AI's $600B Question

https://www.sequoiacap.com/article/ais-600b-question/

by fh973 • 2 years ago

397 533 2 years ago

jfghi• 2 years ago

Reminds me of the gnomes from South Park.

threeseed7• 2 years ago

Founders and company builders will continue to build in AI—and they will be more likely to succeed, because they will benefit both from lower costs and from learnings accrued during this period of experimentation

Highly debatable.

When we look back during the internet and mobile waves it is overwhelmingly the companies that came in after the hype cycle had died that have been enduring.

malfist2• 2 years ago

Let's see: Microsoft Windows: wasn't close to the first OS

Microsoft Office: wasn't close to the first office editing suite

Google: Wasn't close to the first search engine

Facebook: Wasn't close to the first social media website

Apple: ~~First "smart phone"~~ but not the first personal computer. Comments reminded me that it wasn't the first smartphone

Netflix: Wasn't close to the first video rental service.

Amazon: Wasn't close to the first web store

None of the big five were first in their dominate categories. They were first to offer some gimmick (i.e., google was fast, netflix was by mail, no late fees), but not first categorically.

Though they certainly did benefit from learnings of those that came before them.

AlexandrB2• 2 years ago

Apple: First "smart phone" but not the first personal computer

Was it the first smartphone? I would call phones like the Palm Treo and later BlackBerries smartphones. There were even apps, but everything was lot more locked down and a lot more expensive.

robbiemitchell• 2 years ago

some gimmick

"key differentiator" and not necessarily easy to pull off or pay for

olalonde• 2 years ago

I have a pet peeve with this common piece of wisdom. You can always find a "predecessor" for about anything. The corollary being that there is never a "first". And therefore, stating that "none of the big companies were the first in their categories" is just stating a tautology.

edanm• 2 years ago

i.e., google was fast,

Just to quibble with this - that was not even close to the reason Google got popular. It was because Google was much, much better at finding what you actually wanted. It was just a far better product.

You can debate why this is exactly, Joel Spolsky pointed out many years ago that it was because Google got that what matters to users most isn't "finding all pages related to X" but rather "ranking" those pages, a take I agree with.

jjtheblunt• 2 years ago

“Pioneers get the arrows, and settlers get the land”?

chrisweekly• 2 years ago

"The early bird gets the worm -- but the second mouse gets the cheese."

malshe• 2 years ago

There is an old study that supports your point. The abstract reads:

"Several studies have shown that pioneers have long-lived market share advantages and are likely to be market leaders in their product categories. However, that research has potential limitations: the reliance on a few established databases, the exclusion of nonsurvivors, and the use of single-informant self-reports for data collection. The authors of this study use an alternate method, historical analysis, to avoid these limitations. Approximately 500 brands in 50 product categories are analyzed. The results show that almost half of market pioneers fail and their mean market share is much lower than that found in other studies. Also, early market leaders have much greater long-term success and enter an average of 13 years after pioneers."

PDF available here:

https://people.duke.edu/~moorman/Marketing-Strategy-Seminar-...

dmix7• 2 years ago

Yes the "first mover advantage" is mostly just a common myth in business that refuses to die, but if we look at the original statement:

Founders and company builders will continue to build in AI—and they will be more likely to succeed, because they will benefit both from lower costs and from learnings accrued during this period of experimentation

This still lines up with the 2nd wave benefiting more. The first movers helped established the large scale AI hardware industry, got a bunch of smart kids trained on how to make AI, a bunch of people will fail and learn, etc and this experimentation stage sets the groundwork for OpenAI 2.0.

We could very well just in the Altavista vs Yahoo days of AI and an upstart takes over in 5yrs.

mupuff1234• 2 years ago

I expect this will lead to a final surge in demand for NVDA chips

But other than FOMO why would someone buy better chips when they don't actually know what to do with their old ones?

alecco2• 2 years ago

H100s are in very high demand and usually running work 24/7. So much that the energy cost is a big factor. The B100 halves the energy costs, among many other things.

technotony• 2 years ago

If they are in such high demand, then are they just being priced below cost? why else is the capex so much higher than the revenues? These things must depreciate over only 3-5 years (or less?)

neaanopri• 2 years ago

This seems about as bearish as a VC is allowed to be. My takeaway is:

Sell! Sell! Sell now before it's too late!

beejiu• 2 years ago

It interests me that the $200-600 billion number seems to be all-derived from GPUs. Are LLMs/AIs totally dependent on GPUs? I read last week (https://news.ycombinator.com/item?id=40787349) that there is research ongoing to run LLMs on FPGAs at greater energy efficiency.

I'm reminded of Bitcoin/crpyto, which in its early history was all operated on GPUs. And, then, almost overnight, the whole thing was run on ASICs.

Is there an intrinsic reason something similar couldn't happen with LLMs? If so, the idea of a bubble seems even more concerning.

cma2• 2 years ago

Nvidia and AMD bought out the big FPGA makers.

jamessinghal2• 2 years ago

AMD bought Xilinx, but Intel recently spun off Altera.

sason• 2 years ago

There is a fairly new ASIC named "Sohu" that is purpose-built for transformers. They have some bold claims that are impressive if true.

I found a short discussion[2] you may find useful.

[1] https://www.etched.com/

[2] https://www.lesswrong.com/posts/qhpB9NjcCHjdNDsMG/new-fast-t...

cmcclellan• 2 years ago

This is just a PowerPoint slide at this point.

wmf4• 2 years ago

These numbers are just the hole from GPUs that have already been bought/ordered. Today's GPUs will inevitably be replaced by something, whether it be better GPUs, NPUs/TPUs, ASICs, or FPGAs. As chips get cheaper in the future the hole will grow at a slower rate but it only grows.

pixl973• 2 years ago

Is there an intrinsic reason something similar couldn't happen with LLMs?

Only if we can increase the efficiency of LLMs by 2-3 orders of magnitude, there are only some in lab examples of this and nothing really being publicly shown.

Even then the models are still going to require rather large amounts of memory, and any performance increases that could boost model efficiency would very likely increase performance on GPU hardware to the point we could get continuous learning models from multimodal input like video data and other sensors.

light_hue_12• 2 years ago

There is a reason why we don't use ASICs and instead use GPUs.

While people may say something is a Transformer that's more of a general description. It's not a specific algorithm; there are countless transformers and people are making progress on finding new ones.

Bitcoin runs a specific algorithm that never changes. That's for an ASIC. AI/ML runs a large class of models. GPUs are already finely tuned for his case.

ryandrake8• 2 years ago

Others are saying this article is bearish, but then...

A huge amount of economic value is going to be created by AI. Company builders focused on delivering value to end users will be rewarded handsomely.

Such strong speculative predictions about the future, with no evidence. How can anyone be so certain about this? Do they have some kind of crystal ball? Later in the article they even admit that this is another one of tech's all-too-familiar "Speculative frenzies."

The whole AI thing just continues to baffle me. It's like everyone is in the same trance and simply assuming and chanting over and over that This Will Change Everything, just like previous technology hype cycles were surely going to Change Everything. I mean, we're seeing huge companies' entire product strategies changing overnight because We Must All Believe.

How can anyone speak definitively about what AI will do at this stage of the cycle?

glitchc4• 2 years ago

Whenever I hear the AI hype cycle, I'm always reminded of expert systems and how they were going to revolutionize the world.

awahab92• 2 years ago

there were probably people who doubted electricity, vaccines and indoor plumbing.

llm_trw7• 2 years ago

You should also be reminded about the internet. After the dotcom bubble it was extremely common to hear it outright dismissed as never being useful for anything.

Sometimes the future just gets here before we're ready for it.

cjbgkagh• 2 years ago

This really is different, and I say that as someone who spent a lot of time on expert systems, not as someone who is overly bought into AI hype.

The problem with expert systems is that even if the tooling was perfect the people using them needed a rather nuanced and sophisticated understanding of ontologies. That just wasn’t going to happen. There is not enough of that kind of expertise to go around. Efforts to train people largely failed. I think the intentional undermining of developer salaries pushed a lot of smart people out of the software industry making the problem even worse.

That’s what makes AI special, the ability to deliver value even when used by unsophisticated operators. Many workflows can largely stay the same and AI can be sprinkled in where it makes the most sense. I use it for documentation writing and UI asset production and it’s better in that role than the people I used to pay.

stale20023• 2 years ago

Such strong speculative predictions about the future, with no evidence. How can anyone be so certain about this?

The evidence is all around you. For anyone who has made any serious attempt to add AI to your current life and work process, you will fairly quickly notice that your productivity has doubled.

Now, do I as a random software engineer who is now producing higher quality code, twice as fast, know how to personally capture that value with a company? No. But the value is out there, for someone to capture.

It's like everyone is in the same trance and simply assuming and repeating over and over that This Will Change Everything

It already is changing everything, in multiple fields. Go look up what happened to the online art commission market. It got obliterated over a year ago and is replaced by people getting images from midjourney/ect.

Furthermore, if you are a software engineer and you haven't included tools like github copilot, or cursor AI into your workflow yet, I simply don't consider you to be a serious engineer anymore. You've fallen behind.

And these facts are almost immediately obvious to anyone who has been paying attention in the startup space, at least.

GenerocUsername2• 2 years ago

Ive added "how have you incorperated generative AI into your workflow" as an interview question, and I dont know if it is stigma or actual low adoption, but I have not had a single enthusiastic response across 10+ interviews for senior engineer positions.

Meanwhile, I have chatGPT open in background and go from unaware to informed for every new keyword I hear around me all day everyday. Not to mention annotating code, generating utlity functions, and tracing errors

choeger2• 2 years ago

Furthermore, if you are a software engineer and you haven't included tools like github copilot, or cursor AI into your workflow yet, I simply don't consider you to be a serious engineer anymore. You've fallen behind.

That sounds like you're fresh out of college. Copilot is great at scaffolding but doesn't do shit for bug fixing, design, or maintenance. How much scaffolding do you think a senior engineer does per week?

beambot2• 2 years ago

Very true! From where I sit, most of the hype cycles were overestimated in the short term & underestimated in the long term: world wide web, mobile, big data, autonomous cars, AI, quantum, biotech, fintech, clean tech, space and even crypto.

rty32• 2 years ago

Twice as fast is way over exaggerating the reality. In certain cases, sure, but more generally you are looking at 10%-50% productivity increase, more likely on the lower end. I say this as someone who has access to ChatGPT and AI code completion tools and use them every day, and the numbers are backed up by Google's study. https://research.google/blog/ai-in-software-engineering-at-g...

americanvirtual• 2 years ago

Yeah some expert I work in the field type YouTubers I remember well over 7 months ago now kept saying that we're going to have AGI within 7 months. He was like the big prediction hinging practically his whole channel on... Sorry I don't have the name but there's a little anecdote.

simonw2• 2 years ago

If, like me, you're using LLMs on a daily basis and getting real personal value out of them, it's hard not to conclude that they're going to have a big impact.

I don't need a crystal ball for this. The impact is already evident for us early-adopters, it's just not evenly distributed yet.

That's not to say they're not OVER hyped - changing the entire company roadmap doesn't feel like a sensible path to me for most companies.

ryandrake8• 2 years ago

Early Adopters are always True Believers. That's why they are early adopters. Every single one of them is going to say "The impact is clear! Look around you! I use XYZ every day!" You really don't know what the adoption curve will look like until you get into the Late Majority.

TeMPOraL35• 2 years ago

How can anyone not see just how impactful it's going to be? Or already is? I can't think of a single recent technology that was so widely adopted by tech and non-tech people alike, immediately integrated into day-to-day experience. The rise of mobile phones and e-commerce in the 90s would be the last time I've seen this happen (I'm not counting smartphones, as those are more of an iteration). Or social media, in purely software space.

I've just had GPT-4o write me a full-featured 2048 clone in ~6 hours of casual chat, in between of work, making dinner, and playing with kids; it cost me some $4 in OpenAI bills, and I didn't write a single line of code. I see non-tech people around me using ChatGPT for anything from comparison shopping to recipe adjustments. One person recently said to me that their dietitian is afraid for their career prospects because ChatGPT is already doing this job better than she is. This is a small fraction of cases in my family&friends circle; anyone who hasn't lived under the rock, or wasn't blinded by the memetic equivalent of looking at a nuclear weapon detonation, likely has a lot of similar things to say. And all of that is not will, it's is, right now.

ryandrake8• 2 years ago

How can anyone not see just how impactful it's going to be? Or already is? I can't think of a single recent technology that was so widely adopted by tech and non-tech people alike, immediately integrated into day-to-day experience. The rise of mobile phones and e-commerce in the 90s would be the last time I've seen this happen (I'm not counting smartphones, as those are more of an iteration). Or social media, in purely software space.

You can't know this for certain until you look back on it in retrospect. We did not know mobile phones and e-commerce were going to be huge back in the 90s. We know now, of course, looking back, and the ones who guessed right back then can pat themselves on the back now.

Everyone is guessing. I'll admit it's totally possible LLMs and AI are going to be as earth shattering as its boosters claim it will be, but nobody can know this now with as much certainty as is being written.

maxlamb• 2 years ago

What’s a 2048 clone?

saulpw• 2 years ago

I canceled my GPT-4 subscription recently because it just wasn't that impactful for me. I found myself using it less and less, especially for things that matter (because I can't trust the results). The things it's good at: boilerplate text, lightweight trivia, some remixing/brainstorming. Oh and "write me a clone". Yes, it can write clones of things, because it's already seen them. I've spent WAY more time trying to get anything useful out of it for a non-clone project, than it took me when I just buckled down and did it.

Yes, "many things are clones", but that just speaks to how uncreative we are all being. A 2048 clone, seriously? It was a mildly interesting game for about 3 minutes in 2014, and it only took the original author a weekend to build in the first place. Like how was that impactful that you were able to make another one yourself for $4?

PaulHoule2• 2 years ago

One difference between AI and mobile is this.

The mobile revolution needs three kinds of investment:

(A) The carrier has to build out a network

(B) You need to buy a handset

The returns that anybody gets from investing in A, B or C depend on the investments that other people have made. For instance, why should I buy a handset if the network and the apps aren't there? Why should a business develop an app if the network and users aren't there? These concerns suppress the growth of mobile phones in the early phase.

ChatCPT depends on the existing network and existing clients for delivery so ChatGPT can make 100% of the investment required to bring their product to market which means they can avoid the two decades of waiting for the network and handsets to be there in order to motivate (C).

---

Note another thing that younger people might never have noticed was that the US was far behind the rest of the world in mobile adoption from maybe 1990 to 2005. When I changed apartments in the US in the 1990s I could get landline service turned on almost immediately by picking up the phone. When I was in Germany later I had no idea I could go into a store in most countries other than the US and walk out with a "handy" and be talking right away so I ended up waiting a month for DT to hook up my phone line.

meiraleal• 2 years ago

I've just had GPT-4o write me a full-featured 2048 clone in ~6 hours of casual chat

Honestly I'm totally in the AI camp but 6 hours to make a 2048 clone?! And that's a good result? Come on.

lend000• 2 years ago

GPT-4 is an upgrade over a search engine (on the 2010 internet, which was much easier to search than the internet today) and there is certainly opportunity in using it to chain together complex programming tasks fully programmatically, but we are stuck right on the cliff of a truly reliable and generalizable AI, and it isn't clear that we can just train an AI with the next generation of GPU's and more data and bridge that gap. Most of the truly high value add activities (fully autonomous programs and AGI that creates novel inventions) rely on a model more intelligent and more consistent than the current state of the art. So I think most of the valuation is in speculative potential.

madeofpalk2• 2 years ago

I think it’s reasonably obvious that the tech could have a lot of potential, but that’s yet to be realised. Chatbot interfaces are so primitive and clearly not the final form for LLMs, but people have to invent that.

But, tech being impactful doesn’t mean it will create and deliver value for others.

cfeduke• 2 years ago

Okay I guess I've just had a different experience entirely. Maybe I'm jaded by hallucinations.

The code ChatGPT generates is often bad in ways that are hard to detect. If you are not an experienced software engineer, the defects could be impossible to detect, until you/ChatGPT has gone and exposed all your customers to bad actors, or crash at runtime, or do something terribly incorrect.

As far as other thought work goes, I am not consulting ChatGPT over, say, a dietician or a doctor. The hallucination risk is too high. Producing an answer is the not the same as producing a correct answer.

woodruffw4• 2 years ago

I don't think the uptake of LLMs by non-technical people has been that dramatic. Nobody in my familial or social circles (which spans doctors, lawyers, artists, waitresses, etc.) has really mentioned them outside of asking my what I think about them.

As for what I think about them: I've been impressed with some aspects of code generation, but nothing else has really "wowed" me. Prose written with the various GPT models has an insincere quality that's impossible to overlook; AI-generated art tends to look glossy and overproduced in the same way that makes CGI-heavy movies hard to watch. I have not found that my Google Search experience was made better by their AI experiments; it made it harder, not easier, for me to find things.

pavel_lishin2• 2 years ago

I've just had GPT-4o write me a full-featured 2048 clone in ~6 hours of casual chat

May we see it?

grumbel• 2 years ago

Just because it's impactful doesn't mean it's going to make much money. Take audiobooks for example, the market is valued at around $5 billion. In the very near future audiobooks will be created with AI. Does that mean anybody is making billions with those AI audiobooks? I don't think so. The value of audiobook will go towards $0 and audiobooks as a product category will completely disappear. Audiobooks will simply be the text2speech feature of your eBook reader.

Similar stuff will happen with a lot of other content, things that used to be costly will become very cheap. And then what? The amount of books people can consume doesn't scale into infinity. Their entertainment needs will be served by auto-generated AI content. Even the books themselves will be written by AI sooner or later.

Advertising industry might also start hurting badly, as while they will certainly try getting ads into AI content, users will have AI at home to filter it out. A lot of classic tricks and dark pattern to manipulate the user behavior will no longer work, since the user has a little AI helper to protect them from those tricks.

I don't doubt that the impact of AI will be gigantic, but a lot of AI produced content won't be worth anything, since it's so easy to create for everybody. And there isn't much of a moat either, since new models with better capabilities pop up all the time from different companies. Classic lock-in is also not really usable anymore, as AI can effortlessly translate between different APIs and user-interfaces.

bamboozled5• 2 years ago

I've just had GPT-4o write me a full-featured 2048 clone in ~6 hours of casual chat, in between of work, making dinner, and playing with kids;

As cool as this might be, what is the actual economic value of this? 2048 is free, you didn't even have to spend a dollar to get it.

tempusalaria2• 2 years ago

Being able to create 2048 in 6 hours has basically zero economic value.

Can ChatGPT materially and positively impact the code written by big companies? Can it do meaningful work in excel? Can it do meaningful PowerPoint work? Can it give effective advice on management?

Right now we don’t know the answer to those questions. LLM apps can still improve in many ways - better base models, better integration with common enterprise applications, agentic processes, verifiability and so on - so there is definitely hope that there will be significant value created. Companies and people are excited because there’s huge potential. But it is really just potential right now … current systems aren’t creating real enterprise value at this moment in time

elicksaur2• 2 years ago

I can't think of a single recent technology that was so widely adopted by tech and non-tech people alike, immediately integrated into day-to-day experience.

This is not meant to be an offense, but you are in a bubble. The vast, vast majority of people do not use LLMs in their day-to-day life. That’s ok, we’re all in our own bubbles.

You should also post the 2048 clone as proof. Lots people saying they built X in Y minutes with AI. But, when it’s inspected, it’s revealed it very obviously doesn’t work right and needs more development.

epolanski2• 2 years ago

Meanwhile I have the opposite experience.

I have used chatgpt less and less, and bar copilot which is a useful autocomplete I just don't have much use for AI.

I know I'm not alone, and even though I've seen many people super excited by Dall-E first and chatgpt later they use very rarely both of them.

roenxi• 2 years ago

And we seem to be in an exponential upswing of hardware capacity, so we expect extreme improvements from an already impressive base. >90% of the compute that can be used to train models doesn't exist yet.

somesortofthing3• 2 years ago

I can't think of a single recent technology that was so widely adopted by tech and non-tech people alike, immediately integrated into day-to-day experience.

I've heard this asserted sometimes, and I just don't think it's true. ChatGPT's use cases as consumer software were discovered basically immediately after GPT 3 came out, and nothing new has really emerged since then. It's great for automating high school/undergrad B-quality writing and the occasional administrative email. Beyond that, it sometimes does better than 2024 Google(though probably still worse than 2019 Google) on knowledge questions.

ChatGPT is software. The barrier to entry is almost zero, and the tech industry has had decades of practice in enticing people into walled gardens and making sure they can never leave. If it's not completely taken over the world in the time it's had, I wouldn't bet on it doing so without a massive jump in capability or accuracy.

jmartin2683• 2 years ago

This is the type of thing that I’ve only ever read about on the internet and have never heard of a normal person actually doing.

mvdtnz• 2 years ago

I see non-tech people around me using ChatGPT for anything from comparison shopping to recipe adjustments.

This is baffling to me, because these are two use cases I have tried and in which ChatGPT completely fails to produce any useful information.

kortilla8• 2 years ago

No offense, but you’re group is just very early on the adoption curve and is not representative of at all.

I have a bunch of peers that haven’t used chatgpt at all and they are software developers. A bunch more tried it once, realized how terrible it was for anything you aren’t already knowledgeable in and then haven’t gone back to it.

Recipe adjustments has to be a joke unless they are really basic things like “cut it in half”. ChatGPT is terrible at changing recipes without fundamentally changing them and will offer multiple “substitutions” for an ingredient that have extremely different outcomes that it doesn’t warn or know about.

prng2021• 2 years ago

The article explains a $600B gap in AI revenue expectations vs actuals. Rather than addressing that, you're posting about some dietician you know who worries their job will get replaced, as if it has any relevance whatsoever to the big picture.

We should have seen massive revenue growth and raises in future quarter revenue forecasts in the most recent round of SaaS company earnings reports. I think tons of companies have hyped up AI as if it's just on the cusp of AGI. The lack of massive top line growth has proven we're not even close, but the enormous investor speculation these companies triggered is the main reason for this $600B gap.

I'm not at all saying AI won't be transformational because it definitely does bring revolutionary capabilities that weren't possible before.

dimgl• 2 years ago

I actually don't think it's going to be that impactful. It often gets everything wrong. Today I asked ChatGPT questions about a game I used to play. It got it all wrong. I've recently asked questions about coding. A majority of it is also wrong. I've tried using it in a professional setting and it's also hit or miss.

I'm not saying AI is useless but it's certainly not the panacea that some say it is.

chillfox2• 2 years ago

I think that comes down to the kind of people you hang out with.

While I use AI quite often, none of my friends or family does. A few of them will use an image gen once or twice a year. And at work, only a few of my colleagues use AI.

So my impression is that current gen AI is too hard to use correctly, has too many rough edges and is not useful enough for most people.

Progress also seems to have stalled around the GPT-4 quality. Everything after GPT-4 (GPT-4 Turbo, GPT-4o, Claude 3 Opus, Claude 3.5 Sonnet) seems to be pretty much producing the same quality output, I have been using Open WebUI to bounce around between the different models and I can't really tell a difference in the quality of them, they are all roughly the same for my use case (programming/sysadmin stuff).

So the question of if a plateau has been hit or if scale can still improve quality is real to me.

ClimaxGravely2• 2 years ago

can you show the 2048 clone?

EDIT : My bad, I see you posted the link elsewhere (link for posterity http://jacek.zlydach.pl/v/2048/ )

TBH 6 hours seems a lot longer than I would have expected.

shermanyo• 2 years ago

I've just had GPT-4o write me a full-featured 2048 clone in ~6 hours of casual chat, in between of work, making dinner, and playing with kids; it cost me some $4 in OpenAI bills, and I didn't write a single line of code.

This kind of example always confuses me. I don't see the value vs reading an article like this: https://www.freecodecamp.org/news/how-to-make-2048-game-in-r...

If I said I built a 2048 clone by following this tutorial, noone would be impressed. I just don't see how reading a similar tutorial via a chat interface is some groundbreaking advancement.

nl2• 2 years ago

I agree with this take.

The perspective I take is the 15 year view: The iPhone 1 sucked objectively but by the iPhone 3 the trajectory was clear and 15 years later the world is a very different place.

You hear people very focused on specific shortfalls: "I asked it to write code and look it made a mistake". But there are very clear routes to fixing these and there are lots of people finding it useful despite these bugs.

I think AI is bigger than mobile. I'm nearly 50, and I remember the PC boom, the Internet boom, Social Networking boom, Mobile boom, SaaS boom - probably more that I forget.

I think the PC and Internet booms are the only ones that are as impactful as AI will be in 15 years.

Maybe mobile is as big, maybe not - depends if someone can build AI devices that replace the UX of phones sometime in the next 15 years.

woopsn• 2 years ago

Keep in mind, the "hole" takes ChatGPT and Copilot/Gemini/etc into account at a rate of $5-10B per product. The remainder of $500B is about the size of the global cell phone market. Where will it come from?

aleph_minus_one3• 2 years ago

I can't think of a single recent technology that was so widely adopted by tech and non-tech people alike, immediately integrated into day-to-day experience.

Which technology are you talking about? ;-)

What I can clearly say is that I know no one from my social circles and extended social circles who used these AI chatbots for anything else than "simply trying out what is possible" (and ridiculing the results). A quote from a work colleague of me when I analyzed the output of some latest generation AI chatbot: "You shouldn't ask so complicated questions to the AI chat bots [with a huge smile on his face]. :-)"

tootie• 2 years ago

I can't see any news out of Sequoia without remember how massively bullish they were on FTX.

fragmede10• 2 years ago

they're human and were taken in by con artists. it's a reminder that none of us are infallible.

perlgeek• 2 years ago

Remember that this is written by Venture Capital investors, and they make high risk, high reward bets.

I don't know the exact numbers, but I guess only maybe 5% of all investments in a given batch make any impact on the total return.

So for a VC, if there's a 10% chance that this whole AI thing will be a financial success, it's chance of success is already twice as high as average, so a pretty good bet.

xmprt• 2 years ago

My rule of thumb is that if someone was super bullish on crypto 3 years ago and is now super bullish on AI then their opinion is probably not worth that much. But if they've been consistently optimistic about AI progress over the last 5-10 years then they probably know what they're talking about.

apitman4• 2 years ago

IDK. Blockchains have been super hyped. The tech is undeniably cool. But I have yet to see an example of them solving a real problem for anyone who's not a criminal.

In contrast, I've put in very little effort to use AI, but I'm noticing things.

I see high quality AI-generated images in blog posts. They look awesome.

I look over my coworker's shoulder and see vscode predict exactly the CSS properties and values he's looking for.

Another coworker uses AI to generate a working example of FPGA code that compiles and runs on a Xilinx datacenter device.

An AI assistant pops up in Facebook messenger. My girlfriend and I are immediately able to start sending each other high quality, ultra-specific inside joke AI generated memes. This has added real value to my life.

I'm starting to feel FOMO, a bit worried that if I don't go hard on learning this new tool I'm going to be left in the dust. To me at least, AI feels different.

LorenzoBloedow2• 2 years ago

I'll admit blockchains (while they may have potential for the future) don't currently have much use in the real world, but saying the only people it helps are criminals is just that old flawed argument that undermines privacy which in turn only benefits oppressors

Ekaros3• 2 years ago

I have followed one site that has own AI generator for certain type of content... And after a while it just start to feel samey and soulless... I kinda noticed similar stylistic patterns with text generated I have seen posted... Different styles can be asked, but I wonder how soon the AI output stops feeling worth seeing or reading.

sumedh3• 2 years ago

Blockchains have been super hyped.

Were regular people using it like ChatGpt?

Terr_3• 2 years ago

How can anyone be so certain about this?

Oh, it's really simple, you see if they don't get rewarded handsomely, that proves they didn't focus on delivering true [Scotsman] value. /s

paulmd• 2 years ago

just like previous technology hype cycles were surely going to Change Everything. I mean, we're seeing huge companies' entire product strategies changing overnight because We Must All Believe.

this didn’t really happen the way you want it to. Fortune 50 companies never spent billions of dollars on crypto or NFTs like they are doing for AI. No NASDAQ listed companies got trillion-dollar valuations out of crypto.

There is buy-in happening this time, unlike previous times, because this time actually is different.

The whole AI thing just continues to baffle me. It's like everyone is in the same trance and simply assuming and chanting over and over that This Will Change Everything

I mean, some people see a broad consensus forming and reactively assume everyone else must be stupid (not like ME!). That’s a reflection of your own personal contrarianism.

Instead, try to realize that a broad consensus forming means you actually hold heterodox opinions, and if you think you have a good basis for them that’s fine, but if the foundation for your point that everyone in the world is too stupid to see what’s REALLY going on then maybe your opinions aren’t as reasoned as you think they are. You need to at least understand the values differences that are leading you down the road to different conclusions before you just dismiss the whole thing as “everyone else is just too wrapped into the cult to see straight”.

Bitcoin was actually rebuttable on some easily-explicable grounds as to why nobody really needed it. Why do you think semantic embeddings, semantic indexes/generation, multimodal interfaces, and computationally-tractable optimization/approximation generators are not commercially useful ideas?

ryandrake8• 2 years ago

Instead, try to realize that a broad consensus forming means you actually hold heterodox opinions, and if you think you have a good basis for them that’s fine, but if the foundation for your point that everyone in the world is too stupid to see what’s REALLY going on then maybe your opinions aren’t as reasoned as you think they are.

I haven't even formed much of an opinion either way, yet. Sure, I have doubt, but that's more of a default than something I reasoned myself into. I'm saying it's just way too early to make statements either way about the future of LLMs and AI that are anything beyond wild guesses. "This time it's different, it's fundamentally transformative and will obviously change the world" is a religious statement when made this early.

philipwhiuk• 2 years ago

this didn’t really happen the way you want it to. Fortune 50 companies never spent billions of dollars on crypto or NFTs like they are doing for AI. No NASDAQ listed companies got trillion-dollar valuations out of crypto.

nvidia did very well out of crypto.

rsynnott3• 2 years ago

this didn’t really happen the way you want it to. Fortune 50 companies never spent billions of dollars on crypto or NFTs like they are doing for AI.

Got to imagine that IBM’s spending on their weird blockchain hobby was at least in the hundreds of millions.

And Facebook spent tens of billions of dollars on metaverse stuff, of course.

geph20212• 2 years ago

When you think about the promise (or hype) of crypto/bitcoin/blockchain 10 years ago, in some sense it augured equally, if not more, transformative change/disruption than AI.

Crypto portended drastic and fundamental changes: programmable money, disintermediation, and the decentralization of the very foundations of our society (i.e. money, banking, commerce). Suffice to say that nothing close to this has happened, and probably will never happen.

So I can see how many people are equally skeptical that AI, as the next hyped transformative technology, will achieve anything near the many lofty predictions.

2OEH8eoCRo02• 2 years ago

Why is there such an effort to hitch current AI to cryptocurrency? They have nothing in common, not the tech, and not the way people interact with it.

postalrat• 2 years ago

This whole AI thing reminds me of the early 90 and people talking about how computers would change the world. Of course they were right but probably not in the ways they expected.

ip26• 2 years ago

I think many of the changes actually were predicted. What seems to have been the most unexpected was how it would monetize and where market power would gather.

Online banking is great, and people knew it was coming since the dawn of the internet, but they mostly didn’t predict Stripe.

ukuina3• 2 years ago

If you go back and look at the overhyped ads back then, you'd see them describing the future that we are currently living, except tainted by some institutions that were too-ingrained; things like "Using the World Wide Web, you will be able to view your checking account balance and make a payment to your utility provider with just a few clicks!" right after someone brings the milk in. i.e., They could predict online banking but not the rise of DoorDash.

Given the accelerated invention/deployment cycles we're in, it's not hard to extrapolate GPT4o to $0 token cost and 0ms latency. Even assuming stagnation in context lengths and cognition, the extreme scope of impact on every computerized industry becomes self-evident.

michael_nielsen• 2 years ago

There's (at least) two meanings for AI: (1) Software systems based on extensions of the LLM paradigm; and (2) Software systems capable of all human cognitive tasks, and then some.

It's not yet clear what (1) has to do with (2). Maybe it turns out that LLMs or similar can do (2). And maybe not.

I can understand being skeptical about the economic value of (1). But the economic value of (2) seems obviously enormous, almost certainly far more than all value created by humanity to date.

2OEH8eoCRo02• 2 years ago

I think they've tapped into something fundamental about knowledge, the mind, and information and this is only the beginning. How many different ways are there to train, wire these up, and integrate with other systems? Then the silicon built for it...I just don't know where the horizon is.

root_axis• 2 years ago

Transformers clearly represent a significant advancement in software design, this is undeniable. For example, LLMs are so good at language translation that every approach to machine translation ever conceived of is now obsolete by a very large margin. There are a few other examples and certainly some new ones will emerge, so the tech is good and it's here to stay.

The question of "how do we make money from it" is a much harder to answer. Using every available computer to run quadratic time brute force on everything you can scrape from the internet is an unbounded resource sink that offers little practical return for almost everybody, but leveraging modest and practical use of generative machine learning where it works well will absolutely create some real value.

epolanski2• 2 years ago

I can't summarize it better than saying that AI hype is deserved, but the excessive euphoria and FOMO are not.

wayeq• 2 years ago

You know I hear ChatGPT is pretty good at summarizing.

danans• 2 years ago

> A huge amount of economic value is going to be created by AI. Company builders focused on delivering value to end users will be rewarded handsomely.
Such strong speculative predictions about the future, with no evidence.

The speculation makes sense from a VC's perspective, but perhaps not from the perspective of society at large (i.e. human workers).

From the revenue-generating use cases of LLMs (== AI in the article) that I've seen so far, most seem to be about replacing human mental labor with LLMs.

The replacement of workers with AI-based machines will likely happen in mature industries whose market growth is basically capped. Productivity will stay mostly the same, but the returns will increase dramatically as the human workforce is hollowed out.

To the extent that AI instead empowers some workers to multiply their productivity with the same amount of effort, then it can create more economic value overall, and this may happen in industries with a long growth runway ahead.

On balance, it's not clear to me whether the growth (in productivity and employment) that comes from the latter will be enough to offset the employment losses from the former.

But in either scenario, the VCs investing in AI win, either from efficiency gains, or from accelerating growth in new industries.

rsynnott3• 2 years ago

They’re a _VC_. If they don’t believe in it, what are they even doing? You can’t really expect them to be particularly objective about it.

from-nibly3• 2 years ago

Its because it has to. We're so far behind the 8 ball at this point if it doesn't work we are all screwed.

All of society is so freaking leveraged at this point, something has to give.

pas3• 2 years ago

society is so freaking leveraged

can you elaborate on this? in what sense?

jiggawatts2• 2 years ago

Don’t assume “widespread deployment of the same”. Think about next-gen models running faster and at a low cost.

They already understand spoken English and can respond in kind.

This is Siri or Alexa on steroids. Just that alone is a “killer app” for everyone with a mobile phone or a home assistant device!

What’s the addressable market for that right now? Five billion customers? Six or seven maybe?

Computer RPG games are about to become completely different. You’ll be able to actually converse with characters.

Etc…

I’m a short-term pessimist but a long-term optimist.

This all reminds me of 3D graphics a in the early 1990s. The nerds were impressed but nobody else thought it was interesting. Now we have Pixar and a computer games industry bigger than Hollywood.

mechagodzilla• 2 years ago

Siri and Alexa are good examples - they turned out to be incredibly expensive to develop and had extremely limited productivity benefits for users, while being almost impossible to monetize.

tim3335• 2 years ago

Imagine looking back on the earth's history from a billion years in the future. There will be a divide around now between a few billion years before when biological life was the most advanced thing going on and after that when AI life was. It's in a different category to the other tech hypes. And I don't really see any possible way that it won't happen(?)

p1esk2• 2 years ago

I don’t think anyone doubts that.

The question is when exactly do we get to human level intelligence on all tasks (agi)? Is it going to be GPT5? GPT6? Or has the performance improvements saturated already? It makes a huge difference in terms of your investment and even career decisions whether you expect it to happen next year or 10 years from now.

avereveard• 2 years ago

Think about all the high volume processes in the enterprise world with a expensive human fallback. Llm are great after the process and before the human to reduce tasks routed to the fallback.

Think about all human involved in producing unstructured document that people have to read like public councils, court of laws, teachers or other evaluators. Llm can be given a relevancy metric and flag content so that those in need of or waiting for a certain information aren't drowned in noise

Llm are unlocking digital transformation in sectors that have been historically resistant to it, and because they are goal driven they do it with minimal programming, just a few good prompts and a data pipeline.

And it's just the tip. They don't get tired, they don't forget nor omit, they are absolutely bonkers to find relevant products and services given a database a need and a set of preferences and they will transform how the next generation will make purchasing decisions, travel decision and all these opinion based choices.

And while llm are likely not the path to agi and they will cap out in capabilities at some point, they are coming down in price super fast, which will propel adoption even for those cases where other options would be more sensible, just because of the sheer convenience of just asking them to do stuff.

dvt3• 2 years ago

In reality, the road ahead is going to be a long one. It will have ups and downs. But almost certainly it will be worthwhile.

The biggest takeaway from this piece is the stark realism of this article (maybe a bit too bearish, imo) compared to the usual Sequoia VC-speak. Maybe FTX did teach them something, after all.

mike_d3• 2 years ago

VCs in general hate core AI because it is dominated by large players that don't need VC money to be successful. If someone was taking Sequoia money to buy GPUs they'd be singing a completely different tune.

smeeth2• 2 years ago

I don’t think FTX is the right contrast here. This document is mostly about business realism: revenue, margins, etc.

VCs did get burned by speculative investing in the 2019-21 period but FTX wasn’t like the others. At the time of its collapse, FTX was profitable and had $1+ bn in revenue, its doom had nothing to do with product market fit, revenue, margins, etc.

Quibi might be a more relevant example of a learning opportunity.

dvt3• 2 years ago

I don’t think FTX is the right contrast here.

Comparing this article to the (now deleted) SBF profile is night and day.

openrisk• 2 years ago

Those who remain level-headed through this moment have the chance to build extremely important companies.

But in which sector will these extemely important companies be active? Adtech? Knowledge management / productivity tools? Some completely new category?

What is an undeniable fact is the drastic commodization of the hardware / software stack for certain classes of algorithms. How is this technological development going to be absorbed and internalized by the economy feels still rather uncertain.

sumedh3• 2 years ago

But in which sector will these extemely important companies be active?

I dont think anyone knows the answer to that question.

lqprag• 2 years ago

As always, free analysis by VCs and investment banks is not necessarily for the reader's benefit.

So we have this bearish piece and the previous bearish Goldman Sachs piece. While I agree with their analysis in this case, there is a lingering doubt that some banks might just want to tank Nvidia a little in order to go long. Or something like that.

Animats2• 2 years ago

"Unlike the CPU cloud, which became an oligopoly, new entrants building dedicated AI clouds continue to flood the market. Without a monopoly or oligopoly, high fixed cost + low marginal cost businesses almost always see prices competed down to marginal cost (e.g., airlines)."

So why aren't there more entrants in the CPU cloud area? The technology is a commodity. Google and Amazon don't make CPUs.

wmf4• 2 years ago

The secret sauce in the cloud is not hardware but control plane, networking, and storage software.

falcor845• 2 years ago

And battle-tested SREs

mcast• 2 years ago

And IP space.

mike_d3• 2 years ago

So why aren't there more entrants in the CPU cloud area?

Because the market is saturated with players.

AWS, Azure, GCP, Alibaba, IBM Cloud, Digital Ocean, Tencent, Oracle Cloud, Huawei Cloud, that Dell/VMware thing, Linode/Akamai, HP, Scaleway, Vultr, GoDaddy, OVH, Hetzner, etc.

Animats2• 2 years ago

So are margins low?

jamessinghal2• 2 years ago

Would the Graviton CPUs from Amazon and upcoming Axion from Google not count?

TeMPOraL35• 2 years ago

The technology is, but operations isn't. Anyone can start a CPU cloud. Fewer can run it reliably (there are plenty of those at regional level, though). Very few can do it on a global scale, and break through the mindset of Amazon, Google and Microsoft being the only options.

mike_d3• 2 years ago

The calculations here seem to depend on a few false assumptions:

1. That all datacenter GPUs being purchased are feeding AI. You might be able to argue that some are or a lot are, but you don't know how many just looking at Nvidia sales numbers. I know of at least two projects deploying rows of cabinets in datacenters full of GPUs for non-AI workloads.

2. The assumption that pay-for-an-API is the only AI business model. What we now call "AI" has been driving Google's search and ad businesses for nearly a decade, sooo AI is already doing $300B/yr in revenue? There is no way for this guy to quantify how AI is solving problems that aren't SaaS.

David Chan, if you are reading this feel free to email me if you want a fact check for what will surely be the third installment in the series.

jerrygenser• 2 years ago

Yes but Google hasn't needed gpus to power search. It's used cpu even for ML inference and training before deep learning.

LarsDu887• 2 years ago

According to Jensen it takes about 8000 H100s running for 90 days to train a 1.8 Trillion param MoE GPT-4 scale model.

Meta has about 350,000 of these GPUs and a whole bunch of A100s. This means the ability to train 50 GPT-4 scale models every 90 days or 200 such models per year.

This level of overkill suggests to me that the core models will be commoditized to oblivion, making the actual profit margins from AI-centric companies close to 0, especially if Microsoft and Meta keep giving away these models for free.

This is actually terrible for investors, but amazing for builders (ironically).

The real value methinks is actually over the control of proprietary data used for training which is the single most important factor for model output quality. And this is actually as much an issue for copyright lawyers rather than software engineers once the big regulatory hammers start dropping to protect American workers.

laweijfmvo• 2 years ago

A lot of those GPUs are for their 3B users to run inferencing, no?

LarsDu887• 2 years ago

True that, but I think in a very short amount of time, using dedicated general purpose GPUs just for inferencing is going to be mega overkill.

If there's dedicated inferencing silicon (like say the thing created by Groq), all those GPUs will be power sucking liabilities, and then the REAL singularity superintelligence level training can begin.

benreesman• 2 years ago

It’s been a very long time since I had any inside baseball, but I very much doubt that Hopper gear is in the hot inference path.

The precisions and mantissa/exponent ratios you want for inference are just different to a mixed-precision, fault tolerant, model and data parallel pipeline.

Hopper is for training mega-huge attention decoders: TF32, bfloat16, hot paths to the SRAM end of the cache hierarchy with cache coherency semantics that you can reason about. Parity gear for fault tolerance, it’s just a different game.

Kon-Peki2• 2 years ago

It's like someone thinking that they are SOOOO smart, they are going to get rich selling shovels in the gold rush. So they overpay for the land, they overpay for the factory, they overpay for their sales staff.

And then someone else starts giving away shovels for free.

Terr_3• 2 years ago

And then someone else starts giving away shovels for free.

And their business model is shovel-fleet logistics and maintenance... :p

from-nibly3• 2 years ago

It's almost like you can't actually control the demand side.

gwd• 2 years ago

And then someone else starts giving away shovels for free.

Ah, I see -- it's more like a "level 2 gold rush".

So a level 1 gold rush is: There's some gold in the ground, nobody knows where it is, so loads of people buy random bits of land for the chance to get rich. Most people lose, a handful of people win big. But the retailers buying shovels at wholesale and selling them at a premium make a safe, tidy profit.

But now that so many people know the maxim, "In a gold rush, sell shovels", there's now a level 2 gold rush: A rush to serve the miners rushing to find the gold. So loads of retailers buy loads and loads of shovels and set up shop in various places, hoping the miners will come. Probably some miners will come, and perhaps those retailers will make a profit; but not nearly as much as they expect, because there's guaranteed to be competition. But the company making the shovels and selling them at a premium makes a tidy profit.

So NVIDIA in this story is the manufacturer selling shovels to retailers; and all the companies building out massive GPU clouds are the retailers rushing to serve miners. NVIDIA is guaranteed to make a healthy profit off the GPU cloud rush as long as they play their cards right (and they've always done a pretty decent job of that in the past); but the vast majority of those rushing to build GPU clouds are going to lose their shirts.

apitman4• 2 years ago

I thought AI is supposed to put all the lawyers out of work.

threeseed7• 2 years ago

Lexis+ AI and Ask Practical Law AI systems produced incorrect information more than 17% of the time, while Westlaw’s AI-Assisted Research hallucinated more than 34% of the time:

https://hai.stanford.edu/news/ai-trial-legal-models-hallucin...

tracerbulletx• 2 years ago

Nothing will put lawyers or doctors out of work. They are powerful cartels that can easily protect themselves. Realtors are already irrelevant technologically but they have a huge entrenched social and legal system to make it impractical to compete.

vasco2• 2 years ago

The infinitely expanding AI-generated metaverse isn't going to render itself, at least in the case of meta I think that might be one of the only pieces missing.

alberth3• 2 years ago

making the actual profit margins from AI-centric companies close to 0

The same thinking stopped many legacy tech companies from becoming a “cloud” company ~20 years ago.

Fast forward to today and the margin for cloud compute is still obscene. And they all wish in hindsight they got into the cloud business way sooner than they ultimately did.

lmm• 2 years ago

Are the second-tier cloud companies really seeing big margins? Why is it not competed away to zero like airlines?

jordanb2• 2 years ago

That's not the way I remember the cloud transition at all. My company adopted an internal cloud. VMWare had some great quarters. Openstack got really big for a while and everyone was trying to hire for it. All the hosting companies started cloud offerings.

What ended up happening was Amazon was better at scale and lockin than everyone else. They gave Netflix a sweet deal and used it as a massive advertisement. It ended up being a rock rolling down a hill and all the competitors except ones with very deep pockets and the ability to cross-subsidize from other businesses (MSFT and Google) got crushed.

Willish422• 2 years ago

once the big regulatory hammers start dropping to protect American workers

Have we been living in the same universe the last 10 years? I don't see this ever happening. Related recent news (literally posted yesterday) https://www.axios.com/2024/07/02/chevron-scotus-biden-cyber-...

hnthrow2895702• 2 years ago

The only upside is state-level minimum wage increases. The federal minimum wage is still a complete joke at $7.25 an hour.

But there's bigger fish to fry for American politics and worker obsolescence is not really top of mind for anyone.

LarsDu887• 2 years ago

I think people wildly underestimate how protectionist people - particularly educated software engineers and PhDs will get once an AI model directly impacts their source of wealth.

Red state blue collar workers got their candidate to pass tariffs. What happens when both blue state white collar workers and red state blue collar workers need to contest with AI. Perhaps not within the next 10 years, but certainly within 20 years!

And if you think 20 years is a long time... 2004 was when Halo 2 came out

shoggouth• 2 years ago

In my opinion Elsevier and others charging for access to academic publications has held back the advancement of humanity to a lower exponential acceleration into the future at a considerable factor. Think of how cancer could have been cured a decade ago if information was allowed to flow freely from the 50's forward - if anyone could have read scientific publications for free. I have no respect for people that want to protect the moat around information that could be used to advance humanity.

OJFord• 2 years ago

As much as I'd love open access to academic publications and don't think the current model is great:

Think of how cancer could have been cured a decade ago if information was allowed to flow freely from the 50's forward

might be a bit fanciful? Unless you're referring to something particular I'm unaware of.

The people best equipped and trained to deliver a cure for cancer (and then some, since it tends not to be particularly field-restricred) do have access.

I think the loss is more likely in engineering (to the publication's science), cheaper methods, more reliably manufacturable versions of lab prototypes, etc.

I doubt there are many people capable of cancer research breakthroughs who don't have access to cancer research, personally.

(And to be clear: I'm not capable of it.)

robwwilliams2• 2 years ago

Have to disagree. Almost all researchers have essentially unfettered access to all of biomedical literature. Access to papers is therefore a tertiary annoyance wrt progress in science and the cures for cancers.

What IS a huge problem is the almost complete lack of systematically acquired quantitative data on human health (and diseases) for a very large number (1 million subjects) of diverse humans WITH multiple deep-tissue biopsies (yes, essentially impossible) that srr suitable for multiomics at many ages/stages and across many environments. (Note, we can do this using mice.)

Some specific examples/questions to drive this point home: What is the largest study of mRNA expression in humans? ANSWER: The small but very expensive NUH GTEx study (n max of about 1000 Americans). This study acquired postmortem biopsies for just over 50 tissues. And what is the largest study of protein expression in humans across tissues? Oh sorry, this has never been done although we know proteins are the work-horses of life. What about lipids, metabolites, metagenomics, epigenomics? Sorry again, there is no systematically acquired data at all.

What we have instead is a very large cottage-industry of lab-level studies that are structurally incoherent.

Some brag about the massive biomedical data we have, but it is truly a ghost and most real data evaporates with a few years.

Here is my rant on fundamental data design flaws and fundamental data integration flaws in biomedical research:

Herding Cats: The Sociology of Data Integration https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2751652/

jimjimjim• 2 years ago

99%+ of the people doing scientific work in curing cancer have access to all the relevant medical and scientific journals.

eru3• 2 years ago

Eh, most published research papers are wrong anyway.

xhkkffbf• 2 years ago

1) First, most researchers at universities or other institutions have always had unfettered access thanks to a site license. It would be pretty hard to find a real example of a university researcher who couldn't see something.

2) There may be a few researchers who don't have unfettered access. Perhaps they paid $40 for a copy of a paper. Given the high cost of other parts of research labs, I find it hard to believe that any real possibility of curing cancer was halted because someone had to pay $40.

3) It's possible to imagine the opposite being the case. Perhaps someone had a key insight in a clever paper and decided to distribute it for free out of some info-anarchistic impulses. There it would sit in some FTP directory uncrated, unindexed and uncared for. Perhaps the right eyes would find it. Perhaps they wouldn't. Perhaps the cancer researcher would be able to handle all of the LaTeX and FTP chores without slowing down research. Perhaps they would be distracted by sys admin headaches and never make a crucial follow up discovery.

The copyrighted journal system provides curation and organization. Is it wonderful? Nah. Is it better than some ad hoc collection of FTP directories? Yes!

Your opinion may be that this scenario would never happen. In my opinion, this is more likely than your vision.

robertlagrant• 2 years ago

You have to not latch on to causes such as "advance humanity" and then justify making people do work for free. We decided a while ago[0] that making people work for free was a bad thing. There is high demand for curing cancer. Every company that tries it will hire scientists and lab techs and large laboratories, and have subscriptions to journals. Do you think all of those people should work for free, in the cause of advancing humanity?

[0] https://en.wikipedia.org/wiki/Slavery_Abolition_Act_1833

lkrubner• 2 years ago

But anyone who needs to see these publications can reach them through libraries. One of the reasons why Elsevier can charge so much is that their customers have been institutions.

naveen99• 2 years ago

Propriety data is not necessary for training intelligence. Wikipedia, pubmed, arxiv, Reddit and github are probably sufficient. And babies don’t even use that.

I agree though that the returns on hardware rapidly diminish.

kristjansson• 2 years ago

per Zuckerberg[0], ~half of their H100s were for Reels content recommendation:

I think it was because we were working on Reels. We always want to have enough capacity to build something that we can't quite see on the horizon yet. ... So let's order enough GPUs to do what we need to do on Reels and ranking content and feed. But let's also double that.

So there's an immense capacity inside Meta, but the _whole_ fleet isn't available for LLM training.

[0] https://www.dwarkeshpatel.com/p/mark-zuckerberg?open=false#§...

matthewdgreen• 2 years ago

Surely they’re using some of that hardware to overcome Apple’s attempts to deprive them of targeted advertising data.

forgot-im-old• 2 years ago

What percentage of GPUs are being used for training versus inference?

sailingparrot• 2 years ago

This means the ability to train 50 GPT-4 scale models every 90 days or 200 such models per year.

Not anywhere close to that.

Those 350k GPUs you talk about aren't linked together. They also definitely aren't all H100s.

To train a GPT-4 scale model you need a single cluster, where all the GPUs are tightly linked together. At the scale of 20k+ GPUs, the price you pay in networking to link those GPUs is basically almost the same as the price of those GPUs themselves. It's really hard and expensive to do.

FB has maybe 2 such clusters, not more than that. And I'm somewhat confident one of those cluster is an A100 cluster.

So they can train maybe 6 GPT-4 every 90 days.

LarsDu887• 2 years ago

Ok, I might have misread some rumored ballpark figures. And most of the GPUs will be used for inference rather than training. Still 6 GPT-4's every 90 days is pretty amazing.

LarsDu887• 2 years ago

I had to take a second look at this: https://www.datacenterdynamics.com/en/news/meta-to-operate-6...

340,000 H100s 600,000 H100 equivalents (perhaps AMD Instinct cards?) On top of the hundreds of thousands of legacy A100s.

And I'm certain the order for B100s will be big. Very big.

Even the philanthropic org Chan-Zuckerberg institute current rocks 1000 H100s, probably none used for inference.

They are going ALL OUT

VirusNewbie3• 2 years ago

Llama isn't even in the same stratosphere as the big models when it comes to coding, logic, and other interesting tasks that I think are commercially viable.

itkovian_• 2 years ago

Everything is if scaling keeps making the models better. If it does you don't train 50 gpt4s, you have the best model.

weitendorf• 2 years ago

There are more kinds of AI-centric companies than just foundation models. Making that equivalency is akin to equating internet companies during the dotcom bubble with just websites like pets.com. Now one semi-skilled person in a couple days can make websites that entire teams back then would have taken months to build, but that doesn't mean google.com and thefacebook.com are easily commodotized or bad businesses just because they're websites.

boloust2• 2 years ago

Why are we assuming we're topping out at a GPT-4 scale model?

eru3• 2 years ago

The real value methinks is actually over the control of proprietary data used for training which is the single most important factor for model output quality.

Maybe. But we've barely scratched the surface of being more economical with data.

I remember back in the old days, there was lots of work on eg dropout and data augmentation etc. We haven't seen too much of that with the like of ChatGPT yet.

I'm also curious to see what the future of multimodal models holds: you can create almost arbitrarily amounts of extra data by pointing a webcam at the world, especially when combined with a robot, or letting your models also play StarCraft or Diplomacy against each other.

babyshake• 2 years ago

once the big regulatory hammers start dropping to protect American workers.

The US Supreme Court seems determined to make sure that big regulatory hammers are not going to be dropping, from what I can tell.

lkdfjlkdfjlg• 2 years ago

but amazing for builders (ironically).

Could you expand on this? Who are "the builders" here? You mean the model developers? I don't see how this situation can be "amazing" for the builders - developers will just get a wage out of their work.

bufferoverflow• 2 years ago

this means the ability to train 50 GPT-4 scale models every 90 days or 200 such models per year.

What it actually means is that they are training next gen models that are 50X larger.

And, considering MS and OpenAI are planning to build a $100 billion AI training computer, these 350K GPUs is just a tiny portion of what they are planning.

This isn't an overkill. This is the current plan: throw as much compute as possible and hope intelligence scales with compute.

Kon-Peki2• 2 years ago

Many of the winners haven't even been formed yet. And most of the losers have already lost, they just don't know it yet.

Timber-6539• 2 years ago

The problem with AI is that it's very much a gimmick and consumers don't have much use for gimmicks. Certainly not when it works half the time and hallucinating the other half. All it takes is an NBER announcement to pop this mania.

matchagaucho• 2 years ago

There's a growing divide between inference GPUs and training GPUs.

Investors first need to ask what that ratio might look like in 10 years. 10-to-1? 100-to-1? Inference-to-Training

Assuming for each NVDA training GPU sold there are 100 open source / commodity GPUs doing inference, who owns and supplies those data centers and hardware?

dzink3• 2 years ago

AI is dangerous to VCs.

The returns are going to chip-makers and employers, including single founder startups, who don't have to hire a lot of people, and additionally get productivity they never thought possible. A surgeon I know uses AI every day - to translate, to explain, to figure out problems, to write. They wouldn't have paid someone to do that, but now they get that output in seconds. This is a time to solve all kinds of problems we didn't think possible - because AI has made the enterprising among us instantly smarter.

All the fodder about AGI being a next step is smoke and mirrors - for everyone using OpenAI knows they don't need any more niche tools as their one $20 subscription is doing more for them every day. AGI is here. Experts can correct AI generated mistakes, but those are getting less and less too. The real benchmark is: Name how many people you know who can out-do ChatGPT on a question. You won't bother to check LinkedIn for that.

The gains are aggregating towards Chips, Clouds and Entrepreneurs. The VCs, since A16Z's original AI blog post (all expense, little return, echoed this Sequoia post but did it but years ago), know they are not needed as much anymore. Fewer VCs will beat the market when founders can grow startups without raising too much money (they don't need to hire as many people). Hiring needs lead to PR waves which require VC funding. Valuation is not a big deal for founders making money either, so they may not even disclose how successful their companies are. Bragging about your gains only invites competition. So other than ponzi-type ventures where you need to attract the dinner to serve dinner, you won't hear much about the good ones.

A different era indeed. The tech giants are in for a lot of change as well. Those who have distribution may try to push their models to the masses to be the point of reference, but that can get expensive, especially for those who don't charge. AI will help improve AI performance as well and that means cheaper better performance with time.

What's most needed in this era are people who know what the world needs that hasn't been invented yet. They need to be inventing and monetizing it. Little stopping you now.

nojvek• 2 years ago

Well written argument.

The holy grail of AI is still in future. Where it can interact with software tools like we do. Competent AI Agents will be a huge productivity unlock.

anon-39882• 2 years ago

This. Whenever AI come up, people are quick to think of automations completely making every jobs obsolete. But that is probably not going to happen. What is probably going to happen is that we are going to have 1 artist handling 10x more commissions because they can just use AI to do 90% of the work and just cleanup afterwards.

I am also using this to solve problems that are usually delegated to junior developers. I get faster results (that I would have to fix up anyways) for far less effort.

threeseed7• 2 years ago

This is the sort of grifter/influencer style comment that we saw in crypto and now pervasive in AI.

Not just that AI is a great tool that will over time have a significant impact on society. It’s the breathless hype e.g. we have AGI today, society will be instantly smarter because of it and every tool and employee will be impacted. The FOMO i.e. you must jump on board now or be left behind. And the complete lack of any data or evidence.

dzink3• 2 years ago

Except I see no grift or FOMO. You don’t need to put your money into it. All you need now is instinct and creativity. The FOMO to raise money or be nobody goes away instead. The FOMO in giants to appear like they are riding the AI horse is real. Evidence is in the productivity of each individual and how many would consult with experts or expert friends vs just using AI.

brcmthrowaway• 2 years ago

Looked at their profile, total grifter vibe.

yieldcrv• 2 years ago

Yeah one things that bothered me about artist complaints is the idea that anybody was ever going to pay them.

The people expressing themselves with image AI would never have gone to fiverr or upwork to begin with.

And only some of the existing clientele would change their behaviors too.

Additionally, I know artists that always wanted to express themselves differently than what they became known for, and actually create and sell AI generated work to their clientbase now.

tim3335• 2 years ago

What people mean by AGI varies but consider:

The Coffee Test (Wozniak)
A machine is required to enter an average American home and figure out how to make coffee: find the coffee machine, find the coffee, add water, find a mug, and brew the coffee by pushing the proper buttons.

That is a step yet to come.

joebob42• 2 years ago

Well, that seems like a dumb test for the intelligence part. You need a robot for that. But that means intelligence cannot exist without a physical presence" which I think is at least controversial.

slicerdicer12• 2 years ago

"The gains are aggregating towards Chips, Clouds and Entrepreneurs. "

Are the gains aggregating to entrepreneurs? It seems like every just a matter of time before the function of the big models overtakes any entrepreneurial idea other than hardware and the models themselves.

dzink3• 2 years ago

AI overtakes software, finance, and distraction industries (content generation of any kind - text, image, video, multi-modal). Distraction industries (social and regular media) are a time waster and brain frier for most humans who often consume to escape their world or decorate /fill their time.

In software the UX is the big burden AI will overcome. Not having to deal with all the typing and clicking frees up more tasks and energy for deciding what needs to be done. Brain energy.

Distraction industries, like sugar, become obviously tart when oversaturated and AI is quickly pushing that boundary. Once people realize they’ve been served a pacifier to the brain in every free minute, they will start thinking more and consuming less.

So now AI frees more human brain energy towards what is actually needed - what problems need solved for humans, not for overloaded interfaces or zombified content consumers.

Examples: Trustworthy, efficient and safe transport for kids to and from enrichment activities. Education of others on tasks that could earn them a living. A better healthcare experience, because 60% of the admin paperwork is AI automated and health workers can talk to patients instead of typing. Organizing people to do more things together to clear the social-media-generated loneliness epidemic. Making new, interactive experiences people would pay to do, especially with friends. People ask for more things to look forward to. Not more things to type. AI is a new hands-free take on UX and UI.

Ekaros3• 2 years ago

Has anyone asked will AI actually very soon be commodity tech? With too many players competing with each other driving prices to bottom? Is there actually meaningful value to extract, after you have spend money on hardware and power?

Modern web is full of examples of platforms that really don't make money...

pedalpete2• 2 years ago

I think this is the correct take. My understanding of the article is that huge investments in hardware, mostly to NVIDIA, and spending by major tech companies is currently defining the market, even if we include OpenAI, Anthropic, etc. It is FAANG money they are running on.

I put this as equivalent to investing in Sun Microsystems and Netscape in the late 90s. We knew the internet was going to change the world, and we were right, but we were completely wrong as to how, and where the money would flow.

npalli• 2 years ago

The better analogy is the massive investment in fiber optic cable in the late 90s. All the companies in that line (Global Crossing, Worldcom etc.) went bust after investing 10s of billions but the capacity was useful (with a >90% drop in price) for future internet services. Around 2000 when the bubble was bursting only 5% of capacity was being used but proved to be useful to get all internet-first companies like the Googles, Amazon, NetFlix's going.

cruffle_duffle• 2 years ago

Good old JDS Uniphase was one of the first individual stocks I bought. I mean it had to go up right? Fiber and dark fiber and the continual threat of the internet collapsing due to load… better buy that stock!

pedalpete2• 2 years ago

I initially was agreeing with you, but I don't see NVIDIA, AWS, Microsoft, etc going to zero (and Worldcom was unraveled by accounting fraud).

Sun Microsystems sold to Oracle for $7B, and Netscape was acquired by AOL for $10B.

ddrmaxgt37• 2 years ago

I wonder how the analogy holds up given computational advances. Will a bunch of H100s be as useful a decade later like fiber ended up being?

hnburnsy• 2 years ago

I put this as equivalent to investing in Sun Microsystems and Netscape in the late 90s.

Cisco too.

treis• 2 years ago

Think the FAANGs are doing part moat defending and part value add. Like AI powered spreadsheet might dethrone Excel so Excel has to be AI powered. MS will probably get some additional revenue from it but I don't think it will be a revolutionary amount.

nabla9• 2 years ago

38 OECD countries have combined population 1.38 billion, GDP $49.6 trillion

$600 billion is $434 per person, $36 per month per person, 1.2% percent of GDP.

If 75% of the spending goes to increasing productivity, I could see it. Get rid of $450 billion in labor costs (12 - 15 million work years). Cut worked hours in call centers, customer service, many services, menial programming jobs, ...

But I don't see it happening fast enough to pay for current investments.

light_hue_12• 2 years ago

This is not an AI or ML problem. This is an Nvidia, Google, Microsoft, Meta, Tesla, etc. problem.

Most AI startups aren't building massive data centers so they're unaffected. Most money isn't spent on compute in most startups. Only a few companies spend big.

It's obviously a terrible idea to invest massive amounts into compute when Nvidia's profit margins are so astronomical if you need ROI in the long term. The massive corporations won't get their money back for these investments; but they don't have to.

sadhorse• 2 years ago

I recall Marvin Minsky saying that 1 GigaFlops would suffice for doing most of what humans do. Current AI is addiction to more data, more compute but no smarts. At least they gave us cheap compute, soon the right people will figure out how to produce real AI, not this travesty.

sheeshkebab2• 2 years ago

The only thing AI needs to do to demonstrate its value is replacing jobs at scale. Until it happens, it’s all capex and opex bs and hobby projects.

dbish2• 2 years ago

Yes, and I think we're on the way to that happening in chunks of the economy, but it's not going to be overnight, there are still a number of improvements to make along the way. I am willing to bet my time working on it that we will be replacing many jobs in the next few years.

sheeshkebab2• 2 years ago

Maybe Musk will show to all how it’s done starting with robotaxis, however looking at current state I wouldn’t bet on it, at least not anytime in near future. Buying more gpus will definitely not be the thing that solves this.

the__alchemist• 2 years ago

About a week ago, [Angela Collier posted a video on this topic](https://www.youtube.com/watch?v=dKmAg4S2KeE) highlighting the "malicious optimism" of AI hype. She used comments by the Zoom CEO as a basis, but it generalizes.

andsoitis• 2 years ago

"Consider how much value you get from Netflix for $15.49/month or Spotify for $11.99. Long term, AI companies will need to deliver significant value for consumers to continue opening their wallets."

julianozen3• 2 years ago

ELI5, why are GPUs not a commodity piece of hardware that any sophisticated chip manufacturer can't also produce?

This is one of the first time in the tech industry where the value was fully reaped by the hardware itself and not by the differentiated software that ran on top of it

alberth3• 2 years ago

Intel for a few decades didn’t do to shabby.

julianozen3• 2 years ago

Yes, they did have great run, but I think over the long run the OS they were tied to was more important

ineedaj0b• 2 years ago

they are very small, very advanced, and production yields are poor. The equipment is also stupidly expensive and takes reams of smart people just to run.

Silicon is currently the most advanced tech humans have ever made and those GPUs are on the cutting edge of that

paulmendoza• 2 years ago

Amazon has a some AI chips they created themselves. Same with Tesla. They are both behind Nvidia and probably won’t catch up BUT raw performance isn’t always the most important part. Often it’s the cost per compute unit and companies are quickly getting close to Nvidia.

julianozen3• 2 years ago

Can more less sophisticated chips perform as well as fewer more expensive chips?

_xnmw• 2 years ago

Maybe because the revenue isn't directly attributable to AI itself, but is realized in the cost savings and productivity improvements in already existing revenue streams? That's where AI has been useful to me. I can't put a number on how much AI has made me exactly, but it has certainly helped all aspects of my bootstrapped startup.

alok-g• 2 years ago

Any product should bring benefits to both the producer and the consumer.

For the case where a company is using their own AI for their own cost reduction and productivity improvements, they can keep doing that but not offer to another party.

If they offer to another party, and that party is having benefits (like you have said), the price should be such that a part of the consumer benefit is shared with the producer resulting in benefits for the producer.

The real challenge here is because of price wars, i.e., too much competition already with producers willing to take a hit on profitability in anticipation that they will be able to do so later after creating a moat above and beyond competitors. Or they think that it will strenghen their overall bigger offering by adding an otherwise lossy feature.

In a nutshell, even if there's a lot of value for the consumers, it must result in a win-win for a new product to be sustainable in the market.

dmix7• 2 years ago

but it has certainly helped all aspects of my bootstrapped startup.

Well if there's value to you then how much did you pay for it and would it realistically cover operating cost once VC cash dries up? That's the only question.

barnabyjones• 2 years ago

I think there is far too much focus on potential productivity gains, and not nearly enough on entertainment value, which still has a ways to go but much higher potential compared to serious problem solving, which may or may not be be feasible with these models. Nobody has really figured out yet a good way to integrate generative multimedia together in a way that makes a hit, but surely someone will in the next few years. Right now there are utterly half-assed apps like Linky making good money, and that's just midjourney and CAI glued together awkwardly. I don't know what a genuine hit product is going to look like, or if it'll even be an app, but the potential for generative multimedia is so much higher that what we're seeing now.

mark_l_watson• 2 years ago

Context: I have been paid to work as an AI practitioner since 2982, nothing special about me except I have worked with amazing people. I have lived through at least two “AI winters.”

The author of this blog makes a great argument that there is a risk of AI investments not paying off because if a revenue gap: The author argues that the gap between the revenue expectations implied by the AI infrastructure build-out and actual revenue growth in the AI ecosystem has increased from $200B to $600B. This is due to factors such as the subsiding of the GPU supply shortage, growing GPU stockpiles, and the dominance of OpenAI in AI revenue. The author also notes that the $125B hole in AI revenue has now become a $500B hole.

However, my experience with previous AI winters is not relevant here because now is the first time in history that there is a possibility of what we used to call “real AI” and now call AGI. No investor wants to miss out completely on the creation of near limitless wealth.

artisin• 2 years ago

LLMs are undeniably remarkable, but their wheels start to fall off once you go beyond the basics and a few party tricks. The cynical part of me thinks this tracks pretty well with our society's tendency to favor appearance over substance. Yet, if my burger order gets messed up, I don't fault the restaurant; however, if an LLM messes up my order, the same cannot be said. As a seasoned human, I feel confident saying that we humans love blaming other humans, whether it's justified or not.

So while I initially thought customer-facing roles would be front and center in the "AI revolution." Today, I tend to think they'll be bringing up the rear, with entertainment/smut applications at the forefront along with a few unexpected applications where LLMs operate behind the scenes.

bamboozled5• 2 years ago

Even smut seems to be having a pretty slow take off, I had a go of an AI porn generator for fun recently, it was nightmare fuel. I know it's "almost right and it will get better" but not being "there" yet just isn't good enough when it comes to accurately depicting penetration.

joshuakarl• 2 years ago

Data center GPUs are not only used for LLMs. Meta makes hundreds of billions and invests tens of billions on GPUs, using them directly in its core business, not just for cute chatbots. OpenAI is not the clear winner in revenue generation from "AI" if we define AI as deep learning models trained on GPUs.

surfingdino• 2 years ago

Investment incineration

Just two words to describe all the idiocy of the current wave of AI offerings.

A huge amount of economic value is going to be created by AI. Company builders focused on delivering value to end users will be rewarded handsomely. We are living through what has the potential to be a generation-defining technology wave.

No. It's crap no matter how much money you throw at it. It will end in tears, because there is no standard, no operating system, no protocol, only a handful of APIs controlled by a couple of companies. They are not building networks, but hubs with a single point of failure--the API provider. The internet is such a world-changing force because it is built on top of TCP/IP, which allows the rest of the internet to survive even if a part of it goes down. When an AI API provider shuts down, all those bullshitters repackaging LLMs will be left holding the bag, or rather their investors will be. In a way, the coming AI bubble burst is going to be a self-fulfilling prophecy--AI will make its creators redundant.

But we need to make sure not to believe in the delusion that has now spread from Silicon Valley to the rest of the country, and indeed the world. That delusion says that we’re all going to get rich quick, because AGI is coming tomorrow, and we all need to stockpile the only valuable resource, which is GPUs.

No, the delusion is that Gen AI is good for anything. It is not.

Soon, the $600B question is going to be, "where's the money gone?"

timestap• 2 years ago

Are there any case studies of companies/cloud vendors using non-Nvidia GPUs for inference at scale?

Assuming startups like Etched (with its recent massive funding) could shrink CapEx quite a bit (and make it not such a large revenue shortfall)

arisAlexis• 2 years ago

The article doesn't say anything. First is says AI is meh for profit and it ends with AI is the most important tech ever and will generate tons of money. I think if it wasn't written in the sequoia blog it would have gotten very little attention.

demaga• 2 years ago

It's all relative. The author does appreciate AI and its potential value. He simply argues that this value won't be as high as $600B.

ksec• 2 years ago

This article and most of these thesis assume one thing, you need to make a return of investment from AI while using OpenAI revenue as an anchor to measure it.

What if these AI investment were only to protect or strengthen their current business? AI in Windows, macOS, Adobe, iPhone, Facebook, Instagram may not bring in any additional revenue. But it add additional value to their current product line, making competition harder, further hardening their moat.

Nvidia or Jensen is also smart to play the national security card. Does the European want their model to be all US based. Are the answer culturally correct? Just like how every single country invested in their own Telecom or Internet infrastructure, if this pitch were even half as successful, do these numbers we are looking at even matter when it is spread out across G7 or G20?

While I believe we are still far, or at least 10+ years away from AGI, the current form of AI still has a lot of improvement incoming and are already bringing in real world benefits and value to a lot users. The adoption curve will accelerate once it is integrated into Windows, Office and Mac. So even if we are in a bubble, I still think we are very early in the curve before it burst.

barbequeer• 2 years ago

AI's $600B Question

What do you get if you multiply six by seven

padiyar83• 2 years ago

I think we are applying the wrong model here. We should not try to force-fit an app store model. A more applicable model is that of a decentralized internet and intranet. As in the case of intra-net, even though there were no visible benefits to the end-user, it did help the business itself improve margins by making information broadly available. Then just like the internet I would see these AI optimisations to work with one another Ex: It's totally possible that a model from Amazon and DHL talk to each other to optimize package delivery given a constraint like a truck parked on a loading dock and unable to move.

#1 Just like the intranet there are a lot of productivity gains that firms like Tesla, Meta, Google and Amazon can gain internally by optimizing their own workflows. That in itself should justify the investment. Granted some of these optimisations will use their own chips instead of Nvidia, but Nvidia will get a lion-share of this.

#2. Then there are other verticals - pharma, oil and gas, logistics who can optimize their internal workflows to gain productivity. It just helps them improve their margins. No end user benefit may be realized and that’s fine.

#3. Nation states are buying GPUs too. Ex: Falcon2 was trained on a cluster owned by a middle eastern country. Nation states see something larger at stake here than just releasing an app. This does not have to even be a profitable endeavour.

AI's $600B Question

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