Ask yourself if AI was so profitable, why don't any of the big hyperscalers break out AI revenue in their earnings. OpenAI and Anthropic both project huge losses for the next couple years, it's not hard to find.

The real problem is, as the GP comment pointed out, that they can never stop training. As long as they're committed to building these behemoth models, the second they stop training, someone else will catch up and everybody will switch over because it's trivial to do so.

I'll give you the coding harnesses themselves are better because that was a new product category with a lot of low-hanging fruit, but have the models actually improved in a way that isn't just benchmaxxing? I'd argue the models seem to be regressing. Even the most AI-pilled people at my company have all complained that Opus 4.7 is a dud. Anecdotally, GPT 5.5 seems decent, but it's rumored to be a 10T parameter model, isn't noticeably better than 5.4 or 5.3, is insanely expensive to use, and seems to be experiencing model collapse since the system prompt has to beg the thing to not talk about goblins and raccoons.

But back to the GP comment: I'm still not sure why a CS prof necessarily needs to be able to poke at LLMs at all. There are plenty of other areas of CS that are worth exploring. And if it's not possible to make a good LLM without violating your principles, well, then maybe they aren't such a worthwhile piece of technology.

Agree to disagree.

> The academic field of computer science pretty much started as an exploration into whether machines could be built that could understand human language.

No? CS started as an offshoot of applied mathematics and physics. The study of formal logic, algorithms, digital circuits, etc. predates Turing by centuries. Hell, even the Turing machine predates the Turing test by a couple decades.

Why? Language models are interesting from a technical perspective, but so are tons of areas of CS. There's nothing inherently virtuous about using an LLM.

The AI companies have taken all the wrong lessons from social media and learned how to make their products addictive and sticky.

I’m a certified hater, but even I’ve fallen into the exact trap you’re describing. Late last year I was in the process of buying a house that had a few known issues with a 30 day close. I had a couple sleepless nights because I had asked ChatGPT or Claude about some peculiar situation and the bots would tell me that I was completely screwed and give me advice to get out of the contract or draft a letter to the seller begging for some concession or more time. Then the next day I’d get a call from the mortgage guy or the attorney or the insurance broker and turns out, the people who actually knew what they were doing fixed my problem in 5 minutes.