Comment by noch

> They can. It's called "taking a risk".

Spoken like a young man. I salute you. However, on your journey remember that risk of ruin is what you want to minimize relative to your estimated rewards. That is, not all risks can be afforded. I happen to have a limited budget, perhaps you don't and costs in terms of money and time don't matter for you.

Ruin can set you back years or decades or permanently and then you find yourself on a ycombinator thread hopelessly trying to find someone who can meaningfully quantity and forecast future medium term AI progress so that you can hire them to help your ongoing project. Alas all you get is the comments' section. :-)

> but there's also no good reason to believe progress will stop, because a) there's many low and mid-hanging fruits to pick, as outlined by GP, and b) because it never did so far, so why would it stop now specifically?

Specifically, due to lack of data. Please refer to the earlier comment[^0]: deep learning requires vast amounts of data. Current models have already been trained on the entire internet and corpus of published human knowledge. Models are now being trained on synthetic data and we're running out of that too. This data bottleneck has been widely reported and documented.

---

[^0]: https://news.ycombinator.com/item?id=42673410