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Why Everybody Is Losing Money On AI

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Re: Why Everybody Is Losing Money On AI

#111
post #102
post #46

Earlier quoted context omitted.

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.

Or unless you work for Coinbase, where people who refused to use AI got fired. Think that's rare? Nope. It's coming everywhere. Most companies are at the stage of trying to monitor AI usage and encourage it, but eventually it'll stop being optional.

I doubt it will become as usual. It scream innefective management in the first place and is not defense of ai at all.

Company trying to get rid if innefective people would make sense, but if you measure it by ai usage all that happens is that your ai usage will go up - and price of using it along with it.

There are always irrational managers enjoying power trips. But the norms normally dont become that irrational

Re: Why Everybody Is Losing Money On AI

#112

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…

But back then, you was better off not depending on pet.com. If products of one of those vaporware companies became important in your process, your company went down along with.

Those were companies that had multiple expensive IT restructurings one after another, each making them more innefective and then either run out of cash or barely made it.

It worked well for companies that were choosing smart.

Re: Why Everybody Is Losing Money On AI

#113

"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.

The first mobile phone, the Motorola DynaTAC 8000X, was launched in 1984 for $3,995 (more than $12k in 2025 dollars). So we should expect a 12x cost reduction in LLMs over 40 years.

IBM 3380 Model K introduced in 1987, has 7.5 GB of storage and costed about $160000 to $170000, or adjusted for inflation it is $455000 in 2025 US dollars, that's $60666/GB. A Solidigm D5-P5336 drive that can store 128 TB costs about $16500 in 2025 US dollars, that is $0.129/GB. That's a 470279x price reduction in slightly less than 40 years. So what is likely going to happen to LLM pricing? No one knows and both your example as well as mine doesn't mean anything.

Re: Why Everybody Is Losing Money On AI

#114
post #111
post #102

Earlier quoted context omitted.

Or unless you work for Coinbase, where people who refused to use AI got fired. Think that's rare? Nope. It's coming everywhere. Most companies are at the stage of trying to monitor AI usage and encourage it, but eventually it'll stop being optional.

I doubt it will become as usual. It scream innefective management in the first place and is not defense of ai at all. Company trying to get rid if innefective people would make sense, but if you measure it by ai usage all that happens is that your ai usage will go up - and price of using it along with it. There are always irrational managers enjoying power trips. But the norms normally dont become that irrational

It's rational and will become standard.

Imagine you had a job doing ordinary database backed web app written in Java, and you found you had a coworker who wrote all their code in Notepad. They also refused to run linters or open code reviews, viewing it all as modern nonsense. Would you find that acceptable? Would you be surprised if a few months later that guy got let go for performance reasons? No.

Developers are given a lot degree of freedom, but in return are expected to use that freedom responsibly to deliver as much value as they can for the company. People refusing to use powerful tools had better have a watertight explanation for why. Mere negative vibes aren't good enough.

Re: Why Everybody Is Losing Money On AI

#115
post #109
post #108

Earlier quoted context omitted.

If developers and enterprises can host their own OSS/fine-tuned models, why will they pay Anthropic or OpenAI?

Because hosting a really GOOD model requires hardware that costs tens of thousands of dollars. It's much cheaper to timeshare that hardware with other users than to buy and run it yourself.

That may be true for independent devs or startups. Larger companies have enough demand to justify a few A/H100s.

Re: Why Everybody Is Losing Money On AI

#116
post #73

Earlier quoted context omitted.

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…

Why do you think OpenAI wanted to get rid of GPT-4 etc so aggressively?

I suppose there's a distinction between new less capable models, I can see why those would be more efficient. But maybe the older frontier models are less efficient to serve?

Re: Why Everybody Is Losing Money On AI

#117
post #73

Earlier quoted context omitted.

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…

Why do you think OpenAI wanted to get rid of GPT-4 etc so aggressively? I suppose there's a distinction between new less capable models, I can see why those would be more efficient. But maybe the older frontier models are less efficient to serve?

Definitely less efficient to serve. They used to charge $60/million input tokens for GPT-3 Da Vinci. They charge $1.25/million for GPT-5.

Plus I believe they have to keep each model in GPU memory to serve it, which means that any GPU serving an older model is unavailable to serve the newer ones.

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