[preommr]

> Plus they have a massive churn problem with people quitting premium after 1-3 months.

Because, tbf, the free version is really good. I feel like a lot of AI companies are in the stage where they're still trying to gain massive marketshare and convince people of it's value. The real test is going to be when they pull the plug to force people to transition to premium.

[atwrk]

Pure anecdata, of course, but my impression so far was the opposite (same as with Gemini): The free version is so bad for me (gpt4o) that I really doubt the paid version can get meaningfully better.

* Text generation is really bad if said text is more niche than typical SEO stuff like "give me 300 words about soccer balls". Anything academic is usually wrong (i.e. full of hallucinations) or lacks/hallucinates proper sources. If I have to check everything anyway I can just use a search engine.

* Image generation is really bad if you don't just want deviantart-like content. Just yesterday I tried generating ideas for visualisations of a few topics (with quite a view different prompt approaches) and they almost all were unusable.

It is good at summing up longform content, though, but then again so am I - and I have to read it anyway to confirm there are no hallucinations...

Obviously many people use it for coding (which appears to be the low hanging fruit because code is so heavily formalized), but I can imagine that market is almost saturated by now.

[greg_V]

They have a 180 million users who are contributing no net revenue but are probably costing them significant amounts.

The math comes down to the fact that they raised enough money to stay in business until they have to raise even more money.

And a 180 mil users might seem like a lot in two years, but with the free media coverage they have... even if their free to premium conversion rate is pretty dismal, the "have you heard about them" to "active free user" rate is also very bad!

[physicsguy]

It’s only got easier to run models locally though, if performance continues to improve on smaller models, something like running ollama locally might be ‘good enough’ for a lot of people.

[petesergeant]

Wonder what the value in training data is of those millions of users.

[Workaccount2]

It's the "open hand" model that every tech start-up follows.

1. Be extremely generous to customers. Give away incredible tech at bargain basement prices. Pamper your employees with extraordinary benefits. Everyone from all angles loves your business.

2. People integrate your product into their lives. They become dependent on it because the value is so good. They tell everyone else in their lives about it. (2.5 IPO. This is where you make an exit, where those people who "love" your product that everyone else loves want to get in on the investment. Retail runs to buy up your shares. Also could be an acquisition.)

3. Close the hand. Competition has been ruined and people are addicted. Now it's time to raise prices and lower product quality. Initial investors are already out, so retail will carry the blame for the enshitification of your product.