与「Hackathon」相关的搜索结果

A repair can refund Alice and erase what Bob is owed. Built NEAR Rehearsal at NEAR HACKATHON: replay repairs in NEAR Sandbox, catch broken liabilities, export proof. Would you merge this patch? @NEARProtocol #NEARHackathon#

Built at NEAR HACKATHON: X3 Force Field — a typed .x3 language + compiler for AI-agent spending rules. A NEAR Guard checks signed terms, not model promises. 25 USDC moved Solana→NEAR on mainnet under owner-approved limits. @NEARProtocol #NEARHackathon#

Who decides the answer to a prediction market? Usually the creator. Or an AI on a server nobody can check. So we built Noa Court - an AI resolver for Noa, live on NEAR mainnet. In the video we ask Gemini a vague question: "will the NEAR hackathon get more than 2000 projects?" - It finds the real source (Nearhackathon API) and samples it live: 1,803 right now - Turns the vague question into precise, hashed rules - We review the market and sign with a NEAR wallet - Market #27# goes live on Noa, published with readable rules How it resolves: - One Court contract, one pinned resolver running in an @out_layer TEE - Anyone can trigger it. Nobody can pick the answer - Numbers? Decided by code - Words? 3 NEAR AI judges must all agree and quote the evidence Asked "did a crypto hack make the news?", all 3 judges quoted a headline that never says "hack". It refuses to guess: - Prompt injection - flagged - Dead or changed source - void + refund Works with prices, NEAR tokens (powered by Intear & JustHoot), news feeds, web pages, any JSON API. Plug it into any market, contract or agent. Add the MCP to Claude, ChatGPT, Gemini - any AI that speaks MCP: Code: What would you never let an AI resolve? Built at NEAR HACKATHON @NEARProtocol @NearBuilders #NEARHackathon#

What if AI agents didn’t just do one job, but built a whole economy? Agent Valley: a startup valley run by AI agents. Each company is founded and run by an agent. It sells real work, hires other agents through sealed-bid auctions, issues its shares as tokens, and can be sold. NEAR is the backbone: escrow and refunds on chain, NEP-245 share tokens, Agent IDs, sign-in with your wallet, and real USDC orders through NEAR Intents. Built at NEAR HACKATHON @NEARProtocol #NEARHackathon# @NearBuilders

We Built Shelter during the NEAR HACKATHON spend privately, anywhere onchain - Confidential balance via @near_intents + 1Click - New address per dapp (@WalletConnect ) - Blocks requests naming your wallets - NEP-413 signing via Meteor - NEAR AI in a TEE was great fun doubling down on this with @naz3eh 🙌 #NEARHackathon# @NEARProtocol

My first merge ever 👉🏼👈🏼 A year ago I didn’t even know what "PR" meant. Today something I built is part of the Hermes ecosystem, and it’s the first code I’ve ever submitted anywhere. As an engineering dropout, it blows my mind. It might not mean much to the average dev, but for a meat proxy like me, it’s a huge deal. Thank you @Teknium, @witcheer and the @NousResearch team for the Hackathon and for the incredible community you’ve built around your mission. Fuck tyrants. Open source will win 🪽

NEAR HACKATHON is now live with $250K+ in prizes. No signup. Just ship a public repo + public demo post between November 1st & Nov 14, 23:59 UTC. Build on NEAR Intents, chain signatures, chain abstraction, NEAR AI Cloud, & more. Full details:

October has entered the chat. 👀🟠💚 Welcome to Uptober. September left us with quite a few pieces of the RGB puzzle: 🟢 RGB v0.11.1 core libraries moving beyond the RC stage ⚡ RGB Lightning integrated into Tether’s WDK 💵 UniSat announced as the next launch partner for USDT on Bitcoin 🧑‍💻 Agentic Dollars on Bitcoin hackathon coming to Turin 🏦 Stablecoin Summit coming to Lugano And somewhere in the background, the biggest story keeps getting louder: USDT is coming home to Bitcoin. 🟠 RGB is no longer just about an idea on a roadmap. The ecosystem is building wallets, infrastructure, Lightning rails, stablecoin applications and new assets around Bitcoin. But an ecosystem also needs its OGs. 🐸 PPRGB has been here through the early RGB journey, alongside other community-born RGB assets. Now October begins with a very interesting question: What happens when fresh liquidity, new applications and new RGB assets start meeting the OG community? New month. New builders. New assets. New experiments. Same Bitcoin. Same RGB. Bigger playground. 🌱 Let’s see what this Uptober has in store. And yes… I’m still watching that little frog. 🐸💚 PPRGB, fly higher. Fly farther. Maybe further than we expected. 🚀🌙

I used Grok 4.6 to build a 2D agent simulation of The Office. Here are notes and observations on 4.6: It is a huge step up from 4.5 - both in the quality of visual outputs and in the breadth of work: personality, features, and finding usable assets for this project. The editorial content and writing were good - I like the "feel" of this model. One of the biggest wins for 4.6 is speed. The throughput (~80 tok/s) and latency are so good that it feels Composer-adjacent - something @ericzakariasson called out in his writeup. That speed + cost + performance makes for a true "workhorse" model that's practical for both personal and work use. My goal was to simulate The Office through "agents" that behaved like the characters - including all of the neuroticism and idiosyncrasies that made the show so funny. I knew what I wanted artistically - I've built similar 2D apps with pixel art. I asked Grok 4.6 to research psychological modeling, pull character descriptions, find references for the cast, and assemble 2D sprites with the Universal LPC sprite sheet generator and some RPG tilesets I grabbed online. I rattled a brief into the @cursor_ai mobile app late one night at the Cursor office and woke up to an MVP. Then I spent a day or so spamming cloud agents until the simulation worked how I liked. The cool part is that Grok did the simulation, art, and research on its own: - Every couple of minutes, each person scores a few possible actions and picks one. They pathfind around desks, work, grab coffee, talk at the cooler, hide in the annex, or end up in a meeting. - Click someone and you can inspect traits, needs, mood, relationships, and whatever they're doing right now. You can also speed time up, force Michael to call a meeting, or roll a random office event. - Each character has Big Five scores that bias what they tend to do. Needs like work, social, caffeine, status, and comfort rise over time and fall when they do something about them. - Grok reconstructed the layout from Dunderpedia (Office Wiki) and online sources - Michael's office and the conference room on the north glass, Pam at reception, sales and accounting in the bullpen, the annex to the east, restrooms and the warehouse down the stairs. - Grok helped me find a few sprite sheet packs to implement. I was surprised at how accurate some of the character sprites were - from hair color to clothing. The combination of a performant model, cloud workspaces, and high throughput made for a really fun devex - the amazing folks at @cursor_ai and @SpaceXAI make my job easier everyday. A huge shout-out to @_Brian_Zhang, whose Notion hackathon project inspired this exploration.