7 ms·

Most AI startups are doomed

177 points by j-wang 3y ago

dyarosla 3y ago
In short; if AI is a commodity, it cannot be your moat. This is especially relevant wrt startups which can’t compete on compute or research: instead they must compete on something that is more defensible: unique data, first mover adv, etc.
christkv 3y ago
I think we will see some pure play models for different verticals that will work but most apps will integrate an expected set of ai functions that will just be considered standard for all bigger apps.
oceanstone 3y ago
The article mentions "And, indeed, even Alphabet/Google internally have said this." Just a reminder, any employee can write a document saying anything.
BrokrnAlgorithm 3y ago
Deleted comment, wrong thread
deleted 3y ago
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JumpCrisscross 3y ago
Most start-ups are doomed. If you can build it in a weekend, they can too. But they didn't. And you have a weekend's head start.
- simbolit 3y ago
  That's the first section of the article. It then continues for four more sections.
  - JumpCrisscross 3y ago
    Author concludes the only moats for an AI start-up are captured compute and proprietary data. I'm disagreeing. Good execution remains differentiated. It just requires continuous iteration, evolution and improvement. If you build an MVP over a weekend and then pivot 100% of your efforts to fundraising and marketing, as has been the trend over the past decade, yes, you're screwed. You're building dollar apps for another App Store. Most of the arguments the author levels would have worked against the first waves of computerization, digitisation and the emergence of the Internet, in some cases more powerfully. Yet the prediction didn't hold. Capex and IP weren't sole, or even strong, predictors of new-entrant success. For Exhibit A to the first part, see Softbank.
    - Swizec 3y ago
      > Good execution remains differentiated. Levels is a good example of this. While we're sitting here waxing poetic about moat or no moat and what to do with these AI things, he's made some 7 figures in cold hard cash revenue from building and shipping things people want. https://twitter.com/levelsio/status/1669269424543793153 https://twitter.com/levelsio/status/1669269424543793153
      - lumost 3y ago
        7 figures is pretty great for an individual, assuming that there is at least a 50% margin. For a company it's a good start in SF. Scaling a business with no moat will quickly bump into margin compression and a race to the bottom. Not a problem if you are an individual with no intent to scale, but a big problem if you are investor looking to invest 8 figures.
        Swizec 3y ago
        Distribution is a defendable moat however. Even for investors. Once you have a few thousand users giving you cold hard cash to use your service, you also have access to way _way_ better product development and marketing information. Not to mention a lot of data you can use to fine-tune your AI in ways that a competitor starting from scratch couldn't dream to replicate. This is a big part of why you see all these BigTech companies adding AI features. Their existing user-base is the moat.
- deadbabe 3y ago
  You will learn very quickly a head start doesn’t mean anything against very powerful competitors.
  - JumpCrisscross 3y ago
    > a head start doesn’t mean anything against very powerful competitors You know what powerful competitors have a habit of doing? The thing that keeps them powerful? Buying those with a head start.
    - deadbabe 3y ago
      That’s the diplomatic option, otherwise they’ll just crush you.
      - objektif 3y ago
        Good thing is that they can not crush everyone all at once. Large businesses have priorities.
      - JumpCrisscross 3y ago
        > otherwise they’ll just crush you If you go for their core business, sure. Otherwise, this is cartoonish.
        danielmarkbruce 3y ago
        Even if you go for their core business they might not crush you! Social media being the obvious example. If you go for a full frontal attack on their core business, you'll probably get crushed. Short of that... working at a fang will make anyone not very scared of them.
  - cellis 3y ago
    Oh, but it does. Innovator's Dilemma.When Microsoft started, IBM could have destroyed them, if they were willing to become a software first and not a Mainframe company. When Google launched, Microsoft Could have easily "crushed" them, IF they were willing to cannibalize their existing business. Facebook/Instagram is one major data point where this didn't happen. Never forget that "powerful competitors" are slow. Very, very slow, even past 200 employees. Meetings and arguments increase the latency of delivering new products and services. Incentives start to be misaligned that make it difficult to continue delivering at the same quality ( why should I put in 2X to build 100X value, when I'm only getting 0.02%? ) Worry more about the startups that start alongside you.
- throwaway29812 3y ago
  Also some markets just aren't worth it to large companies, and a start up dominating a small market is still a very heathy company.
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0xbadcafebee 3y ago
I don't think he gets the point of a hype cycle. The point is to overinflate the value of a business, to suck up the dollars by the idiotic investors rushing to be part of the next Google, take all the cash you can as quickly as you can, and either exit, or shut down the business, after having pocketed millions/billions. The more and faster you grow, the more you can pocket. Whether this is sustainable or not is beside the point. Actually, if it seems sustainable, that's kind of bad for business. You'll get more money from the inept VCs if you tell them you'll have insane, impossible growth. Yes, AI startups are doomed. So what? Founders can make millions with a doomed startup.
simbolit 3y ago
TLDR: The underlying basis is the same for everyone: # the whole internet to scrape # the largest amount of gpu compute you have ever seen # more or less open source fundamentals thus "ai" will become a commodity, unless you have specific non-public useful data.
ldjkfkdsjnv 3y ago
Yeah but you raise capital, dont have a boss, and get some psuedo elite social status. You get to look down on others, tweet on twitter, act like you had a hand in developing AI. You get to code random software you come up with off the top of your head, try to the newest frameworks. You develop intuition for understanding capital markets, innovation, and what to value. You get to hire people that work the same hours as you, and are probably equally as talented, except they get 10-20x less equity. What a great way to be employed.
- herval 3y ago
  nice job summarizing everything starting a company is NOT.
  - ldjkfkdsjnv 3y ago
    this is almost certainly how it is for ivy league grads raising a few million with no product
ngngngng 3y ago
Don't get caught up in the hype. The technology is becoming commoditized, and only startups with unique advantages will survive. Look for startups with proprietary data, special algorithms, or deep domain expertise. Avoid ones that are just gluing together APIs or building generic applications. And don't chase the hype train. Invest in startups with a real chance of success.
- morkalork 3y ago
  If you want to start your own, it's kind of a depressing realization to have after working at a start-up or interacting with others. It's not some cool tech or algo that makes the difference, it's things like the CTO is leveraging contacts they made previously in their career to get deals to access data that no mere mortal could get, or board members who broker sweet partnerships with legacy companies that matter.
- kirse 3y ago
  Avoid ones that are just gluing together APIs or building generic applications. Debating if I want to respond to this, because there is fistfuls of cash right now in software consulting for this sort of work. Boring CRUDs and API integrations make a lot of the world go round (quietly).
- jqpabc123 3y ago
  Invest in startups with a real chance of success. The difficult part (as it has always been) is identifying these.
ericjmorey 3y ago
I don't get the Intel example. That business has been a duopoly since the 90s, but he's using it as an example of something that won't be able to create and maintain a large advantage for decades?
- prewett 3y ago
  The example isn't Intel, the example is some company three times faster than Intel. Think DEC Alpha, Sun, SGI. None of them were able to maintain their advantage in speed (although for SGI it was graphics and not CPUs where they failed to outpace the commoditization).
personjerry 3y ago
How's that different from any other tech startup? Tech and software have always been a commodity. Twitter is barely more than a CRUD. You always had to build your moat, i.e. network effect or data. The only difference is whereas we used to do "tech" with "algorithms" now replace that word with "AI", and it works a lot better. Seriously, replace all instances of "AI" with "algorithms" in this article and it could've been written 20 years ago. IMO very empty virtue signaling article.
- Mistletoe 3y ago
  Well I can't build a Twitter on my own PC (need other users) like I assume I can in a few years with LLMs you run locally. AI is more general purpose and can do lots or all of the things the algorithms could do before and I needed specialization for. Not only that, but Microsoft and the big players are going to make an AI that is better integrated and more advanced than any startup could for my purposes.
- j-wang 3y ago
  Good point—that is the point. When there's a hype cycle, people often check their normal business sense at the door in terms of customers, value generation, and defensibility. Are there any of these? No, but it's crypto. Or now AI. I do go somewhat beyond that in pointing out exactly why most of these startups don't have defensibility. Perhaps for some people it doesn't need to be said, but back when I wrote this... and now... the market seems to suggest that it isn't that obvious.
- lemmsjid 3y ago
  I think you're really re-stating his case, which is interesting because you then call it 'empty virtue signaling'. He's applying a standard analytical lens to AI startups, e.g. looking for their moats through finding differentiators in economics, data, scalability, etc. He finds that "doing AI" is not a stable enough differentiator to compel him as a VC. He then lays out his reasons. There are plenty of startups selling themselves on their AI platform and/or acumen, so it's rather automatically relevant to a VC at least.
  - 3y ago
jes5199 3y ago
personally I'd be happy with a non-startup "perfectly ok businesses"
gimili 3y ago
I think it is more complex than the author thinks. There are clearly defensible aspects for ai startups. Specifically I think these are: a) in-context and collaborative features (since working alone with ai through a chat box is unlikely the only way we will interact) b) gated knowledge/data (since commonly available technology can be leveraged with unique data) c) edge computing and offline usecases won't be the center piece for many classical companies and therefore can be very well exploited. I wrote up a framework to assess LLM powered Startups/Ideas here: https://assistedeverything.substack.com/p/the-three-hills-model-for-evaluating https://assistedeverything.substack.com/p/the-three-hills-mo...
- neptudemon 3y ago
  Doesn't (a) fall into the bucket of UI, i.e., something that can be easily copied? Agreed on (b) - I think this is anyone's best shot at a moat. Curious to see how (c) evolves. It's unclear to me whether the future of these things are running locally or whether we'll all continue hitting remote APIs
  - gimili 3y ago
    I don't think (a) is a pure UI thing. Think of the difference of using a single-user application to e.g. make mockups for websites or a collaborative environment like figma, in which you happen to also be able to have AI collaborate with you. Very different usecases and solving collaboration workflows, etc. is non trivial. I guess for (c) both things will exist. Local will be done for 2 reasons: - data sovereignty (e.g. companies wanting to have applications that are purely trained/fine tuned on their own data; but that improvement is not shared) - privacy (anything from an AI having access to all your email and calendar up to having intimate "friendships" with AI)
- j-wang 3y ago
  I think various of those aspects you call out here, I do as well. The specificity of the application is fairly key, whether it comes through proprietary data or application-specific stuff or simply business-lock-in. Interesting hill analogy—I do broadly agree with the areas.
germinalphrase 3y ago
Most data about [how people work/play/live] is not being captured. Non-public datasets are abundant. Build a tool to capture and utilize that data in a useful way, and you've built yourself a moat.
buitreVirtual 3y ago
Something that gets overlooked here is that most people will associate the early players for a particular kind of AI (OpenAI) with being at the forefront. Even if there are 100 competitors offering the same service with similar quality, sticking to the best-known provider gives confidence to enterprise buyers, especially when they have to explain the purchase to their bosses or shareholders. This, and the ability to attract and retain top talent, will continue to be an advantage of the early winners as long as they also continue to focus on pushing the boundaries and don't fall too far behind when competitors come up with new advances. Heck, they can even relax and cash out after a while and continue to reap the benefits, like IBM continues to do for enterprise computing even to this day despite (shamefully) not caring to be at the forefront anymore.
megaman821 3y ago
He kind of hints at one way to be successful with his mention of Azure and private blockchains. If Intel or Boeing are going to use AI to help with design, they are going to have train private custom models from their proprietary data. I am sure there a several other services that enhance the effectiveness of AI that a startup could be based on.
agentultra 3y ago
A lot of these companies also misunderstand their value proposition, the classic, "Uber for X," approach to starting a company. Also known as, "Me too!"
lacker 3y ago
This reminds me of people saying that search engines were doomed as a business in the late 90's. They have no real moat. All you need is to gather all the text on the internet, make an index, and build it on well-known information retrieval algorithms. PageRank was even in a published paper. Well, this was only mostly true. With search engines, there was a "winner-take-all" effect. Yes, many companies could build search engines, but Google was just a little bit better. Once one of the search engines is a little bit better, why would you use anything else? Eventually, Google figured out how to create a real moat, by using click data to improve search result ranking. Even though Microsoft is willing to spend billions of dollars on Bing, they don't have access to Google's user data, and aren't quite able to match Google's search quality. I believe that many AI startups will have a similar "data moat". If you are the first AI company to get a significant amount of users, you may be able to learn from their behavior to improve the product. If you can do this, you'll have an advantage that competitors won't be able to easily copy. So just make something people want, gather data on what your users are doing, and use that data to make your product better. If you do that right, you'll keep growing, and you'll be able to describe this simple strategy as a "proprietary data advantage" to give your slides more buzzwords if you need them.
- amelius 3y ago
  The article applies to medium and small businesses. For 99% of these businesses, search engines are a doomed endeavor.
- willdr 3y ago
  Don't worry, Google are hard at work undermining the product they worked so hard to build. Every year google search is worse at surfacing what you're looking for and better at an ads platform, and the advent of LLMs and SEO agencies flooding the internet with no-value regurgitated content is also not helping.
- bdcravens 3y ago
  Additionally, Google dismissed the trend of other search engines: everyone was building a portal, which for the most part didn't add much value for users. Even today, Google, which is really just an advertising company, has no ads or other content on its main page. (it does have a few internal links on the extreme edges, but has arguably the most white space of any online company)
rvz 3y ago
Those in AI that are not data providers or a source of enormous amount of new private data and access to data centers are doomed. ChatGPT wrappers have a huge platform-risk by the GPT marketplace. The ones that are dependent on VC cash and making little money against open source models or cheaper solutions are going to lose the AI race to zero.
hn_throwaway_99 3y ago
I thought this was a pretty good analysis. And for comments along the lines of "Most start-ups are doomed", the article acknowledges this in the first sentence ("The statement that most AI startups are doomed can be fairly mundane. After all, most startups are doomed, just by the numbers.") but then goes on to make an argument specific to these AI startups. I do, though, believe the author missed a large class of AI startups that I think will likely succeed in the "Wait, so what IS defensible?" section: startups that focus like a laser on very specific, semi-niche workflows where things like UX and compliance are critical. My best example of this so far is Harvey.ai, whose tagline is "Generative AI for Elite Law Firms": 1. First, elite law firms have lots of money to spend, and they'll spend it if they see an ROI. 2. There are plenty of Web 2.0 startups who won primarily because of first-mover advantage. I mean, Docusign wasn't exactly amazing, world-changing technology, but they became synonymous with "legal signatures over the internet" such that they became the default for this use case. 3. Obviously something like "generative AI for elite law firms" has tons of compliance concerns around it. If Harvey.AI can address that, it's a huge wn. As another example, I know of some big financial firms/banks that have giant committees around anything remotely label-able as "AI" because there are so many compliance concerns around AI (a system that gives you an answer with no visibility into how that answer was generated is anathema to the "everything must be auditable" mindset of the financial world). Again, Docusign is a good analogy here, because so much of their initial work was not in tech but ensuring that there was a legal framework (in many jurisdictions) that would deem internet signatures valid. My overall point is that a UX that is highly tailored to specific, profitable use cases can still win out.
- __loam 3y ago
  I'm biased because I worked in legal tech for a while but I think Harvey is kind of fucked. There's a bunch of cloud native legal startups in the space already that can easily plug in this technology and that already have an established reputation and rapport with existing users.
  - hn_throwaway_99 3y ago
    To be clear, I'm not necessarily saying Harvey will be the "winner", but I believe that their will be a winner in the "Legal AI startup" space, and I think this startup will win by having the UX that is best focused on lawyers and addresses lawyers' compliance concerns (not that they will have the best models or tons and tons of data).
bloppe 3y ago
Drop the "AI". It's cleaner.
elhospitaler 3y ago
I think this is mostly true, except I imagine OpenAI has a more defensible head start due to all the user data they've collected from people's queries. If they can maintain their lead in model quality (which is definitely possible - the engineering task of training the best and largest LLMs is not for the faint of heart) and remain the "best" general use chatbot, I could definitely see them build an insurmountable lead with all of their user data.
jeffreyw128 3y ago
This is the dumbest thing I've read in a long time
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toddmorey 3y ago
tldr: most companies on the planet are "doomed to be perfectly ok businesses".
amelius 3y ago
AI developer is the new web developer.
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bdcravens 3y ago
Last year crypto, this year AI, next year...?
- jqpabc123 3y ago
  And these two have a lot in common. Both consume large amounts of computing resources and energy to produce questionable results.
beefman 3y ago
You can have a moat if you have an app store...
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zombiwoof 3y ago
Does this include porn ai?
axegon_ 3y ago
Well... Yeah. Most startups are doomed by definition. The AI breakthroughs definitely made a lot of people open their pockets. Admittedly a year and a half ago I was banking on a second AI winter - it seemed that we had peaked for the time being. OpenAI changed that and re-opened the gates that were starting to close. Funny thing is we are still recovering from half a decade of "everything-blockchain". While I did say that blockchain was nothing more than a ponzi scheme(and I still stand by this statement), in the realm of AI, I'm not entirely sure what to expect.
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Markleodx 3y ago
Everyone's racing to build their own data moat, but here's the catch: AI tech is moving at lightning speed. Less data, more power. It's like trying to build a castle on quicksand. And then there's the Google effect – they turned 'searching' into 'Googling', basically winning the internet. So, for AI startups, it's not just about gathering data; it's about adapting quickly and carving out your niche before the landscape shifts again. Here's to the brave souls navigating this wild AI terrain!
tinyhouse 3y ago
I like the article but I also disagree with one important assumption that author makes implicitly. It assumes that LLM is all you need so in order to differentiate you need something that others don't have, like health care data. The reality is that for many problems you still need a lot of work to build a quality solution around LLM. Not something that you can build in a weekend.
molave 3y ago
It's just like most bubbles (automaking, 1990s dotcoms, crypto, etc)
nojvek 3y ago
Title should be “Most VC funded AI startups are doomed”. I dunno man, levelsio (Pieter) and Danny his friend are making millions as solopreneurs taking existing models, some light training and adding beautiful frontends to it. You’re right they’re not VC scale but this is what excites me. AI for indiehackers is a massive multiplier. One person million dollars net after tax / year is a phenomenal business. I personally think Statups that raise millions of dollars are doomed. Long live the lean cockroach startups. Midjourney is 100M+ with 10-ish engineers. That’s a phenomenal business. They raised 0 VC.
- raztogt21 3y ago
  Pieter and Danny businesses are not startups, these are "lifestyle" business. They even say that continuously. They see what's trending and feasible, glue some generative APIs with an okish frontend and publish it. Repeat.
hunterhod 3y ago
I think there are certainly more AI startups than there are viable business models. I still see exceptions like https://cursor.sh https://cursor.sh though. There are people building things that people actually want and who are building brand loyalty.
geniium 3y ago
This is more a clickbait title than anything else. The problem are the same in any buble. AI is a bubble right now. And if you don't create a valid business, brand, etc.. you wont success.
1vuio0pswjnm7 3y ago
Nevermind "AI". Fact is, most startups are doomed. Only small percentage succeed.
eadmund 3y ago
‘This principle runs through most of the AI sector today. There’s going to be a lot of value generated that just accrues to society, and isn’t captured by any private player. Which is wonderful, by the way—this is how technology becomes one of the few “free lunches” we have in society and macroeconomics. ‘There’s also going to be a lot of value generated that is simply captured by existing industry incumbents, using their market power and scale. That’s not a free lunch for society, but is also just how capitalism works and often still generates “surplus” (Econ speak for “good stuff”) for society.’ The first paragraph is also just how capitalism works, and it arguably works better than other systems at generating uncaptured value.

177 points by j-wang 3y ago

In short; if AI is a commodity, it cannot be your moat. This is especially relevant wrt startups which can’t compete on compute or research: instead they must compete on something that is more defensible: unique data, first mover adv, etc.

christkv 3y ago

I think we will see some pure play models for different verticals that will work but most apps will integrate an expected set of ai functions that will just be considered standard for all bigger apps.

oceanstone 3y ago

The article mentions "And, indeed, even Alphabet/Google internally have said this." Just a reminder, any employee can write a document saying anything.

BrokrnAlgorithm 3y ago

Deleted comment, wrong thread

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JumpCrisscross 3y ago

Most start-ups are doomed. If you can build it in a weekend, they can too. But they didn't. And you have a weekend's head start.

simbolit 3y ago
That's the first section of the article. It then continues for four more sections.
- JumpCrisscross 3y ago
  Author concludes the only moats for an AI start-up are captured compute and proprietary data. I'm disagreeing. Good execution remains differentiated. It just requires continuous iteration, evolution and improvement. If you build an MVP over a weekend and then pivot 100% of your efforts to fundraising and marketing, as has been the trend over the past decade, yes, you're screwed. You're building dollar apps for another App Store. Most of the arguments the author levels would have worked against the first waves of computerization, digitisation and the emergence of the Internet, in some cases more powerfully. Yet the prediction didn't hold. Capex and IP weren't sole, or even strong, predictors of new-entrant success. For Exhibit A to the first part, see Softbank.
  - Swizec 3y ago
    > Good execution remains differentiated. Levels is a good example of this. While we're sitting here waxing poetic about moat or no moat and what to do with these AI things, he's made some 7 figures in cold hard cash revenue from building and shipping things people want. https://twitter.com/levelsio/status/1669269424543793153 https://twitter.com/levelsio/status/1669269424543793153
    - lumost 3y ago
      7 figures is pretty great for an individual, assuming that there is at least a 50% margin. For a company it's a good start in SF. Scaling a business with no moat will quickly bump into margin compression and a race to the bottom. Not a problem if you are an individual with no intent to scale, but a big problem if you are investor looking to invest 8 figures.
      - Swizec 3y ago
        Distribution is a defendable moat however. Even for investors. Once you have a few thousand users giving you cold hard cash to use your service, you also have access to way _way_ better product development and marketing information. Not to mention a lot of data you can use to fine-tune your AI in ways that a competitor starting from scratch couldn't dream to replicate. This is a big part of why you see all these BigTech companies adding AI features. Their existing user-base is the moat.
deadbabe 3y ago
You will learn very quickly a head start doesn’t mean anything against very powerful competitors.
- JumpCrisscross 3y ago
  > a head start doesn’t mean anything against very powerful competitors You know what powerful competitors have a habit of doing? The thing that keeps them powerful? Buying those with a head start.
  - deadbabe 3y ago
    That’s the diplomatic option, otherwise they’ll just crush you.
    - objektif 3y ago
      Good thing is that they can not crush everyone all at once. Large businesses have priorities.
    - JumpCrisscross 3y ago
      > otherwise they’ll just crush you If you go for their core business, sure. Otherwise, this is cartoonish.
      - danielmarkbruce 3y ago
        Even if you go for their core business they might not crush you! Social media being the obvious example. If you go for a full frontal attack on their core business, you'll probably get crushed. Short of that... working at a fang will make anyone not very scared of them.
- cellis 3y ago
  Oh, but it does. Innovator's Dilemma.When Microsoft started, IBM could have destroyed them, if they were willing to become a software first and not a Mainframe company. When Google launched, Microsoft Could have easily "crushed" them, IF they were willing to cannibalize their existing business. Facebook/Instagram is one major data point where this didn't happen. Never forget that "powerful competitors" are slow. Very, very slow, even past 200 employees. Meetings and arguments increase the latency of delivering new products and services. Incentives start to be misaligned that make it difficult to continue delivering at the same quality ( why should I put in 2X to build 100X value, when I'm only getting 0.02%? ) Worry more about the startups that start alongside you.
throwaway29812 3y ago
Also some markets just aren't worth it to large companies, and a start up dominating a small market is still a very heathy company.

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0xbadcafebee 3y ago

I don't think he gets the point of a hype cycle. The point is to overinflate the value of a business, to suck up the dollars by the idiotic investors rushing to be part of the next Google, take all the cash you can as quickly as you can, and either exit, or shut down the business, after having pocketed millions/billions. The more and faster you grow, the more you can pocket. Whether this is sustainable or not is beside the point. Actually, if it seems sustainable, that's kind of bad for business. You'll get more money from the inept VCs if you tell them you'll have insane, impossible growth. Yes, AI startups are doomed. So what? Founders can make millions with a doomed startup.

simbolit 3y ago

TLDR: The underlying basis is the same for everyone: # the whole internet to scrape # the largest amount of gpu compute you have ever seen # more or less open source fundamentals thus "ai" will become a commodity, unless you have specific non-public useful data.

ldjkfkdsjnv 3y ago

Yeah but you raise capital, dont have a boss, and get some psuedo elite social status. You get to look down on others, tweet on twitter, act like you had a hand in developing AI. You get to code random software you come up with off the top of your head, try to the newest frameworks. You develop intuition for understanding capital markets, innovation, and what to value. You get to hire people that work the same hours as you, and are probably equally as talented, except they get 10-20x less equity. What a great way to be employed.

herval 3y ago
nice job summarizing everything starting a company is NOT.
- ldjkfkdsjnv 3y ago
  this is almost certainly how it is for ivy league grads raising a few million with no product

ngngngng 3y ago

Don't get caught up in the hype. The technology is becoming commoditized, and only startups with unique advantages will survive. Look for startups with proprietary data, special algorithms, or deep domain expertise. Avoid ones that are just gluing together APIs or building generic applications. And don't chase the hype train. Invest in startups with a real chance of success.

morkalork 3y ago
If you want to start your own, it's kind of a depressing realization to have after working at a start-up or interacting with others. It's not some cool tech or algo that makes the difference, it's things like the CTO is leveraging contacts they made previously in their career to get deals to access data that no mere mortal could get, or board members who broker sweet partnerships with legacy companies that matter.
kirse 3y ago
Avoid ones that are just gluing together APIs or building generic applications. Debating if I want to respond to this, because there is fistfuls of cash right now in software consulting for this sort of work. Boring CRUDs and API integrations make a lot of the world go round (quietly).
jqpabc123 3y ago
Invest in startups with a real chance of success. The difficult part (as it has always been) is identifying these.

ericjmorey 3y ago

I don't get the Intel example. That business has been a duopoly since the 90s, but he's using it as an example of something that won't be able to create and maintain a large advantage for decades?

prewett 3y ago
The example isn't Intel, the example is some company three times faster than Intel. Think DEC Alpha, Sun, SGI. None of them were able to maintain their advantage in speed (although for SGI it was graphics and not CPUs where they failed to outpace the commoditization).

personjerry 3y ago

How's that different from any other tech startup? Tech and software have always been a commodity. Twitter is barely more than a CRUD. You always had to build your moat, i.e. network effect or data. The only difference is whereas we used to do "tech" with "algorithms" now replace that word with "AI", and it works a lot better. Seriously, replace all instances of "AI" with "algorithms" in this article and it could've been written 20 years ago. IMO very empty virtue signaling article.

Mistletoe 3y ago
Well I can't build a Twitter on my own PC (need other users) like I assume I can in a few years with LLMs you run locally. AI is more general purpose and can do lots or all of the things the algorithms could do before and I needed specialization for. Not only that, but Microsoft and the big players are going to make an AI that is better integrated and more advanced than any startup could for my purposes.
j-wang 3y ago
Good point—that is the point. When there's a hype cycle, people often check their normal business sense at the door in terms of customers, value generation, and defensibility. Are there any of these? No, but it's crypto. Or now AI. I do go somewhat beyond that in pointing out exactly why most of these startups don't have defensibility. Perhaps for some people it doesn't need to be said, but back when I wrote this... and now... the market seems to suggest that it isn't that obvious.
lemmsjid 3y ago
I think you're really re-stating his case, which is interesting because you then call it 'empty virtue signaling'. He's applying a standard analytical lens to AI startups, e.g. looking for their moats through finding differentiators in economics, data, scalability, etc. He finds that "doing AI" is not a stable enough differentiator to compel him as a VC. He then lays out his reasons. There are plenty of startups selling themselves on their AI platform and/or acumen, so it's rather automatically relevant to a VC at least.
- 3y ago

jes5199 3y ago

personally I'd be happy with a non-startup "perfectly ok businesses"

gimili 3y ago

I think it is more complex than the author thinks. There are clearly defensible aspects for ai startups. Specifically I think these are: a) in-context and collaborative features (since working alone with ai through a chat box is unlikely the only way we will interact) b) gated knowledge/data (since commonly available technology can be leveraged with unique data) c) edge computing and offline usecases won't be the center piece for many classical companies and therefore can be very well exploited. I wrote up a framework to assess LLM powered Startups/Ideas here: https://assistedeverything.substack.com/p/the-three-hills-model-for-evaluating https://assistedeverything.substack.com/p/the-three-hills-mo...

neptudemon 3y ago
Doesn't (a) fall into the bucket of UI, i.e., something that can be easily copied? Agreed on (b) - I think this is anyone's best shot at a moat. Curious to see how (c) evolves. It's unclear to me whether the future of these things are running locally or whether we'll all continue hitting remote APIs
- gimili 3y ago
  I don't think (a) is a pure UI thing. Think of the difference of using a single-user application to e.g. make mockups for websites or a collaborative environment like figma, in which you happen to also be able to have AI collaborate with you. Very different usecases and solving collaboration workflows, etc. is non trivial. I guess for (c) both things will exist. Local will be done for 2 reasons: - data sovereignty (e.g. companies wanting to have applications that are purely trained/fine tuned on their own data; but that improvement is not shared) - privacy (anything from an AI having access to all your email and calendar up to having intimate "friendships" with AI)
j-wang 3y ago
I think various of those aspects you call out here, I do as well. The specificity of the application is fairly key, whether it comes through proprietary data or application-specific stuff or simply business-lock-in. Interesting hill analogy—I do broadly agree with the areas.

germinalphrase 3y ago

Most data about [how people work/play/live] is not being captured. Non-public datasets are abundant. Build a tool to capture and utilize that data in a useful way, and you've built yourself a moat.

buitreVirtual 3y ago

Something that gets overlooked here is that most people will associate the early players for a particular kind of AI (OpenAI) with being at the forefront. Even if there are 100 competitors offering the same service with similar quality, sticking to the best-known provider gives confidence to enterprise buyers, especially when they have to explain the purchase to their bosses or shareholders. This, and the ability to attract and retain top talent, will continue to be an advantage of the early winners as long as they also continue to focus on pushing the boundaries and don't fall too far behind when competitors come up with new advances. Heck, they can even relax and cash out after a while and continue to reap the benefits, like IBM continues to do for enterprise computing even to this day despite (shamefully) not caring to be at the forefront anymore.

megaman821 3y ago

He kind of hints at one way to be successful with his mention of Azure and private blockchains. If Intel or Boeing are going to use AI to help with design, they are going to have train private custom models from their proprietary data. I am sure there a several other services that enhance the effectiveness of AI that a startup could be based on.

agentultra 3y ago

A lot of these companies also misunderstand their value proposition, the classic, "Uber for X," approach to starting a company. Also known as, "Me too!"

lacker 3y ago

This reminds me of people saying that search engines were doomed as a business in the late 90's. They have no real moat. All you need is to gather all the text on the internet, make an index, and build it on well-known information retrieval algorithms. PageRank was even in a published paper. Well, this was only mostly true. With search engines, there was a "winner-take-all" effect. Yes, many companies could build search engines, but Google was just a little bit better. Once one of the search engines is a little bit better, why would you use anything else? Eventually, Google figured out how to create a real moat, by using click data to improve search result ranking. Even though Microsoft is willing to spend billions of dollars on Bing, they don't have access to Google's user data, and aren't quite able to match Google's search quality. I believe that many AI startups will have a similar "data moat". If you are the first AI company to get a significant amount of users, you may be able to learn from their behavior to improve the product. If you can do this, you'll have an advantage that competitors won't be able to easily copy. So just make something people want, gather data on what your users are doing, and use that data to make your product better. If you do that right, you'll keep growing, and you'll be able to describe this simple strategy as a "proprietary data advantage" to give your slides more buzzwords if you need them.

amelius 3y ago
The article applies to medium and small businesses. For 99% of these businesses, search engines are a doomed endeavor.
willdr 3y ago
Don't worry, Google are hard at work undermining the product they worked so hard to build. Every year google search is worse at surfacing what you're looking for and better at an ads platform, and the advent of LLMs and SEO agencies flooding the internet with no-value regurgitated content is also not helping.
bdcravens 3y ago
Additionally, Google dismissed the trend of other search engines: everyone was building a portal, which for the most part didn't add much value for users. Even today, Google, which is really just an advertising company, has no ads or other content on its main page. (it does have a few internal links on the extreme edges, but has arguably the most white space of any online company)

rvz 3y ago

Those in AI that are not data providers or a source of enormous amount of new private data and access to data centers are doomed. ChatGPT wrappers have a huge platform-risk by the GPT marketplace. The ones that are dependent on VC cash and making little money against open source models or cheaper solutions are going to lose the AI race to zero.

hn_throwaway_99 3y ago

I thought this was a pretty good analysis. And for comments along the lines of "Most start-ups are doomed", the article acknowledges this in the first sentence ("The statement that most AI startups are doomed can be fairly mundane. After all, most startups are doomed, just by the numbers.") but then goes on to make an argument specific to these AI startups. I do, though, believe the author missed a large class of AI startups that I think will likely succeed in the "Wait, so what IS defensible?" section: startups that focus like a laser on very specific, semi-niche workflows where things like UX and compliance are critical. My best example of this so far is Harvey.ai, whose tagline is "Generative AI for Elite Law Firms": 1. First, elite law firms have lots of money to spend, and they'll spend it if they see an ROI. 2. There are plenty of Web 2.0 startups who won primarily because of first-mover advantage. I mean, Docusign wasn't exactly amazing, world-changing technology, but they became synonymous with "legal signatures over the internet" such that they became the default for this use case. 3. Obviously something like "generative AI for elite law firms" has tons of compliance concerns around it. If Harvey.AI can address that, it's a huge wn. As another example, I know of some big financial firms/banks that have giant committees around anything remotely label-able as "AI" because there are so many compliance concerns around AI (a system that gives you an answer with no visibility into how that answer was generated is anathema to the "everything must be auditable" mindset of the financial world). Again, Docusign is a good analogy here, because so much of their initial work was not in tech but ensuring that there was a legal framework (in many jurisdictions) that would deem internet signatures valid. My overall point is that a UX that is highly tailored to specific, profitable use cases can still win out.

__loam 3y ago
I'm biased because I worked in legal tech for a while but I think Harvey is kind of fucked. There's a bunch of cloud native legal startups in the space already that can easily plug in this technology and that already have an established reputation and rapport with existing users.
- hn_throwaway_99 3y ago
  To be clear, I'm not necessarily saying Harvey will be the "winner", but I believe that their will be a winner in the "Legal AI startup" space, and I think this startup will win by having the UX that is best focused on lawyers and addresses lawyers' compliance concerns (not that they will have the best models or tons and tons of data).

bloppe 3y ago

Drop the "AI". It's cleaner.

elhospitaler 3y ago

I think this is mostly true, except I imagine OpenAI has a more defensible head start due to all the user data they've collected from people's queries. If they can maintain their lead in model quality (which is definitely possible - the engineering task of training the best and largest LLMs is not for the faint of heart) and remain the "best" general use chatbot, I could definitely see them build an insurmountable lead with all of their user data.

jeffreyw128 3y ago

This is the dumbest thing I've read in a long time

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toddmorey 3y ago

tldr: most companies on the planet are "doomed to be perfectly ok businesses".

amelius 3y ago

AI developer is the new web developer.

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bdcravens 3y ago

Last year crypto, this year AI, next year...?

jqpabc123 3y ago
And these two have a lot in common. Both consume large amounts of computing resources and energy to produce questionable results.

beefman 3y ago

You can have a moat if you have an app store...

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zombiwoof 3y ago

Does this include porn ai?

axegon_ 3y ago

Well... Yeah. Most startups are doomed by definition. The AI breakthroughs definitely made a lot of people open their pockets. Admittedly a year and a half ago I was banking on a second AI winter - it seemed that we had peaked for the time being. OpenAI changed that and re-opened the gates that were starting to close. Funny thing is we are still recovering from half a decade of "everything-blockchain". While I did say that blockchain was nothing more than a ponzi scheme(and I still stand by this statement), in the realm of AI, I'm not entirely sure what to expect.

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Markleodx 3y ago

Everyone's racing to build their own data moat, but here's the catch: AI tech is moving at lightning speed. Less data, more power. It's like trying to build a castle on quicksand. And then there's the Google effect – they turned 'searching' into 'Googling', basically winning the internet. So, for AI startups, it's not just about gathering data; it's about adapting quickly and carving out your niche before the landscape shifts again. Here's to the brave souls navigating this wild AI terrain!

tinyhouse 3y ago

I like the article but I also disagree with one important assumption that author makes implicitly. It assumes that LLM is all you need so in order to differentiate you need something that others don't have, like health care data. The reality is that for many problems you still need a lot of work to build a quality solution around LLM. Not something that you can build in a weekend.

molave 3y ago

It's just like most bubbles (automaking, 1990s dotcoms, crypto, etc)

nojvek 3y ago

Title should be “Most VC funded AI startups are doomed”. I dunno man, levelsio (Pieter) and Danny his friend are making millions as solopreneurs taking existing models, some light training and adding beautiful frontends to it. You’re right they’re not VC scale but this is what excites me. AI for indiehackers is a massive multiplier. One person million dollars net after tax / year is a phenomenal business. I personally think Statups that raise millions of dollars are doomed. Long live the lean cockroach startups. Midjourney is 100M+ with 10-ish engineers. That’s a phenomenal business. They raised 0 VC.

raztogt21 3y ago
Pieter and Danny businesses are not startups, these are "lifestyle" business. They even say that continuously. They see what's trending and feasible, glue some generative APIs with an okish frontend and publish it. Repeat.

hunterhod 3y ago

I think there are certainly more AI startups than there are viable business models. I still see exceptions like https://cursor.sh https://cursor.sh though. There are people building things that people actually want and who are building brand loyalty.

geniium 3y ago

This is more a clickbait title than anything else. The problem are the same in any buble. AI is a bubble right now. And if you don't create a valid business, brand, etc.. you wont success.

1vuio0pswjnm7 3y ago

Nevermind "AI". Fact is, most startups are doomed. Only small percentage succeed.

eadmund 3y ago

‘This principle runs through most of the AI sector today. There’s going to be a lot of value generated that just accrues to society, and isn’t captured by any private player. Which is wonderful, by the way—this is how technology becomes one of the few “free lunches” we have in society and macroeconomics. ‘There’s also going to be a lot of value generated that is simply captured by existing industry incumbents, using their market power and scale. That’s not a free lunch for society, but is also just how capitalism works and often still generates “surplus” (Econ speak for “good stuff”) for society.’ The first paragraph is also just how capitalism works, and it arguably works better than other systems at generating uncaptured value.