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What's the catch? How do they plan to make money out of it? Or maybe the plan is to use the massive amount of data gathered to make it better for e.g. Bing sear

What's the catch? How do they plan to make money out of it? Or maybe the plan is to use the massive amount of data gathered to make it better for e.g. Bing search? Cut out the competition before it has a chance to flourish? Companies, especially giant publicly traded ones like MS (the de facto owner of OpenAI) don't give out freebies.

overcast 4y ago
The API is a paid service, like all the other APIs.
- alpark3 4y ago
  I believe his underlying assumption is that the API is so cheap that there's no way they're making money off of it. Yes it's paid, but doesn't matter if they're losing money on every API call.
- ianmcgowan 4y ago
  If they're selling below cost, it doesn't matter. When you're selling a dollar for 90 cents, it's hard to make up for that in volume.
  - scottLobster 4y ago
    It's not like there are individual units of ChatGPT. With enough subscribers they could sell it for 1 cent per month and profit.
    - supermatt 4y ago
      Not sure what you mean by “individual units” but the suggestion is that it costs more than they charge. i.e it’s not profitable, and the more they sell the more they lose.
      - scottLobster 4y ago
        My point was "making it up on volume" is largely irrelevant when it comes to mass market web-apps. Costs are relatively fixed outside of infrastructure, and potential customers are any number up to and including the internet-connected population of the world. The marginal cost of a new subscription is way less than they charge. The more they sell the less they lose, even if they're still losing overall to gain market-share.
        pixl97 4y ago
        This depends on the compute power quantum stepping.... That is what is the upgrade cost to expand capacity as new customers are added. If for example adding 1 million new users requires $200,000k in hardware expenditure and $20k in yearly power expenditure, but your first year return on those customers is only going to be $50k, you're in a massive money losing endeavor. The point here is we really don't know the running and upkeep costs of these models at this point.
        supermatt 4y ago
        ChatGPT isnt a web-app. It takes serious hardware to run the model. More users means more hardware. If they are charging per token (which they are) then the costs will scale linearly with usage, given 100% usage per node. Anything less than 100% is an even greater loss.
chessgecko 4y ago
People are speculating that gpt3.5 turbo is actually much smaller and that they are very likely currently making a profit on it. It seems likely just given how quickly some of the 3.5 turbo responses are from the api, and how much they push users to it. I haven't seen any really compelling theories of how they did it though, just the results...
- ethbr0 4y ago
  They wouldn't be the first business to have showroom halo products to attract customers, who instead but more profitable mass-market products. Auto industry 101.
deeviant 4y ago
I don't know why everybody is asking themselves why they are offering it so cheaply, it seems rather obvious: 1. Get near every company to jump on the hype train and integrate openai api into their processes. 2. Get overwhelming market share. 3. Slowly reduce costs by increasing model and computation efficiency and raise prices. 4. Profit.
- theturtletalks 4y ago
  Step 3 also includes raising prices once people have integrated the API. Google Maps was the "easy" and "cheap" way of integrating maps into apps until they got almost all the market share and raised prices through the roof.
- sacred_numbers 4y ago
  Alternatively: 1. Quickly reduce costs by increasing model and computation efficiency. 2. Massively reduce prices while still maintaining some gross margin. 3. Massively increase market size and take the vast majority of market share. 4. End up with a higher gross profit due to a much larger market size despite decreasing prices and gross margins. 5. Profit.
- ChatGTP 4y ago
  I find it hard people can’t see that will be the play?
swatcoder 4y ago
The wildly successful public buzz draws internal and external money towards the project. Outsiders now see Microsoft as freshly repositioned against Google, and OpenAI as a rising rocket; internal budget is likewise drawn to related endeavors because everybody wants to claim a piece of whatever hits big. Meanwhile, yes, the preview provides both training data for the tooling, which has engineering value in AI, and usage data into how users think about this technology and what they intuitively want to do with it, which helps guide future product development. Both these reasons are also why they’re (1) being so careful to avoid scandal, and (2) being very slow to clear up public misconceptions. An safe, excited public that’s fully engaged with the tool (even if misusing and misunderstanding it) is worth a ton of money to them right now and so has plenty of justification to absorb investment. It won’t last forever, but a new innovation door seems to have opened and we’ll probably see this pattern a lot for a while.
waboremo 4y ago
Yes your second guess is accurate. They will be changing pricing down the line when enough of the market is captured and competitors have been deterred. Most notably, Microsoft's largest competitor: Google.
bakugo 4y ago
They'll hike up the price by 10x once enough companies are relying on it to do business.
- politician 4y ago
  We'll see AWS step in at that point with their own product offering.
nico 4y ago
This is a market grab. They are moving fast to capture the market. Being cheap allows them to capture the market faster. The main customers won’t be end users of ChatGPT directly, but instead companies with a lot of data and documents that are already integrating the apis with their systems. Once companies have integrated their services with OpenAIs apis, they are unlikely to switch in the future. Unless of course something revolutionary happens again.
- riku_iki 4y ago
  > their services with OpenAIs apis, they are unlikely to switch in the future. why is that? If competitor release better or cheaper LLM, it is not that hard to switch API calls..
  - nico 4y ago
    Sure, that’s the case if all your software does is make a couple of api calls and you have very few stake holders. But when you have built a big service around an external api, you have thousands or millions of users and thousands of employees - replacing an api is not just a big technical project, it’s also a huge internal political issue for the organization to rally the necessary teams to make the changes. People hate change, they actively resist it. The current environment is forcing companies to adapt and adopt the new technologies. But once they’ve done it, they’ll need an even bigger reason to switch apis.
- potatolicious 4y ago
  > "Being cheap allows them to capture the market faster." I think it's worth remarking that this is IMO a smarter way of using price to capture market than what we've seen in the post decade (see: Uber, DoorDash) - in OpenAI's case there's every reasonable expectation that they can drop their operating costs well below the low prices they're offering, so if they are running in the red the expectation of temporariness is reasonable. What was unreasonable about the past tech cycle is that a lot of the expectations of cost reduction a) never panned out, and b) if subjected to even slight scrutiny would never have reasonably panned out. OpenAI has direct line-of-sight to getting these models dramatically cheaper to run than now, and that's a huge benefit. That said I remain a bit skeptical about the market overall here - I think the tech here is legitimately groundbreaking, but there are a few forces working against this as a profitable product: - Open source models and weights are catching up very rapidly. If the secret sauce is sheer scale, this will be replicated quickly (and IMO is happening). Do users need ChatGPT or do they need any decently-sized LLM? - Productization seems like it will largely benefit incumbent large players (see: Microsoft, Google) who can afford to tank the operating costs and additional R&D required on top to productize. Those players are also most able to train their own LLMs and operate them directly, removing the need for a third party provider. It seems likely to me that this will break in three directions (and likely a mixture of them): - Big players train their own LLMs and operate them directly on their own hardware, and do not do business with OpenAI at any significant volume. - Small players lean towards undifferentiated LLMs that are open source and run on standard cloud configurations. - Small players lean towards proprietary, but non-OpenAI LLMs. There's no particular reason why GCP and AWS cannot offer a similar product and undercut OpenAI.
m3kw9 4y ago
OpenAI wins by innovating faster than everyone because a lot of these models inner workings are known and can be trained to meet ChatGPTs metrics. so all they have to do is hire the best and move faster, as long as they have on par or better, people won’t be switching
dragonwriter 4y ago
> What’s the catch? The catch is its a tactic to discourage investment in competing technologies, enabling OpenAI to build their lead to the point it is insurmountable. > How do they plan to make money out of it? Altman’s publicly-stated plan for making money from OpenAI is (I’m completely serious) [0]: (1) Develop Artificial General Intelligence under the control of OpenAI. (2) Direct the AGI to find a way to make a return for investors. [0] https://techcrunch.com/2019/05/18/sam-altmans-leap-of-faith/ https://techcrunch.com/2019/05/18/sam-altmans-leap-of-faith/
- guiriduro 4y ago
  That idea might actually work. If a startup is a build-measure-learn loop, then coming up with ballpark viable ideas, devising experiments to test them and optimising for traction/profit should be a cinch for AGI. So just train it to build a business for itself.
- throwwwaway69 4y ago
  #2 is sort of silly. There's endless use cases for a superhuman intelligence to make billions of dollars. Just the application into medicine and drug development would create trillions of dollars of value and completely change the world. Illness as we know it could potentially disappear, treatment could be nearly free, we'd never need to run real world clinical trials ever again, etc.
  - logicchains 4y ago
    >Illness as we know it could potentially disappear, treatment could be nearly free, we'd never need to run real world clinical trials ever again, etc This is magical thinking. Real physical science and experiments will always be necessary until we have the computational power to simulate the physical body completely, something which would require exponentially more computational power than an AGI is expected to need. Plus, fundamentally in nature there are many "chaotic" processes that are impossible to accurately simulate more than a few seconds ahead due to the amount of computation required growing exponentially with simulation duration.
sebzim4500 4y ago
It's also possible they have found a way to run the model extremely cheaply. To be fair, there has been many improvements to transformer inference since they initally set their prices (most notably flash attention), so if they were barely making a profit back then they could still be making a profit now. That's a big if, however, and no one really will give you figures on exactly what this costs at scale. Especially since we don't know for a fact how big GPT-3.5-turbo actually is.
sourcecodeplz 4y ago
There is plenty of money from the 2012 - 2020 meteoric period that has not been spent yet. If I had plenty of money I would bet on Microsoft and OpenAI, as I am sure others are doing already. Thus they have enough to sustain this growth.

overcast 4y ago

The API is a paid service, like all the other APIs.

alpark3 4y ago
I believe his underlying assumption is that the API is so cheap that there's no way they're making money off of it. Yes it's paid, but doesn't matter if they're losing money on every API call.
ianmcgowan 4y ago
If they're selling below cost, it doesn't matter. When you're selling a dollar for 90 cents, it's hard to make up for that in volume.
- scottLobster 4y ago
  It's not like there are individual units of ChatGPT. With enough subscribers they could sell it for 1 cent per month and profit.
  - supermatt 4y ago
    Not sure what you mean by “individual units” but the suggestion is that it costs more than they charge. i.e it’s not profitable, and the more they sell the more they lose.
    - scottLobster 4y ago
      My point was "making it up on volume" is largely irrelevant when it comes to mass market web-apps. Costs are relatively fixed outside of infrastructure, and potential customers are any number up to and including the internet-connected population of the world. The marginal cost of a new subscription is way less than they charge. The more they sell the less they lose, even if they're still losing overall to gain market-share.
      - pixl97 4y ago
        This depends on the compute power quantum stepping.... That is what is the upgrade cost to expand capacity as new customers are added. If for example adding 1 million new users requires $200,000k in hardware expenditure and $20k in yearly power expenditure, but your first year return on those customers is only going to be $50k, you're in a massive money losing endeavor. The point here is we really don't know the running and upkeep costs of these models at this point.
      - supermatt 4y ago
        ChatGPT isnt a web-app. It takes serious hardware to run the model. More users means more hardware. If they are charging per token (which they are) then the costs will scale linearly with usage, given 100% usage per node. Anything less than 100% is an even greater loss.

chessgecko 4y ago

People are speculating that gpt3.5 turbo is actually much smaller and that they are very likely currently making a profit on it. It seems likely just given how quickly some of the 3.5 turbo responses are from the api, and how much they push users to it. I haven't seen any really compelling theories of how they did it though, just the results...

ethbr0 4y ago
They wouldn't be the first business to have showroom halo products to attract customers, who instead but more profitable mass-market products. Auto industry 101.

deeviant 4y ago

I don't know why everybody is asking themselves why they are offering it so cheaply, it seems rather obvious: 1. Get near every company to jump on the hype train and integrate openai api into their processes. 2. Get overwhelming market share. 3. Slowly reduce costs by increasing model and computation efficiency and raise prices. 4. Profit.

theturtletalks 4y ago
Step 3 also includes raising prices once people have integrated the API. Google Maps was the "easy" and "cheap" way of integrating maps into apps until they got almost all the market share and raised prices through the roof.
sacred_numbers 4y ago
Alternatively: 1. Quickly reduce costs by increasing model and computation efficiency. 2. Massively reduce prices while still maintaining some gross margin. 3. Massively increase market size and take the vast majority of market share. 4. End up with a higher gross profit due to a much larger market size despite decreasing prices and gross margins. 5. Profit.
ChatGTP 4y ago
I find it hard people can’t see that will be the play?

swatcoder 4y ago

The wildly successful public buzz draws internal and external money towards the project. Outsiders now see Microsoft as freshly repositioned against Google, and OpenAI as a rising rocket; internal budget is likewise drawn to related endeavors because everybody wants to claim a piece of whatever hits big. Meanwhile, yes, the preview provides both training data for the tooling, which has engineering value in AI, and usage data into how users think about this technology and what they intuitively want to do with it, which helps guide future product development. Both these reasons are also why they’re (1) being so careful to avoid scandal, and (2) being very slow to clear up public misconceptions. An safe, excited public that’s fully engaged with the tool (even if misusing and misunderstanding it) is worth a ton of money to them right now and so has plenty of justification to absorb investment. It won’t last forever, but a new innovation door seems to have opened and we’ll probably see this pattern a lot for a while.

waboremo 4y ago

Yes your second guess is accurate. They will be changing pricing down the line when enough of the market is captured and competitors have been deterred. Most notably, Microsoft's largest competitor: Google.

bakugo 4y ago

They'll hike up the price by 10x once enough companies are relying on it to do business.

politician 4y ago
We'll see AWS step in at that point with their own product offering.

nico 4y ago

This is a market grab. They are moving fast to capture the market. Being cheap allows them to capture the market faster. The main customers won’t be end users of ChatGPT directly, but instead companies with a lot of data and documents that are already integrating the apis with their systems. Once companies have integrated their services with OpenAIs apis, they are unlikely to switch in the future. Unless of course something revolutionary happens again.

riku_iki 4y ago
> their services with OpenAIs apis, they are unlikely to switch in the future. why is that? If competitor release better or cheaper LLM, it is not that hard to switch API calls..
- nico 4y ago
  Sure, that’s the case if all your software does is make a couple of api calls and you have very few stake holders. But when you have built a big service around an external api, you have thousands or millions of users and thousands of employees - replacing an api is not just a big technical project, it’s also a huge internal political issue for the organization to rally the necessary teams to make the changes. People hate change, they actively resist it. The current environment is forcing companies to adapt and adopt the new technologies. But once they’ve done it, they’ll need an even bigger reason to switch apis.
potatolicious 4y ago
> "Being cheap allows them to capture the market faster." I think it's worth remarking that this is IMO a smarter way of using price to capture market than what we've seen in the post decade (see: Uber, DoorDash) - in OpenAI's case there's every reasonable expectation that they can drop their operating costs well below the low prices they're offering, so if they are running in the red the expectation of temporariness is reasonable. What was unreasonable about the past tech cycle is that a lot of the expectations of cost reduction a) never panned out, and b) if subjected to even slight scrutiny would never have reasonably panned out. OpenAI has direct line-of-sight to getting these models dramatically cheaper to run than now, and that's a huge benefit. That said I remain a bit skeptical about the market overall here - I think the tech here is legitimately groundbreaking, but there are a few forces working against this as a profitable product: - Open source models and weights are catching up very rapidly. If the secret sauce is sheer scale, this will be replicated quickly (and IMO is happening). Do users need ChatGPT or do they need any decently-sized LLM? - Productization seems like it will largely benefit incumbent large players (see: Microsoft, Google) who can afford to tank the operating costs and additional R&D required on top to productize. Those players are also most able to train their own LLMs and operate them directly, removing the need for a third party provider. It seems likely to me that this will break in three directions (and likely a mixture of them): - Big players train their own LLMs and operate them directly on their own hardware, and do not do business with OpenAI at any significant volume. - Small players lean towards undifferentiated LLMs that are open source and run on standard cloud configurations. - Small players lean towards proprietary, but non-OpenAI LLMs. There's no particular reason why GCP and AWS cannot offer a similar product and undercut OpenAI.

m3kw9 4y ago

OpenAI wins by innovating faster than everyone because a lot of these models inner workings are known and can be trained to meet ChatGPTs metrics. so all they have to do is hire the best and move faster, as long as they have on par or better, people won’t be switching

dragonwriter 4y ago

> What’s the catch? The catch is its a tactic to discourage investment in competing technologies, enabling OpenAI to build their lead to the point it is insurmountable. > How do they plan to make money out of it? Altman’s publicly-stated plan for making money from OpenAI is (I’m completely serious) [0]: (1) Develop Artificial General Intelligence under the control of OpenAI. (2) Direct the AGI to find a way to make a return for investors. [0] https://techcrunch.com/2019/05/18/sam-altmans-leap-of-faith/ https://techcrunch.com/2019/05/18/sam-altmans-leap-of-faith/

guiriduro 4y ago
That idea might actually work. If a startup is a build-measure-learn loop, then coming up with ballpark viable ideas, devising experiments to test them and optimising for traction/profit should be a cinch for AGI. So just train it to build a business for itself.
throwwwaway69 4y ago
#2 is sort of silly. There's endless use cases for a superhuman intelligence to make billions of dollars. Just the application into medicine and drug development would create trillions of dollars of value and completely change the world. Illness as we know it could potentially disappear, treatment could be nearly free, we'd never need to run real world clinical trials ever again, etc.
- logicchains 4y ago
  >Illness as we know it could potentially disappear, treatment could be nearly free, we'd never need to run real world clinical trials ever again, etc This is magical thinking. Real physical science and experiments will always be necessary until we have the computational power to simulate the physical body completely, something which would require exponentially more computational power than an AGI is expected to need. Plus, fundamentally in nature there are many "chaotic" processes that are impossible to accurately simulate more than a few seconds ahead due to the amount of computation required growing exponentially with simulation duration.

sebzim4500 4y ago

It's also possible they have found a way to run the model extremely cheaply. To be fair, there has been many improvements to transformer inference since they initally set their prices (most notably flash attention), so if they were barely making a profit back then they could still be making a profit now. That's a big if, however, and no one really will give you figures on exactly what this costs at scale. Especially since we don't know for a fact how big GPT-3.5-turbo actually is.

sourcecodeplz 4y ago

There is plenty of money from the 2012 - 2020 meteoric period that has not been spent yet. If I had plenty of money I would bet on Microsoft and OpenAI, as I am sure others are doing already. Thus they have enough to sustain this growth.