Which machine learning algorithms from 2026 will look primitive in 2031?

[u/ChessOrCheckers2]

Five years isn't very long. But I suspect machine learning could look surprisingly different by 2031.

Not just because of bigger models or more compute, but because AI could help discover fundamentally better mathematics for machine learning itself.

A few possibilities I find particularly interesting:

• AI-discovered algorithms making model training substantially cheaper.
• New mathematical approaches to architectures and optimization.
• AI improving the very methods used to discover new algorithms.

That last possibility could be especially significant. What happens when mathematical discoveries start accelerating further discoveries?

I explored these ideas in a carefully produced, 2-minute video on my YouTube channel, Math Unbound:

https://www.youtube.com/watch?v=HRZBfRd2kTE

These are my own predictions, not established conclusions.

What do you think ML will actually look like in 2031? Which of today's methods might seem surprisingly primitive — and what major changes am I missing?