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Genuine question … What business are you in when selling AI/ML? I’m far from being knowledgeable in this space, but it seems like AI/ML “is a feature, not a pr

Genuine question … What business are you in when selling AI/ML? I’m far from being knowledgeable in this space, but it seems like AI/ML “is a feature, not a product”. And if that’s the case, what business are you in when a company sells AI/ML? Are you in the business of licensing the model you created? Charging for the output? Hosting infrastructure? What exactly are you in the business to sell? To use an analogy, if you’re selling AI/ML, are you in the IaaS industry, PaaS industry, SaaS industry (or something else?)

tilne 3y ago
Aren’t you in all of those? The further you keep the user away from training and hosting, the less you’re in those businesses. But I would think it’s only economical to do that if you have some type of advantage in implementing the things you’re abstracting away.
- traveler1 3y ago
  I think the opposite may be true. If you control the training and hosting, surely that means you have to be more involved in many industries to make the product useful? Whereas with offloading training/tuning to the user, you kinda just become PaaS, in that you provide a platform which enables others.
nemo44x 3y ago
They are selling picks and shovels. There will be a few huge winners in the AI space, a good amount of modest winners, and a lot of losers. They don't care who wins or loses but are happy to sell the supplies needed for anyone that wants to take a shot. If they can make it easier and worthwhile to use their product and create business value, then they will sell a lot of picks and shovels.
- 1letterunixname 3y ago
  Yep. Meta is spending $22 B on CapEx over 2 years without any plan of how to use it, with about half of it tied to buying shit tons of H100 to go in custom servers.
- version_five 3y ago
  I agree and so far I think it's picks and shovels all the way down. Most of the "AI" companies I see sell tooling, often to "help your AI team work faster|better|spend less time doing x|whatever. It all presupposes there are end uses, which are few and far between, certainly almost none are being sold. AI is still in the hype mode of companies having internal budget to "invest in AI" and so that's who the AI companies are targeting, as opposed to actually making products that do something. See also blockchain wallet companies. PS - I'm optimistic about AI, but it's important to be realistic about the current state of the industry
  - nemo44x 3y ago
    Indeed, lots of tooling out there. Which makes sense as it's very early days. I imagine that LLM AI will be integrated into so many things down the road though that it will be an expected feature of most any product.
  - calebkaiser 3y ago
    It's important to note that despite the recent excitement about LLMs, which is still an emerging technology, "AI" is not a new market by any means, nor are major companies only now investing in it. For the better part of a decade, ML has been widely adopted across industries, and the average person uses an "AI" system many times in a given day. For example, if you open the home screen on the average smartphone right now, you'll see apps like: - Delivery apps like Uber, Lyft, etc., whose recommendations, ETA predictions, driver matching, and more are built on ML. - Media apps like YouTube, Netflix, etc., all of whom rely on models for recommendations. - Email apps like Gmail, whose filtering (both spam and categorization) and text completion are based on ML. - Photo apps like Instagram, Snapchat, and even your phone's basic Camera app, all of which use computer vision. If you Google anything, you're perusing the output of a model. If you're being recommended something on basically any platform, you're interacting with ML. If you ever use speech-to-text, you're using a neural network. Your bank uses ML for fraud detection, your posts on social media are moderated by ML-based content moderation, and if you have a car with any recent-ish sort of lane departure assistance, you're driving with help from a neural network. Most of these companies have large, mature ML teams, whose outputs represent massive amounts of revenue. Hence, they represent a legitimate market for selling picks and shovels.
- alberth 3y ago
  Picks and shovels are tools. But what “tools” are being sold for AI/ML? - A model isn’t a tool, that’s a purpose built offering that can be used for 1 use case. Tools are by definition, intended to help with broad/general use cases. - Hosting isn’t a tool, it’s a commodity and lots of cloud players already occupy that space. Please don’t take my comments as trolling, I just geninuely don’t understand what exactly is being sold that is new or unique that doesn’t already exist.
  - nemo44x 3y ago
    They have a suite of software you can use to power your own software. These are tools and no different than what database vendors, etc in terms of being software you use to build software. In addition there’s support and services. I imagine they have big plans on how to expand and grow the business.
emmender1 3y ago
you are: a) a hardware vendor nvidia/amd whose products are needed by anyone in the game b) you have a captive customer base already ( microsoft, salesforce, servicenow, adobe) to whom you can sell ai/ml value adds c) you make money via ads (google facebook) and ai/ml helps with better targeting everyone else is pissing away VC money.
- htrp 3y ago
  > a) a hardware vendor nvidia whose products are needed by anyone in the game FTFY.... I don't think AMD will be competitive in AI until at least 2025, though given their broken roadmap promises, not sure if anyone will be willing to invest in them
  - unmole 3y ago
    I mean you still need CPUs to run your workloads. And AMD makes decent ones. I work for a company that sells data centre network switches. There's nothing AI specific in our boxes but we will sell a lot more if them if people are building more data centres to cater to AI driven demand. Something, something gold rush, shovels.
    - htrp 3y ago
      Great point! But while demand for network switches explodes, do you really get a competitive advantage from one company's switches vs another? (serious question as I've never had to build a DGX superpod or anything like it from scratch).
      - unmole 3y ago
        > do you really get a competitive advantage from one company's switches vs another? I am obviously biased but IMHO, yes. High end switches are not commodity gear. And a lot of the differentiating secret sauce is in software. So, even if two switches from two different vendors have the same silicon, they might have dramatically different characteristics. That is without going into other aspects like integration with the rest of the stack, quality of support and even lead times.
stevofolife 3y ago
To be fair, I don't think there are clear dichotomies in this space. It really has the potential to be a feature or a product in either of the IaaS/PaaS/SaaS industry. Just do a quick HN search on companies selling AI/ML, you will see what I mean.
PeterisP 3y ago
I believe that some of the most valuable short-term use cases for AI/ML seem to be "feature, not a product" - this means that the incumbents making various products can unlock lots of competitive value by adding those features in a way that is difficult for newcomers, because they not only need to develop the AI/ML feature but also have to build a competitive solution for the core system which generates or contains the data on which the feature relies. Like, it's plausible that many organizations would be willing to pay lots of money for a "ChatGPT which knows my internal documents" AI/ML feature for the Sharepoint/Confluence/etc they are currently using, but a would be very wary of migrating those internal documents to some upcoming startups' new document management system.

tilne 3y ago

Aren’t you in all of those? The further you keep the user away from training and hosting, the less you’re in those businesses. But I would think it’s only economical to do that if you have some type of advantage in implementing the things you’re abstracting away.

traveler1 3y ago
I think the opposite may be true. If you control the training and hosting, surely that means you have to be more involved in many industries to make the product useful? Whereas with offloading training/tuning to the user, you kinda just become PaaS, in that you provide a platform which enables others.

nemo44x 3y ago

They are selling picks and shovels. There will be a few huge winners in the AI space, a good amount of modest winners, and a lot of losers. They don't care who wins or loses but are happy to sell the supplies needed for anyone that wants to take a shot. If they can make it easier and worthwhile to use their product and create business value, then they will sell a lot of picks and shovels.

1letterunixname 3y ago
Yep. Meta is spending $22 B on CapEx over 2 years without any plan of how to use it, with about half of it tied to buying shit tons of H100 to go in custom servers.
version_five 3y ago
I agree and so far I think it's picks and shovels all the way down. Most of the "AI" companies I see sell tooling, often to "help your AI team work faster|better|spend less time doing x|whatever. It all presupposes there are end uses, which are few and far between, certainly almost none are being sold. AI is still in the hype mode of companies having internal budget to "invest in AI" and so that's who the AI companies are targeting, as opposed to actually making products that do something. See also blockchain wallet companies. PS - I'm optimistic about AI, but it's important to be realistic about the current state of the industry
- nemo44x 3y ago
  Indeed, lots of tooling out there. Which makes sense as it's very early days. I imagine that LLM AI will be integrated into so many things down the road though that it will be an expected feature of most any product.
- calebkaiser 3y ago
  It's important to note that despite the recent excitement about LLMs, which is still an emerging technology, "AI" is not a new market by any means, nor are major companies only now investing in it. For the better part of a decade, ML has been widely adopted across industries, and the average person uses an "AI" system many times in a given day. For example, if you open the home screen on the average smartphone right now, you'll see apps like: - Delivery apps like Uber, Lyft, etc., whose recommendations, ETA predictions, driver matching, and more are built on ML. - Media apps like YouTube, Netflix, etc., all of whom rely on models for recommendations. - Email apps like Gmail, whose filtering (both spam and categorization) and text completion are based on ML. - Photo apps like Instagram, Snapchat, and even your phone's basic Camera app, all of which use computer vision. If you Google anything, you're perusing the output of a model. If you're being recommended something on basically any platform, you're interacting with ML. If you ever use speech-to-text, you're using a neural network. Your bank uses ML for fraud detection, your posts on social media are moderated by ML-based content moderation, and if you have a car with any recent-ish sort of lane departure assistance, you're driving with help from a neural network. Most of these companies have large, mature ML teams, whose outputs represent massive amounts of revenue. Hence, they represent a legitimate market for selling picks and shovels.
alberth 3y ago
Picks and shovels are tools. But what “tools” are being sold for AI/ML? - A model isn’t a tool, that’s a purpose built offering that can be used for 1 use case. Tools are by definition, intended to help with broad/general use cases. - Hosting isn’t a tool, it’s a commodity and lots of cloud players already occupy that space. Please don’t take my comments as trolling, I just geninuely don’t understand what exactly is being sold that is new or unique that doesn’t already exist.
- nemo44x 3y ago
  They have a suite of software you can use to power your own software. These are tools and no different than what database vendors, etc in terms of being software you use to build software. In addition there’s support and services. I imagine they have big plans on how to expand and grow the business.

emmender1 3y ago

you are: a) a hardware vendor nvidia/amd whose products are needed by anyone in the game b) you have a captive customer base already ( microsoft, salesforce, servicenow, adobe) to whom you can sell ai/ml value adds c) you make money via ads (google facebook) and ai/ml helps with better targeting everyone else is pissing away VC money.

htrp 3y ago
> a) a hardware vendor nvidia whose products are needed by anyone in the game FTFY.... I don't think AMD will be competitive in AI until at least 2025, though given their broken roadmap promises, not sure if anyone will be willing to invest in them
- unmole 3y ago
  I mean you still need CPUs to run your workloads. And AMD makes decent ones. I work for a company that sells data centre network switches. There's nothing AI specific in our boxes but we will sell a lot more if them if people are building more data centres to cater to AI driven demand. Something, something gold rush, shovels.
  - htrp 3y ago
    Great point! But while demand for network switches explodes, do you really get a competitive advantage from one company's switches vs another? (serious question as I've never had to build a DGX superpod or anything like it from scratch).
    - unmole 3y ago
      > do you really get a competitive advantage from one company's switches vs another? I am obviously biased but IMHO, yes. High end switches are not commodity gear. And a lot of the differentiating secret sauce is in software. So, even if two switches from two different vendors have the same silicon, they might have dramatically different characteristics. That is without going into other aspects like integration with the rest of the stack, quality of support and even lead times.

stevofolife 3y ago

To be fair, I don't think there are clear dichotomies in this space. It really has the potential to be a feature or a product in either of the IaaS/PaaS/SaaS industry. Just do a quick HN search on companies selling AI/ML, you will see what I mean.

PeterisP 3y ago

I believe that some of the most valuable short-term use cases for AI/ML seem to be "feature, not a product" - this means that the incumbents making various products can unlock lots of competitive value by adding those features in a way that is difficult for newcomers, because they not only need to develop the AI/ML feature but also have to build a competitive solution for the core system which generates or contains the data on which the feature relies. Like, it's plausible that many organizations would be willing to pay lots of money for a "ChatGPT which knows my internal documents" AI/ML feature for the Sharepoint/Confluence/etc they are currently using, but a would be very wary of migrating those internal documents to some upcoming startups' new document management system.