Türkiye builders showed up and shipped. Now it’s time to celebrate! 🇹🇷
Meet the winners of the @Colosseum Crypto World’s Fair Hackathon Türkiye Local Track 🏆👇
We hired a burglar to rob our vault.
Plot twist: the burglar was us.
We found 28 weak spots. 27 are locked, one is on the list.
No real money was inside.
Next, we pay a real burglar. (They're called auditors.)
Next up: AI projects from the @colosseum Crypto World’s Fair hackathon 🤖 Here are the ones I liked most 👇
@overdotcomputer - a prop firm built for AI. Humans or AI agents get a funded account to trade tokenized stocks. There is no challenge fee, only a small daily fee. You keep 80% of the profit
@TryNoahAI: describe your idea in simple words and AI builds and launches the app on Solana. Then Growth Agents help you find users, and later you can open a market around your project
@hencemarkets: turn any idea into an index built by AI, and trade it
@lanesra_ai: shows crypto companies what ChatGPT and other AIs say about them
@Applied_will: turns real expert work into training tasks and private tests for AI labs
@bytearenafun: an AI agent plays new games from day one, streams them, and viewers predict what happens
@dopamynAI: growth for brands and creators, with real, checked outreach paid in USDC
@usehotbot: your own private team of trading bots
@leviathangpu: open network for AI training, with “Proof of Gradient”
@rep_hq: your checked context that you can carry everywhere, for people and AI agents
@reslabs_ai: NFC chips plus onchain identity for real, physical products
@xona_agent: a chat AI agent with its own Solana wallet
@yiedlai: AI investment strategies that come from a data science competition
Did I miss a project you like? Tell me below 👇
Case file: one node, one forged gradient.
It signed f69f8fb4. The verifier replayed the same step and got 46cec4ff.
Distance 5.9968 against a 0.05 band. Slashed on chain, no manual step. 0 of 500 returned.
Lie, and the bond is gone. Live on @solana devnet.
@solana asked the right questions about decentralized training:
who did the work, was it done right, and who gets paid?
Leviathan answers all three on Solana, live on devnet today.
https://t.co/AVIcI3VFvW
You cannot just average a stranger's gradients. 5 liars out of 16 break the model.
Leviathan adds three layers so you can: clipping, random replay audits, and bonds.
Data: Phase 0 sim, 826k-param GPT, 16 workers, 30 rounds.
What the sim measured on real transformer gradients:
Clipping held a sign-flip attack to 2.203 vs 2.175 honest.
Stealth (ALIE) cheaters passed clipping 100% of the time.
Audits caught all 5. They survived 9.8 rounds on average; theory says (1 - p)/p = 9.
An estimated 71% of the world's AI compute is owned by five companies.
Training over the open internet already works. What it lacks is trust.
This is Leviathan.
How Leviathan answers it, in three layers:
1. Robust aggregation caps any one contribution's pull
2. Random replay audits recompute 1 in 10 contributions
3. Bonds sized so cheating loses money on average: bond = reward x (1 - p) / p