Why Everybody Is Losing Money On AI • Hacker News Board

Re: Why Everybody Is Losing Money On AI

#31

Post by exe34 » Fri, Sep 05, 2025, 5:40 PM UTC

gdbsjjdn wrote: post #22

I think Ed hits on an interesting point about the new user who spends $4 on a TODO file. Current LLM users are very enthusiastic about finding different models for different use cases and evaluating the cost-benefit of those models. But the average end user doesn't give a shit. If LLMs are going to "eat the world" they need to either be a lot better in the median case (bad prompts, bad model selection) or they need t…

> If LLMs are going to "eat the world" they need to either be a lot better in the median case (bad prompts, bad model selection) or they need to be so cost-effective that you can farm out your query to an ensemble and choose the result dialogue-tree-style.

LLMs have been around for two years. it took decades before the PC really took hold.

Re: Why Everybody Is Losing Money On AI

#32

Post by bionhoward » Fri, Sep 05, 2025, 5:41 PM UTC

Is this really surprising given how VC funded capitalism works? Spend money to build amazing technology and gain market share, then eventually flip into extraction mode.

Yes, a pullback will kill some weaker companies, but not the ones with sufficient true fans. Plus, we’re talking about a wide-ranging technological revolution with unknown long term limits and economics, you don’t just give up because you’re afraid to spend some money.

I don’t want to pay Anthropic, because I don’t trust them, but I will absolutely pay cursor, because I trust them, and I doubt I’m alone. My cursor usage goes to GPT-5, too, so it’s definitely not 100% Anthropic, even if I’m the only idiot using GPT5 on Cursor

It’s fun to innovate. Making money is a happy byproduct of value creation. Isn’t the price of success always paid in advance, anyway? Why would winning AI tech companies pack it up and stop crushing it over the long term just because they’re afraid to lose someone else’s money in the short term? Wouldn’t capitulation guarantee losses moreso than continued effort?

Re: Why Everybody Is Losing Money On AI

#33

Post by hall0ween » Fri, Sep 05, 2025, 5:42 PM UTC

tristor wrote: post #17

umbauk wrote: post #7

I mean, we know everyone is losing money on AI. I thought from the title it was going to explain why. As in, why are they choosing to lose all that money?

> As in, why are they choosing to lose all that money? Executive egos and market hype

The market hype is real. Check-signers at businesses expect LLMs to have the ability the AI CEOs talk about in their interviews and conferences but don’t exist (and are no where near existing).

Re: Why Everybody Is Losing Money On AI

#34

Post by panosv » Fri, Sep 05, 2025, 5:42 PM UTC

What about Google? Anyone has any insights on their unit economics since they own the models and the infrastructure (which is also custom TPUs)? Are they doing better or are they in the same money losing business?

Re: Why Everybody Is Losing Money On AI

#35

Post by [deleted] » Fri, Sep 05, 2025, 5:43 PM UTC

mewpmewp2 wrote: post #9

I'm not making any claims as to whether AI will become profitable or when, but if there's a new tech that has high potential or is highly desirable, I think it's expected that initially money will be lost. Simply because strategically if there's high long term potential, it initially makes sense to put more money in than you get out of. Not saying that AI is this, but if you determined that you have a golden goose th…

[deleted]

Re: Why Everybody Is Losing Money On AI

#36

Post by habinero » Fri, Sep 05, 2025, 5:43 PM UTC

golergka wrote: post #16

> OpenAI spent 50% of its revenue on inference compute costs alone This means that they operate existing models with very healthy 50% profit margin, that’s excellent unit economics actually. Losing money by investing more into R&D that you make is not the same as burning it by selling a dollar for 90 cents.

Revenue minus compute is not profit lol. You still have to pay salaries and rent on your buildings, which are usually the biggest expenses.

Re: Why Everybody Is Losing Money On AI

#37

Post by leptons » Fri, Sep 05, 2025, 5:43 PM UTC

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.

Computers do get more powerful, but the price for a decent system has been about the same for a long time. $1500 got me a good system 10 years ago, but I'd still be paying $1500 for a good system today.

Re: Why Everybody Is Losing Money On AI

#38

Post by cwmma » Fri, Sep 05, 2025, 5:44 PM UTC

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.

He isn't saying they won't ever come down, he's saying they will not be coming down any time soon due to structural factors he discusses in the article.

Re: Why Everybody Is Losing Money On AI

#39

Post by cwmma » Fri, Sep 05, 2025, 5:45 PM UTC

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

Re: Why Everybody Is Losing Money On AI

#40

Post by toddmorey » Fri, Sep 05, 2025, 5:47 PM UTC

golergka wrote: post #16

> OpenAI spent 50% of its revenue on inference compute costs alone This means that they operate existing models with very healthy 50% profit margin, that’s excellent unit economics actually. Losing money by investing more into R&D that you make is not the same as burning it by selling a dollar for 90 cents.

50% margins would be actually low and concerning for a saas business. What makes software an attractive business is how well it scales. The standard for saas has been at least 80% or higher margins.

Most all saas accounts require lengthy and generous free trials and boy AI compute throws a bit of a hand grenade into that PLG strategy. It’s just new economics that the industry will have to figure out.