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Why Everybody Is Losing Money On AI

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Re: Why Everybody Is Losing Money On AI

#71

Post by cmrdporcupine »

FL33TW00D wrote: post #6

"Please don't waste your breath saying "costs will come down." They haven't been, and they're not going to." Yes, every new technology has always stayed exorbitantly priced in perpetuity.

There has to be a name for the fallacy where people in our profession imagine that everything in technology follows Moore's law -- even when it doesn't.

We're standing here with a kind of survivorship bias because of all the technologies we use daily that did cost reduce and make it. Plenty did not. We just forget about them.

Re: Why Everybody Is Losing Money On AI

#72

Post by Jimmc414 »

uludag wrote: post #70
Jimmc414 wrote: post #63

Cursor burning cash to subsidize Anthropic's losses to subsidize Amazon's compute investments is their problem, not mine. The people writing all of these "AI is unprofitable" pieces are doing financial journalism similar to analyzing the dot-com bubble by looking at pets.com's burn rate. The infra overspend was real as well as the bankruptcies, but it existentially foolish for a business to ignore the behavioral shif…

I think the main fear is that these products will become so enshitified and engrained into everywhere that, looking back, we'll be wishing we didn't depend so much on the technology. For example, the Overton window around social media has shifted so much to the point that it's pretty normal to hear views that social media is a net negative to society and we'd be better off without it. Obviously the goal of these comp…

I don't disagree with anything you've said.

Re: Why Everybody Is Losing Money On AI

#73

Post by simonw »

jjfoooo4 wrote: post #69
simonw wrote: post #28

> Please don't waste your breath saying "costs will come down." They haven't been, and they're not going to. Cost to run a million tokens through GPT-3 Da-Vinci in 2022: $60 Cost to run a million tokens through GPT-5 today: $1.25

I think what we'll eventually see is frontier models getting priced dramatically more expensive (or rate limited), and more people getting pickier about what they send to frontier models vs cheaper, less powerful ones. This is already happening to some extent, with Opus being opt-in and much more restricted than Sonnet within Claude Code. An unknown to me: are the less powerful models cheaper to serve, proportional t…

Everything I've seen makes me suspect that models have continually got more efficient to serve.

The strongest evidence is that the models I can run on my own laptop got massively better over the last three years, despite me keeping the same M2 64GB machine without upgrading it.

Compare original LLaMA from 2023 to gpt-oss-20b from this year - same hardware, huge difference.

The next clue is the continuing drop in API prices - at least prior to the reasoning rush of the last few months.

One more clue: o3. OpenAI's o3 had a 80% price drop a few months ago which I believe was due to them finding further efficiencies in serving that model at the same quality.

My hunch is that there are still efficiencies to be wrung out here. I think we'll be able to tell if that's not holding if API prices stop falling over time.

Re: Why Everybody Is Losing Money On AI

#75

Post by orbital-decay »

cwmma wrote: post #39
simonw wrote: post #28

> Please don't waste your breath saying "costs will come down." They haven't been, and they're not going to. Cost to run a million tokens through GPT-3 Da-Vinci in 2022: $60 Cost to run a million tokens through GPT-5 today: $1.25

yes but due to reasoning models the same query uses VASTLY more tokens today then a couple years ago

In most use cases the main cost is always input, not output. Agentic workflows, on the other hand, do eat up a ton of tokens on multiple calls. Which can usually be optimized but nobody cares.

Re: Why Everybody Is Losing Money On AI

#76

Post by orbital-decay »

ASinclair wrote: post #18
km3r wrote: post #14

> At this point, it's becoming obvious that it is not profitable to provide model inference, despite Sam Altman recently saying that OpenAI was. Except the authors own provided data says it cost them $2B in inference costs to generate $4B in revenue. Yes training costs push it negative, but this is like tech growth 101, debt now to grow faster leads to larger potential upsides in the future.

Training costs keep exploding and several companies are providing frontier models. They'll have to continue shoveling tons of money into training just to stay in place with respect to the competition. So you can't just ignore training costs.

DeepSeek alone demonstrated a massive reduction in training costs, and there's a ton of low-hanging fruits nobody even started to use.

Re: Why Everybody Is Losing Money On AI

#77

Post by ffsm8 »

watwut wrote: post #46
mewpmewp2 wrote: post #30

Earlier quoted context omitted.

Yeah, but I have also dreamed of living in the woods, being completely self sustainable blissfully. It doesn't mean there aren't capitalists out there looking to produce and sell more, and people out there looking to buy.

The difference is that choice to live out in the woods costs you. Choice to not have a phone costs you. A choice to not pay ai at this point ... does not cost you unless you live in special situation.

Not getting a phone didn't really cost you either for the first 5-10 yrs.

But the people that didn't definitely had a harder time adjusting when it got increasingly annoying to live without a smartphone.

It's ultimately a choice you can make, but it definitely also comes with consequences - especially if your dayjob is software - as this is an industry that loves to discriminate against people that aren't aboard the hype train and don't have "10 yrs of experience in d̵o̵c̵k̵e̵r̵ LLMs"

Re: Why Everybody Is Losing Money On AI

#78

Post by simonw »

orbital-decay wrote: post #75
cwmma wrote: post #39

Earlier quoted context omitted.

yes but due to reasoning models the same query uses VASTLY more tokens today then a couple years ago

In most use cases the main cost is always input, not output. Agentic workflows, on the other hand, do eat up a ton of tokens on multiple calls. Which can usually be optimized but nobody cares.

With multiple calls an important factor to consider is token caching, where repeat inputs are discounted.

This is particularly important if you constantly replay the previous conversation and grow it with each subsequent prompt.

GPT-5 offers a 90% discount on these cached tokens! That's a huge saving for this kind of pattern.

Re: Why Everybody Is Losing Money On AI

#79

Post by Eddy_Viscosity2 »

simonw wrote: post #28

> Please don't waste your breath saying "costs will come down." They haven't been, and they're not going to. Cost to run a million tokens through GPT-3 Da-Vinci in 2022: $60 Cost to run a million tokens through GPT-5 today: $1.25

Are these the costs (what the supplier pays) or the prices (what the consumer pays)?

Re: Why Everybody Is Losing Money On AI

#80

Post by joenot443 »

candiddevmike wrote: post #2

This is a really well written article and contains references to back up the claims made. This part was mind blowing though: > Cursor sends 100% of their revenue to Anthropic, who then takes that money and puts it into building out Claude Code, a competitor to Cursor. Cursor is Anthropic's largest customer. Cursor is deeply unprofitable, and was that way even before Anthropic chose to add "Service Tiers," jacking up…

What are the odds that Microsoft acquires Cursor eventually, folding those users into a VS Code Premium of sorts?
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