506 sats \ 3 replies \ @k00b 29 Sep 2023 \ on: Mutiny Blog Our Data Driven Approach to Fixing Payment Reliability bitcoin
Great technical hero's journey! I hope we can eventually get to a point where mobile nodes don't need to do so much outsourcing, but based on this blog post it seems unavoidable for the time being.
We're interested in combining probing data with gossip data to create a reinforcement learning AI that can hook into our prober to continue learning from, with the plan to take the trained model and ship it to end users. When trampoline routing comes along, this may be very useful to us from a reliability and privacy standpoint.
AI? vc swipes right
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317 sats \ 2 replies \ @TonyGiorgio 29 Sep 2023
I've thought about it for quite awhile tbh, and this current AI wave is just swimming in garbage LLM stuff, so it's not the hotest thing anyways lol. But I do think there's something in RL for Lightning, espeically if you have the data and continued learning. At the very least it can be passive until it starts being correct most of the time.
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183 sats \ 1 reply \ @anon 30 Sep 2023
I'm really excited to see Mutiny digging into RL attachment strategies, though I'm less optimistic about it being useful for mobile users. Generally speaking, end users will want to minimize their on-chain footprint (ideally 1 channel), so there's not much insight to be gained. LSPs on the other hand will be big winners as they can dramatically improve node positioning (e.g betweenness)
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0 sats \ 0 replies \ @TonyGiorgio 30 Sep 2023
Maybe on the trampoline level it'll be useful. Positioning is one aspect an LSP can taken advantage of it for better connectivity. But also being aware of the graph and a trained model on graph components could be useful for end nodes. I do agree tho, probably more on the LSP level. And long term goals is that trampoline will be a scaling solution for end users and trampoline nodes can take advantage of AI.
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