeyeblitzar 2y agoPeople are announcing the death of foundational models too early. Don’t people realize that the big AI players will take all of the proprietary things they’ve been building up behind closed doors and simply layer onto them all the winning techniques everyone else is publishing (like what DeepSeek has used)? DeepSeek itself is taking ideas that have proven out in various other papers and stacking them up to produce their gains (which they’ve been transparent about in their papers). I also still don’t believe their cost figures, and think they’re leaving out the capital to acquire their secret GPU stash and the cost of pre training their base model (DeepSeek-V3-base). I also suspect their training corpus, which they’ve only vaguely described, would reveal the savings came from working off other foundational models’ work without counting those costs in their figure. For now, I treat the cost claim as simply a calculated strategy for China to not look like they’re behind in the most important race, to prevent investors from continuing to boost US technology by causing them to doubt the ROI, and to take value out of the US stock market as they did today.
- bambax 2y agoYeah, the cost figures need more scrutiny; they started with Llama3 which they got for free; had they had to build it from scratch it would have cost more than $6M. But as for your first paragraph: even if the "big AI players" have some secret sauce that will make their products better (and that they can actually keep secret), it seems unlikely it would be enough to command higher prices durably. A model would have to be incredibly superior to justify paying for it, when there are so many free (or dirt cheap) alternatives that are simply good enough.
- blackeyeblitzar 2y agoYou make a good point, that maybe the models won’t perform much better with those improvements, or at least not enough to get people to pay more. I’m curious about the Llama3 bit - do you have a source for that? I’ve been hearing they trained using OpenAI outputs (not sure how that would work).
- Palmik 2y agoI don't know where you're getting your information from. Maybe you're confusing DeepSeek v3/r1 and the distilled r1 models. DeepSeek V3/R1 architecture isn't anything like Llama 3. Llama 3 isn't even a mixture of experts, not to mention the various other differences like attention compression etc
- elijahbenizzy 2y agoWe’ve just learned that it’s possible to do AI on less compute (deepseek). if OpenAI doesn’t scale and that’s the problem then I’d argue that in the long run, if you believe in their ability to do research, then the news this week is a very bullish sign. IMO the equivalent of moores law for AI (both on software and hardware development) is baked into the price, which doesn’t make the valuation all too crazy.
- SlightlyLeftPad 2y agoHonestly, I’m not sure I’m completely sold on the value of LLMs long term but this is the most realistic and reasonable take I’ve read on this post so far. If anything, it’s an downward adjustment in the cost implications but could actually unlock exponential improvements on a shorter time horizon than expected because of that. Investors getting scared probably is a good opportunity to buy in.
- markvdb 2y agoBullish on the use. Bearish on the profit margins for the big players. If (big if!) I understand correctly, the ceiling for edge/local/offline AI has just blown off.
- benatkin 2y agoIs there an acronym for edge/local/offline? ELO could be confused with something AI already dominates at. As someone working in the edge/local/offline space it’s interesting to hear these together though. Offline is local but local often isn’t offline :)
- kleene_op 2y agoBullish on the prospects for small players, then.
- deleted 2y ago[deleted]
- refulgentis 2y ago
- stego-tech 2y agoA pretty good read that succinctly picks apart the realities of current AI businesses. Easily something I’d reference as a “primer” to someone that is more business-minded than technically-minded. One point I’ll agree on is his final one: that the true big players haven’t even been founded yet. Right now, the AI hype seems to still revolve around the dream of replacing humans with machines and still magically making Capitalism work in the process, which is something I (and other “contrarians”) have beaten to death in other threads. That said, what these companies have managed to demonstrate is that transformer-based predictive models are a part of the future - just not AGI. If I were a VC, I’d be looking at startups that take the same training techniques but apply them in niche fields with higher success rates than general models. An example might be a firm that puts in the grunt work of training a foundational model in a specific realm of medicine, and then makes it easier for a hospital network to run said model locally against patient data while also continuously training and fine-tuning the underlying model. I wouldn’t want to get into the muck of SaaS in these cases, because data sovereignty is only going to become an ever-thornier issue in the coming decades, and these prediction models can leak user data like a sieve if not implemented correctly. Same goes for other narrow applications, like single-mode logistics networks or on-site hospitality interfaces. The real money will be in the ability to run foundational models against your own data in privacy and security, with inference at the edge or on-device rather than off in a hyperscaler datacenter somewhere. Then again, I could be totally wrong. Guess we’ll all find out together.
- deleted 2y ago[deleted]
- broken_clock 2y agoAren't there already a ton of startups doing finetunes for their local niche? Many aren't even "AI" companies - it's pretty easy to slap a finetune together if you enough data. If you mean developing a model from scratch just for your niche - the bitter lesson is that scale is everything and that a finetune from an internet-scale model will outperform you easily.
- coffeebeqn 2y ago
- tempeler 2y agoPricing is the betting or wishing in the valuation. The buyer thinks it will increase; the seller thinks it's enough. No one knows what will happen in the future. Maybe the Fed will print too much money. Does anyone know what will happen in the future?
- refulgentis 2y agoFor about a month now I've been paying $20-$30/day to delegate the bulk of my coding to Sonnet. The agentic loop thats trained into it is just simply not matched by another other model. I can't admit to myself there's any open question as to if there is any long-term value. I expect within 2 years, this will seem like a non-controversial idea, and it won't bring in a ton of assumptions about the speaker. I have invested much time and effort making sure local models are a peer to remote ones in my app, and none, including DeepSeek's local models, are remotely close to the things needed to make that flow work. EDIT: Reply-throttled, so answering replies here: - The machine is building the machine: Telosnex, a cross-platform Flutter app - it can do 90% of the scope, especially after I wrote precanned instructions for doing e.g. property-based testing. - Things it's done mostly wholesale: -- secure iframe environment, on all 6 platforms, to: execute JS in, or render react components it wrote. -- completely refactoring my llama.cpp inference to use non-deprecated APIs. - Codebase is about 40K real lines of code. (I have to think this helps a lot I doubt that ex. from scratch it would be able to build a Flutter app that used llama.cpp.) - $30/day!?! -- Yeah, it's crazy, its up an order of magnitude from my most busy days when I just copy-pasted back and forth. It reads as much code as it wants, and you're doing more work literally, so it adds up. - $20/day is realistic average - Lines added per day +55%, lines deleted per day +29%, files changed per day 9 -> 21 https://x.com/jpohhhh/status/1881453489852948561 https://x.com/jpohhhh/status/1881453489852948561
- broken_clock 2y agoWhat tools are you using to delegate?
- refulgentis 2y agoMy own app, it's called Telosnex. Unfortunately, the current available version doesn't have the agent stuff yet. Hopefully in a week, realistically two. I had the existing client app I've released-but-not-released-out-loud. Couple days before Christmas, for fun, I spent a couple hours wiring up the Anthropic Model Context Protocol filesystem server example. Within an hour it was clear this was special and I needed to get it out ASAP. Stunning stuff in action.
- poorcedural 2y agoWhy do we not value QBASIC in billions? Honestly, we value current Van Gogh paintings in billions. The past cost us more, we got here because of that art fought through decades of litigation. Does progress mean we forget all of that and hope on a promise of easy answers?
- danaris 2y agoScarcity. Van Goghs have it; QBASIC doesn't. Anyone can download QBASIC for free.
- a13n 2y ago> I’d argue that the most valuable companies of the AI era don’t exist yet. They’ll be the startups that harness AI’s potential to solve specific, costly problems across our economy—from engineering and finance to healthcare, logistics, legal, marketing, sales, and more. I feel like the author's concluding point contradicts himself. There is a gold rush and OpenAI is selling shovels.
- wukerplank 2y agoI thought Nvidia is selling shovels
- nyc_data_geek1 2y agoNvidia is selling shovels. OpenAI is renting out mining crews
- sdenton4 2y agoMickey Mouse animated the shovels with the big spell book, and now they're marching around and need shovels of their own...
- benatkin 2y agoThis has me imagining it in terms of the game Cuphead. That’s also good for visualizing this I think.
- Liwink 2y ago> OpenAI is selling shovels. I think the author argues that OpenAI is not the only one selling shovels, and their shovels won't be always better that others'.
- tyre 2y agoIt's that OpenAI is investing tens of billions of dollars in shovels and others, like deepseek, are open sourcing equivalently good shovels. The vertical specific companies, though, are harder to clone as the invest in the product offering around/on top of AI
- mbowcut2 2y agoDeepSeek has demonstrated that there is no technical moat. Model training costs are plummeting, and the margins for APIs will just get slimmer. Plus model capabilities are plateauing. Once model improvement slows down enough, seems to me like the battle is to be fought in the application layer. Whoever can make the killer app will capture the market.
- keithwhor 2y agoSomething worth noting is that ChatGPT currently is the killer app -- DeepSeek's current chart-topping app notwithstanding (not clear if viral blip or long-term trend).
- tarsinge 2y agoFor me ChatGPT was not that useful for work, the killer app was Cursor. It’ll be similar for other industries, it needs to be integrated directly in core business apps.
- ern 2y agoChatGPT Plus gives me a limited number of o1 calls and o1 doesn't have web access, so I mostly have been using 4o in the last month and supplementing it with DeepSeek in the last week, for when I need advanced reasoning (with web search in DeepSeek as a bonus). The killer app had better start giving better value, or I'd gladly pay the same amount of DeepSeek for unlimited access if they decided to charge.
- LZ_Khan 2y agoYou can't be a killer app if your competitor is just as good and free.
- saati 2y agoKiller app for what platform?
- mirzap 2y agoModel capabilities are not plateauing; in fact, they are improving exponentially. I believe people struggle to grasp how AI works and how it differs from other technologies we invented. Our brains tend to think linearly; that's why we see AI as an "app." With AI (ASI), everything accelerates. There will be no concept of an "app" in ASI world.
- ripped_britches 2y agoWhat a great take, I have thought this for a while.
- Mr_Blacky 2y ago[flagged]
- openrisk 2y ago"Linux ultimately prevailed-not because it was better from the start, but because it allowed developers to modify the code freely, run it more securely and affordably, and build a broader ecosystem that enabled more capabilities than any closed system" Deepseek followed llama and will be followed by others in the usual mushroom fashion of open source. People really dont appreciate the magnitude of the disruptive force that is unleashed by the open source paradigm. In a year from now the landscape will be brimming with new initiatives. In a few years nobody will even remember "open"ai. Conventional economic theory will always misread the future of computing (and thus "AI"). The zero marginal cost and infinite replicability is not a bug, its a feature. But so far we dont really have a good model how to think about it and merge it with mainstream business models. Something must pay the bills eventually but these are very different bills from those of conventional scarcity based businesses. Ironically in the end the main scarcity is human ingenuity. Read the interview of the Deepseek founder on why their models are open source.
- hx8 2y agoWith current generation AI we really need AI + Humans to have good results. It seems likely that the entire LLM branch of products will have this limitation. If that's the case let's race to make the best open source AI as fast as possible, so it can be spread as wide as possible and can be used to fix our shared problems. It's the spreading widely that will lead to breakout results in fields such a cancer research just as much as having the most intelligent system, because humans bring some X factor for creativity/ingenuity/novelty.
- Jasondells 2y agoThe OpenAI vs. DeepSeek debate is fascinating... but I think people are oversimplifying both the challenges and the opportunities here. First, OpenAI’s valuation is a bit wild—$157B on 13.5x forward revenue? That’s Meta/Facebook-level multiples at IPO, and OpenAI’s economics don’t scale the same way. Generative AI costs grow with usage, and compute isn’t getting cheaper fast enough to balance that out. Throw in the $6B+ infrastructure spend for 2025, and yeah, there’s a lot of financial risk. But that said... their growth is still insane. $300M monthly revenue by late 2023? That’s the kind of user adoption that others dream about, even if the profits aren’t there yet. Now, the “no moat” argument... sure, DeepSeek showed us what’s possible on a budget, but let’s not pretend OpenAI is standing still. These open-source innovations (DeepSeek included) still build on years of foundational work by OpenAI, Google, and Meta. And while open models are narrowing the gap, it’s the ecosystem that wins long-term. Think Linux vs. proprietary Unix. OpenAI is like Microsoft here—if they play it right, they don’t need to have the best models; they need to be the default toolset for businesses and developers. (Also, let’s not forget how hard it is to maintain consistency and reliability at OpenAI’s scale—DeepSeek isn’t running 10M paying users yet.) That said... I get the doubts. If your competitors can offer “good enough” models for free or dirt cheap, how do you justify charging $44/month (or whatever)? The killer app for AI might not even look like ChatGPT—Cursor, for example, has been far more useful for me at work. OpenAI needs to think beyond just being a platform or consumer product and figure out how to integrate AI into industry workflows in a way that really adds value. Otherwise, someone else will take that pie. One thing OpenAI could do better? Focus on edge AI or lightweight models. DeepSeek already showed us that efficient, local models can challenge the hyperscaler approach. Why not explore something like “ChatGPT Lite” for mobile devices or edge environments? This could open new markets, especially in areas where high latency or data privacy is a concern. Finally... the open-source thing. OpenAI’s “open” branding feels increasingly ironic, and it’s creating a trust gap. What if they flipped the script and started contributing more to the open-source ecosystem? It might look counterintuitive, but being seen as a collaborator could soften some of the backlash and even boost adoption indirectly. OpenAI is still the frontrunner, but the path ahead isn’t clear-cut. They need to address their cost structure, competition from open models, and what comes after ChatGPT. If they don’t adapt quickly, they risk becoming Yahoo in a Google world. But if they pivot smartly—edge AI, better B2B integrations, maybe even some open-source goodwill—they still have the potential to lead this space.