4 ms·

I remember when Amazon was going to go broke every year for over a decade. Until they didn't.

by robomartin 2mo ago

lelanthran 2mo ago
I remember when hundreds of dotcom companies were going to go broke, and they all did. Not sure what your point is.
- robomartin 2mo ago
  Simple: None of us have a crystal ball. Trying to predict the future is foolish. I am not saying that what we are seeing might not be problematic. I am only saying that nobody really knows. We can't know.
  - lelanthran 2mo ago
    LLMs are probabilistic. I am too. The probable outcome of highly leveraged, loss-making companies trying to land grab with no clear path to profit and absolutely no moat is... probably failure. As AI proponents and AI coders are quick to tell you, the probable outcome is usually quite consistent. If it weren't, they wouldn't be using AI in the first place. It's a bit ironic that many are expecting success for companies whose only product is a probability distribution, pointing to outliers such as Amazon as evidence of probable success.
anukin 2mo ago
That’s because they were reinvesting the profits. I think they had given a profitable quarter just to show that they could do it.
- aurareturn 2mo ago
  And I'm sure Anthropic would be immensely profitable if they stopped investing their inference profits into training newer models.
  - stnikolauswagne 2mo ago
    For how long though? If Amazon never built AWS the core business conceivably would still be around today, if Anthropic stopped providing new models two years ago no one would care about them now.
  - oersted 2mo ago
    And then everyone would stop using their inference as soon as a better model for a reasonable price came out. The R&D expenditure is a critical requirement for the inference profits, to the point where we should probably lump their financials together, at which point is definitely not profitable. What will it look like when R&D plateaus (and yes it definitely will, but it could take a while), investment falls, and a few main competitors remain in the music chairs? It's very difficult to predict. The inference profits we are seeing the profits of a company that is temporarily ahead, but the revenue will level-out in a more stable market, depending on how many survived. It's also hard to tell where the costs will be at the end of the game, with constant efficiency optimisation mixed with cost increases for higher intelligence. I think it will be quite similar to the semiconductor industry, where, yes there are some key monopolies, but they are not the initial big players, and none of it is actually very profitable; while the real profits are reaped by those that make popular consumer products based on the foundational tech. I guess the main difference is that OpenAI and specially Anthropic have been quite effective at directly tapping into the consumer market rather than remaining technology providers.
    - aurareturn 2mo ago
      And then everyone would stop using their inference as soon as a better model for a reasonable price came out. Exactly. It's competition now that is driving high training costs - not a business model problem. There will be winners and losers. The losers won't be able to keep up with the training costs forever. See my post here: https://news.ycombinator.com/item?id=49119265 https://news.ycombinator.com/item?id=49119265
      - oersted 2mo ago
        It's never that simple, that's not the only possible endgame. We have seen plenty of examples in other industries where you can never really stop investing a ton on R&D with diminishing returns (like in semiconductors or pharma), because the moment you stop newcomers overtake you. Or the whole thing becomes a commodity with lots of competitors, where technological advantage is overtaken by marketing as the dominant force. Or you really are left as the only player alive, but you realise that the market cannot absorb higher prices for your product by then, they prefer just not to buy it. Perhaps you are the only player alive because the business has become so low-margin that everyone else has abandoned it intentionally. That Silicon Valley pitch you are echoing rarely works out as advertised, even for the winners.
kryptiskt 2mo ago
That wasn't what it seemed like at the time. Amazon didn't post profits, sure, but they sure as hell weren't a giant money suck either, they didn't need billions in financing to run their business. There were a lot of Amazon bears, but they were concerned about the high valuation, not about them going broke (since even the most pessimistic bear can read a cashflow statement).
matwood 2mo ago
Amazon had a close call around the .com crash as capital markets froze, but they were not going broke every year. They were purposely (and rather famously in business circles) investing every dollar made in order to grow the business. It was clear early on the original business worked. Amazon also added/pivoted to AWS, which is where a huge part of its value comes from today.

I remember when Amazon was going to go broke every year for over a decade. Until they didn't.

lelanthran 2mo ago

I remember when hundreds of dotcom companies were going to go broke, and they all did. Not sure what your point is.

robomartin 2mo ago
Simple: None of us have a crystal ball. Trying to predict the future is foolish. I am not saying that what we are seeing might not be problematic. I am only saying that nobody really knows. We can't know.
- lelanthran 2mo ago
  LLMs are probabilistic. I am too. The probable outcome of highly leveraged, loss-making companies trying to land grab with no clear path to profit and absolutely no moat is... probably failure. As AI proponents and AI coders are quick to tell you, the probable outcome is usually quite consistent. If it weren't, they wouldn't be using AI in the first place. It's a bit ironic that many are expecting success for companies whose only product is a probability distribution, pointing to outliers such as Amazon as evidence of probable success.

anukin 2mo ago

That’s because they were reinvesting the profits. I think they had given a profitable quarter just to show that they could do it.

aurareturn 2mo ago
And I'm sure Anthropic would be immensely profitable if they stopped investing their inference profits into training newer models.
- stnikolauswagne 2mo ago
  For how long though? If Amazon never built AWS the core business conceivably would still be around today, if Anthropic stopped providing new models two years ago no one would care about them now.
- oersted 2mo ago
  And then everyone would stop using their inference as soon as a better model for a reasonable price came out. The R&D expenditure is a critical requirement for the inference profits, to the point where we should probably lump their financials together, at which point is definitely not profitable. What will it look like when R&D plateaus (and yes it definitely will, but it could take a while), investment falls, and a few main competitors remain in the music chairs? It's very difficult to predict. The inference profits we are seeing the profits of a company that is temporarily ahead, but the revenue will level-out in a more stable market, depending on how many survived. It's also hard to tell where the costs will be at the end of the game, with constant efficiency optimisation mixed with cost increases for higher intelligence. I think it will be quite similar to the semiconductor industry, where, yes there are some key monopolies, but they are not the initial big players, and none of it is actually very profitable; while the real profits are reaped by those that make popular consumer products based on the foundational tech. I guess the main difference is that OpenAI and specially Anthropic have been quite effective at directly tapping into the consumer market rather than remaining technology providers.
  - aurareturn 2mo ago
    And then everyone would stop using their inference as soon as a better model for a reasonable price came out. Exactly. It's competition now that is driving high training costs - not a business model problem. There will be winners and losers. The losers won't be able to keep up with the training costs forever. See my post here: https://news.ycombinator.com/item?id=49119265 https://news.ycombinator.com/item?id=49119265
    - oersted 2mo ago
      It's never that simple, that's not the only possible endgame. We have seen plenty of examples in other industries where you can never really stop investing a ton on R&D with diminishing returns (like in semiconductors or pharma), because the moment you stop newcomers overtake you. Or the whole thing becomes a commodity with lots of competitors, where technological advantage is overtaken by marketing as the dominant force. Or you really are left as the only player alive, but you realise that the market cannot absorb higher prices for your product by then, they prefer just not to buy it. Perhaps you are the only player alive because the business has become so low-margin that everyone else has abandoned it intentionally. That Silicon Valley pitch you are echoing rarely works out as advertised, even for the winners.

kryptiskt 2mo ago

That wasn't what it seemed like at the time. Amazon didn't post profits, sure, but they sure as hell weren't a giant money suck either, they didn't need billions in financing to run their business. There were a lot of Amazon bears, but they were concerned about the high valuation, not about them going broke (since even the most pessimistic bear can read a cashflow statement).

matwood 2mo ago

Amazon had a close call around the .com crash as capital markets froze, but they were not going broke every year. They were purposely (and rather famously in business circles) investing every dollar made in order to grow the business. It was clear early on the original business worked. Amazon also added/pivoted to AWS, which is where a huge part of its value comes from today.