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This is why I strongly suspect that AI will not play out the way the Web did (upstarts unseat giants) and will instead play out like smartphones (giants entrenc

This is why I strongly suspect that AI will not play out the way the Web did (upstarts unseat giants) and will instead play out like smartphones (giants entrench and balloon). If all that matters is what you can put into context, then AI really isn't a product in most cases. The people selling models are actually just selling compute, so that space will be owned by the big clouds. The people selling applications are actually just packaging data, so that space will be owned by the people who already have big data in their segment: the big players in each industry. All competitors at this point know how important data is, and they're not going to sell it to a startup when they could package it up themselves. And most companies will prefer to just use features provided by the B2B companies they already trust, not trust a brand new company with all the same data. I fully expect that almost all of the AI wins will take the form of features embedded in existing products that already have the data (like GitHub with Copilot), not brand new startups who have to try to convince companies to give them all their data for the first time.

master_crab 2y ago
Yup. And it’s already playing out that way. Anthropic, OpenAI, Gemini - technically not an upstart. All have hyperscalers backing and subsidizing their model training (AWS, Azure, GCP, respectively). It’s difficult to discern where the segmentation between compute and models are here.
- alephnerd 2y ago
  > It’s difficult to discern where the segmentation between compute and models are here. Startups can outcompete the Foundational Model companies by concentrating on creating a very domain specific model, and providing support and services that comes out of having expertise in that specific domain. This is why OpenAI chose to co-invest in Cybersecurity startups with Menlo Ventures in 2022 instead of building their own dedicated cybersecurity vertical, because a partnership driven growth model nets the most profit with the least resources expended when trying to expand your TAM into a new and very competitive market like Cybersecurity. This is the same reason why hyperscalers like Microsoft, Amazon, and Google themselves have ownership stakes in the foundational model companies like Anthropic, OpenAI, etc because at Hyperscalers size and revenue, Foundational Models are just a feature (an important feature, but a feature nontheless). Foundational Models are a good first start, but are not 100% perfect in a number of fields and usecases. Ime, tooling built with these models are often used to cut down on headcount by 30-50% for the team using it to solve a specific problem. And this is why domain specific startups still thrive - sales, support, services, etc will still need to be tailored for buyers.
  - master_crab 2y ago
    by concentrating on creating a very domain specific model I don’t disagree with this from an economics perspective (it’s expensive running an FM to handle domain specific queries). But the most accurate domain knowledge always tends to involve internal data. And then it becomes the issue raised above: a people problem involving internal knowledge and data management. Incumbent hyperscalers and vendors like MS, Amazon, etc (and even third party data managers like snowflake) tend to have more leverage when it becomes this type of data problem.
    - fuzzfactor 2y ago
      >Startups can outcompete the Foundational Model companies by concentrating on creating a very domain specific model, and providing support and services that comes out of having expertise in that specific domain. Well-put because the business is focused and to-the-point from the beginning. For those applications where this gets you in the door to the domain, or gets you in sooner, this can be a competitive advantage. I think Lukas is pointing out the longer-term limitations of the approach though. I thought this would extend from 1980s electronics myself. You could edit this however: >Startups can [prosper] by concentrating on creating a very domain specific model, and providing support and services that comes out of having expertise in that specific domain. And it may hold true anyway and you may have a lifetime of work ahead of you whether or not the more-generalized capabilities catch up or not. You don't always have to actually be competitive with capitalized corporations in the market if you are adding real value to begin with, and the sky can still be the limit. >the most accurate domain knowledge always tends to involve internal data. >Incumbent hyperscalers . . . tend to have more leverage when it becomes this type of data That can help as a benchmark to gauge when a person or small team actually can occasionally outperform a billion-dollar corporation in some way or another. I'm no Mr. Burns, but to this I have slowly said to myself "ex-cel-lent" similarly for decades. It's good to watch AI approaches come and go and even better to be adaptable over time.
  - ngneer 2y ago
    All of what you wrote is mostly true, except that "not 100% perfect in a number of fields and usecases" is quite an understatement. You mention the cybersecurity vertical. As a datapoint, I have put the simplest code security analysis question to ChatGPT (4o mini, for those who might say wait until the next one comes out). I made a novel vulnerable function, so that it would have never been seen before. I chose a very simple and easy vulnerability. Scores of security researchers in my vicinity spotted the vulnerability trivially and instantly. ChatGPT was more than useless, failing miserably to perform any meaningful analysis. The above is anecdotal data. Could be that a different tool would perform better. However, even if such models were harnessed by a startup to solve a specific problem, there is absolutely no way for present capabilities to yield a 30-50% HC reduction in this subdomain.
ip26 2y ago
The people selling models are actually just selling compute Yes, fully agreed. Anything AI is discovering in your dataset could have been found by humans, and it could have been done by a more efficient program. But that would require humans to carefully study it and write the program. AI lets you skip the novel analysis of the data and writing custom programs by using a generalizable program that solves those steps for you by expending far more compute. I see it as, AI could remove the most basic obstacle preventing us from applying compute to vast swathes of problems- and that’s the need to write a unique program for the problem at hand.
CharlieDigital 2y ago
> AI will not play out the way the Web did (upstarts unseat giants) Yes, I agree. I recently spoke to a doctor that wanted to do a startup one part of which is an AI agent that can provide consumers second opinions for medical questions. For this to be safe, it will require access to not only patient data, but possibly front line information from content origins like UpToDate because that content is a necessity to provide grounded answers for information that's not in the training set and not publicly available via search. The obvious winner is UpToDate who owns that data and the pipeline for originating more content. If you want to build the best AI agent for medical analysis, you need to work with UpToDate. > ...not brand new startups who have to try to convince companies to give them all their data for the first time. Yes. I think of Microsoft and SharePoint, for example. Enterprises that are using SharePoint for document and content storage have already organized a subset of their information in a way that benefits Microsoft as concerns AI agents that are contextually aware of your internal data.
diggan 2y ago
> will instead play out like smartphones (giants entrench and balloon). Someone correct me if I'm wrong, but didn't smartphones go the "upstarts unseat giants" way? Apple wasn't a phone-maker, and became huge in the phone-market after their launch. Google also wasn't a phone-maker, yet took over the market slowly but surely with their Android purchase. I barely see any Motorola, Blackberry, Nokia or Sony Ericsson phones anymore, yet those were the giants at one time. Now it's all iOS/Android, two "upstarts" initially.
- lolinder 2y ago
  > Now it's all iOS/Android, two "upstarts" initially. They weren't upstarts, they were giants who moved into a new (but tightly related) space and pushed out other companies that were in spaces that at first seemed closely related but actually were more different than first appeared. Android and iOS won because smartphones were actually mobile computers with a cellular chip, not phones with fancy software. Seen that way Apple was obviously not an upstart, they were a giant that grew even further. Google is perhaps somewhat more surprising since they didn't do hardware at all before, but they did have Chrome, giving them a major in on the web platform side, and were also able to leverage their enormous search revenue. Neither resource is available to an upstart/startup.
  - umeshunni 2y ago
    Neither Apple nor Google were giants in 2007.
    - asadotzler 2y ago
      Both were giants in 2007. Google was at peak post-IPO fame and Apple was full steam ahead with Jobs at the helm. They were huge players, far from startups or upstarts.
      - Yoric 2y ago
        Seconded. For context, Google was about to launch Chrome and Apple was about to launch the Windows version of Safari. Both companies were clearly on the offense at the time. (and the parent poster was competing with both :) )
scotty79 2y ago
> All competitors at this point know how important data is, and they're not going to sell it to a startup when they could package it up themselves. Except they won't package it themselves because they are inept and inert. They still won't sell it to startups though.

master_crab 2y ago

Yup. And it’s already playing out that way. Anthropic, OpenAI, Gemini - technically not an upstart. All have hyperscalers backing and subsidizing their model training (AWS, Azure, GCP, respectively). It’s difficult to discern where the segmentation between compute and models are here.

alephnerd 2y ago
> It’s difficult to discern where the segmentation between compute and models are here. Startups can outcompete the Foundational Model companies by concentrating on creating a very domain specific model, and providing support and services that comes out of having expertise in that specific domain. This is why OpenAI chose to co-invest in Cybersecurity startups with Menlo Ventures in 2022 instead of building their own dedicated cybersecurity vertical, because a partnership driven growth model nets the most profit with the least resources expended when trying to expand your TAM into a new and very competitive market like Cybersecurity. This is the same reason why hyperscalers like Microsoft, Amazon, and Google themselves have ownership stakes in the foundational model companies like Anthropic, OpenAI, etc because at Hyperscalers size and revenue, Foundational Models are just a feature (an important feature, but a feature nontheless). Foundational Models are a good first start, but are not 100% perfect in a number of fields and usecases. Ime, tooling built with these models are often used to cut down on headcount by 30-50% for the team using it to solve a specific problem. And this is why domain specific startups still thrive - sales, support, services, etc will still need to be tailored for buyers.
- master_crab 2y ago
  by concentrating on creating a very domain specific model I don’t disagree with this from an economics perspective (it’s expensive running an FM to handle domain specific queries). But the most accurate domain knowledge always tends to involve internal data. And then it becomes the issue raised above: a people problem involving internal knowledge and data management. Incumbent hyperscalers and vendors like MS, Amazon, etc (and even third party data managers like snowflake) tend to have more leverage when it becomes this type of data problem.
  - fuzzfactor 2y ago
    >Startups can outcompete the Foundational Model companies by concentrating on creating a very domain specific model, and providing support and services that comes out of having expertise in that specific domain. Well-put because the business is focused and to-the-point from the beginning. For those applications where this gets you in the door to the domain, or gets you in sooner, this can be a competitive advantage. I think Lukas is pointing out the longer-term limitations of the approach though. I thought this would extend from 1980s electronics myself. You could edit this however: >Startups can [prosper] by concentrating on creating a very domain specific model, and providing support and services that comes out of having expertise in that specific domain. And it may hold true anyway and you may have a lifetime of work ahead of you whether or not the more-generalized capabilities catch up or not. You don't always have to actually be competitive with capitalized corporations in the market if you are adding real value to begin with, and the sky can still be the limit. >the most accurate domain knowledge always tends to involve internal data. >Incumbent hyperscalers . . . tend to have more leverage when it becomes this type of data That can help as a benchmark to gauge when a person or small team actually can occasionally outperform a billion-dollar corporation in some way or another. I'm no Mr. Burns, but to this I have slowly said to myself "ex-cel-lent" similarly for decades. It's good to watch AI approaches come and go and even better to be adaptable over time.
- ngneer 2y ago
  All of what you wrote is mostly true, except that "not 100% perfect in a number of fields and usecases" is quite an understatement. You mention the cybersecurity vertical. As a datapoint, I have put the simplest code security analysis question to ChatGPT (4o mini, for those who might say wait until the next one comes out). I made a novel vulnerable function, so that it would have never been seen before. I chose a very simple and easy vulnerability. Scores of security researchers in my vicinity spotted the vulnerability trivially and instantly. ChatGPT was more than useless, failing miserably to perform any meaningful analysis. The above is anecdotal data. Could be that a different tool would perform better. However, even if such models were harnessed by a startup to solve a specific problem, there is absolutely no way for present capabilities to yield a 30-50% HC reduction in this subdomain.

ip26 2y ago

The people selling models are actually just selling compute Yes, fully agreed. Anything AI is discovering in your dataset could have been found by humans, and it could have been done by a more efficient program. But that would require humans to carefully study it and write the program. AI lets you skip the novel analysis of the data and writing custom programs by using a generalizable program that solves those steps for you by expending far more compute. I see it as, AI could remove the most basic obstacle preventing us from applying compute to vast swathes of problems- and that’s the need to write a unique program for the problem at hand.

CharlieDigital 2y ago

> AI will not play out the way the Web did (upstarts unseat giants) Yes, I agree. I recently spoke to a doctor that wanted to do a startup one part of which is an AI agent that can provide consumers second opinions for medical questions. For this to be safe, it will require access to not only patient data, but possibly front line information from content origins like UpToDate because that content is a necessity to provide grounded answers for information that's not in the training set and not publicly available via search. The obvious winner is UpToDate who owns that data and the pipeline for originating more content. If you want to build the best AI agent for medical analysis, you need to work with UpToDate. > ...not brand new startups who have to try to convince companies to give them all their data for the first time. Yes. I think of Microsoft and SharePoint, for example. Enterprises that are using SharePoint for document and content storage have already organized a subset of their information in a way that benefits Microsoft as concerns AI agents that are contextually aware of your internal data.

diggan 2y ago

> will instead play out like smartphones (giants entrench and balloon). Someone correct me if I'm wrong, but didn't smartphones go the "upstarts unseat giants" way? Apple wasn't a phone-maker, and became huge in the phone-market after their launch. Google also wasn't a phone-maker, yet took over the market slowly but surely with their Android purchase. I barely see any Motorola, Blackberry, Nokia or Sony Ericsson phones anymore, yet those were the giants at one time. Now it's all iOS/Android, two "upstarts" initially.

lolinder 2y ago
> Now it's all iOS/Android, two "upstarts" initially. They weren't upstarts, they were giants who moved into a new (but tightly related) space and pushed out other companies that were in spaces that at first seemed closely related but actually were more different than first appeared. Android and iOS won because smartphones were actually mobile computers with a cellular chip, not phones with fancy software. Seen that way Apple was obviously not an upstart, they were a giant that grew even further. Google is perhaps somewhat more surprising since they didn't do hardware at all before, but they did have Chrome, giving them a major in on the web platform side, and were also able to leverage their enormous search revenue. Neither resource is available to an upstart/startup.
- umeshunni 2y ago
  Neither Apple nor Google were giants in 2007.
  - asadotzler 2y ago
    Both were giants in 2007. Google was at peak post-IPO fame and Apple was full steam ahead with Jobs at the helm. They were huge players, far from startups or upstarts.
    - Yoric 2y ago
      Seconded. For context, Google was about to launch Chrome and Apple was about to launch the Windows version of Safari. Both companies were clearly on the offense at the time. (and the parent poster was competing with both :) )

scotty79 2y ago

> All competitors at this point know how important data is, and they're not going to sell it to a startup when they could package it up themselves. Except they won't package it themselves because they are inept and inert. They still won't sell it to startups though.