Learning from continual experience is the key to scaling AI to ASI and beyond.

What will this require?

Different equations / algos. Different software architectures. New chips. New hardware architectures for those chips. New materials science for making those chips on different substrates. New energy sources (likely new solar methods). New (almost) everything.

That's all super expensive... will require more money and capital than ANY single company could muster.

Enter Bittensor incentive mechanisms. Those IMs unlock the language of value for value across a permissionless ledger.

This language has already produced outputs that would require over $1 Billion in capex and opex to deliver using conventional methods.

Tens of thousands of GPUs in a few months

1% the hashrate of Bitcoin in 30 days

Largest 3D asset library in a few weeks

First to ship and fastest improving decentralized training

We can also apply Bittensor incentives to domains like...

Design new neural net architectures that prove to continuously discover more compute efficient and general purpose model architectures

Design and test a new ASIC that continuously improves on its own compute efficiency as scaling demands grow in highly interconnected (but geographically distributed) scenarios

Create reactors for nuclear, storage and collection methods for solar and fusion based energy production technologies

And a lot more...

Those subnets would be able to harness trillions in funding and distribute the rewards fairly across billions of people who contribute to progress on the incentives collectively.

Bittensor will change the course of humanity and amplify the success of our species in profound ways. It's pretty obvious now.