Prof. Eli Ben Sasson joined (finally!) the Freedom of speech protocol.

Censorship resistance for the win.

Nostr is and will be a critical piece of the Integrity Web of tomorrow. So it’s a natural fit for someone who pioneered and contributed so much to the realms of verifiable computation to embrace it and support it!

Ok I will come back and post more often on Nostr. It’s a shame I don’t manage to maintain consistency here. Now there is a real chance with all the buzz on Buzz to make Nostr getting finally the real traction it deserves.
Freedom of speech protocol.
And much more actually.
The future of agentic commerce might happen on Nostr.
Decentralized marketplace of services and billions of agents exchanging services over Nostr DVMs.
Let’s go

I trained a GPT across 4 workers using Nostr as the communication layer.

No central server. No coordinator. Workers exchange compressed pseudo-gradients as signed Nostr events through public relays.

This is "nostrain", distributed ML training over Nostr.

How it works:

1. Each worker trains locally for N steps (standard PyTorch/AdamW)
2. Computes pseudo-gradient: trained_params - initial_params
3. Top-k sparsifies → int8 quantizes → zlib compresses
4. Signs it with BIP340 Schnorr, publishes as a Nostr event (kind 33333)
5. Collects peer gradients from relay
6. Averages + Nesterov outer step

This is DiLoCo, the same algorithm Google used to train LLMs across poorly-connected datacenters.

Except the "datacenter interconnect" here are censorphip resistant Nostr WebSocket relays.

The repo ships a char-level GPT demo (834K params, 4 layers, 4 heads).

4 workers each get a different slice of Shakespeare (inspired by Karpathy nanoGPT).

No worker sees the full text.

Text evolution over 5 rounds:

Round 0: ROMEO:2NYPp@JTb<;2..qce[vP
Round 2: ROMEO: Maf sthat pine ted mes I chat
Round 5: ROMEO: d I shes mear to the ce withat, tre so ther wisho

Loss: 4.5 → 2.4. The workers that saw completely different text are converging to the same model through the relay.

Why Nostr?

Because Open Source / Decentralized / Sovereign AI must win.

Public relay infrastructure already exists. WebSocket pub/sub at scale, with cryptographic identity built in. Every gradient event is Schnorr-signed and verifiable by any subscriber.

You don't deploy servers. You don't manage infrastructure.

You just point workers at relays that already exist.

The relay doesn't know or care that it's carrying ML gradients.

And it is censorship resistant.

Do meta prompting more. Less complex setup and orchestration. Rely more on self reflect capacity of the models.
That’s it.

fgu >>>>> ngu
freedom tech will save the world

Time to shake the balance of power in the world honestly