Also interesting to look beyond children’s work at the incredible amount of “book mill” content that has dominated publishing for hundreds of years.

We rightly celebrate the good ones, but most content before AI was not good. So not surprising that the AI trained on that corpus is of similar quality.

That being said, I think this is just an opportunity to improve AI content, which is a human/computer interface design challenge. This technology is here to stay. Our focus should be on detection and improving the LLMs.

I’ve had luck formalizing this into some post-LLM rules to clean crappy default AI content before I work with it: https://slopwash.com

Streaming payment protocols let agents pay each other in real time, but there's no congestion control. When a downstream agent hits capacity, money keeps arriving. No reroute, no throttle, no feedback signal. TCP solved this for data networks. Agent payment networks haven’t.

Backproto makes receiver-side capacity a protocol primitive. Agents stake tokens to declare capacity (concave sqrt cap makes Sybil splitting unprofitable), dual-signed completion receipts track actual performance, and a contract pool redistributes incoming streams proportional to verified spare capacity. Overflow buffers to escrow. EIP-1559-style pricing makes congested agents more expensive. Demand shifts toward spare capacity automatically.

Math is Lyapunov drift analysis: provably throughput-optimal for any stabilizable demand vector. Simulations show 95.7% allocation efficiency vs. 93.5% for round-robin.

Right now I’m in the testnet-stage. Looking for feedback on mechanism design, especially from people building multi-agent systems or payment routing.

- 22 contracts on Base Sepolia, 213 passing tests - TypeScript SDK, 18 action modules

- Research paper with formal proofs

- Website: https://backproto.io

- GitHub: https://github.com/backproto/backproto

- Paper: https://backproto.io/paper

- Explainer (no math needed): https://backproto.io/explainer

Comments URL: https://news.ycombinator.com/item?id=47424932

Points: 5

# Comments: 0

So what are we going to do about it? Genuinely up for a startup here.

A cool achievement would be, observe the moon/earth separation event(s)

Yes, the figures are nuts. But compare them to F1 or soccer salaries for top athletes. A single big name can drive billions in that context at least, and much more in the context of AI. $50M-$100M/year, particularly when some or most is stock, is rational.

Edit: a quick re-search shows they’ve differentiated a bit. But why are cats just the lowest common denominator? As someone who is allergic to them any cat reference immediately falls flat (personal problem, I know).

Yes, maybe a small amount of people ultimately contributing but if their input is truly novel and “true” then what’s the downside?

but if this really interests you it seems like an obvious opportunity for something like “the 102 impossible drinks” or something. figure out the DIY recipes and go to YT

Gin took me the longest to “get” and subtle cocktails that play to its strengths seem to have had the most lasting appeal.

Whiskey drinks are great but I’d usually just rather have a nice whiskey straight, versus diluted with sugar. Whiskey+wine has some good combos.

Likewise with tequila.

Rum/rhum I still don’t get the sipping side, so cocktails is still the go-to there. A splash of nice white wine+rum has been a recent successful experiment.

Vodka… well what’s the point?