Go-attention: A full attention mechanism and transformer in pure Go

Re:Go-attention: A full attention mechanism and transformer ... by tuckerman on Monday March 03, 2025 @06:41PM (#43248223)

> We’ve long since proven that machines are better for back-breaking labor.

This is contrary to my perception of current trends (and to a perhaps generous reading of Moravec's Paradox). Dexterous manipulation is still quite hard which is why a task like laundry folding is so impressive despite being relatively simple for many humans: https://www.physicalintelligence.company/blog/pi0

Perhaps we disagree on what "back breaking" entails but I'd much rather spend all day coding than folding laundry!

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Re:Go-attention: A full attention mechanism and transformer ... by hnlmorg on Tuesday March 04, 2025 @03:08AM (#43251748)

Yeah I definitely wouldn’t class laundry folding as “back breaking”. But I agree it is manual labor that’s difficult for current robotics.

There have been some advancements in this specific field though. So we might see a mass-produced robot that can do this in our life time. If not for homes then certainly for industrial workflows (dry cleaning services, new workflows for clothes manufacturing, etc)

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