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introducing vim royale - real-time multiplayer duels - Race to clean broken code - elo-based matchmaking - replay & study every match - bot mode + singleplayer - built-in vimtutor to learn vim motions

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jitesh💙

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153,889 просмотров • 4 месяцев назад •via X (Twitter)

ИгрыОбразованиеНаука и технологии
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Been quietly building a browser based live audiovisual studio app for commercial use in Framer It listens to your music, analyses it in real time, then turns the frequency into visuals, type, glitches, motion, scene changes, FX, and more. It’s node based. Connect audio, MIDI, visuals and behaviours together without needing a PhD in noodles. Build scenes. Chain FX. Map parameters. Make things react to sound and MIDI in near real time (milliseconds latency). Performance Mode splits your controls from the clean projector output where you see the knobs and chaos, everyone else sees the magic. Underneath: frankly ridiculous. To use: surprisingly simple. Code named Signaaal. Sneak peak 👀🔊
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Been quietly building a browser based live audiovisual studio app for commercial use in Framer It listens to your music, analyses it in real time, then turns the frequency into visuals, type, glitches, motion, scene changes, FX, and more. It’s node based. Connect audio, MIDI, visuals and behaviours together without needing a PhD in noodles. Build scenes. Chain FX. Map parameters. Make things react to sound and MIDI in near real time (milliseconds latency). Performance Mode splits your controls from the clean projector output where you see the knobs and chaos, everyone else sees the magic. Underneath: frankly ridiculous. To use: surprisingly simple. Code named Signaaal. Sneak peak 👀🔊

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Introducing MIRA. A playable, multiplayer world model. A dream of Rocket League. Trained on 10k hours of data collected with publicly available bots, MIRA learns the dynamics of a four-player game. The model runs in real time at 20 fps, based on the keys you and the other players press. Built by General Intuition and kyutai, in collaboration with Epic Games. Not used to develop Rocket League. ▶️ Play the demo, read the technical report, and explore the open-source code at At ICML? Find us at Booth 111 to try it yourself and dig into the results with the team.
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Introducing MIRA. A playable, multiplayer world model. A dream of Rocket League. Trained on 10k hours of data collected with publicly available bots, MIRA learns the dynamics of a four-player game. The model runs in real time at 20 fps, based on the keys you and the other players press. Built by General Intuition and kyutai, in collaboration with Epic Games. Not used to develop Rocket League. ▶️ Play the demo, read the technical report, and explore the open-source code at At ICML? Find us at Booth 111 to try it yourself and dig into the results with the team.

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Goodbye clicking on Google Street View to check out the route! In your browser, with you can actually drive anywhere in the world🚀 You can also create multiplayer races🚗🏎🚓 The world is generated ahead of you in real-time from OpenStreetMap data combined with satellite elevation data as you drive. Just added a WIP of night mode and replaced the placeholder terrain/road textures with some nicer physics-based textures. Also now anywhere you go a million street lights will be added too. This is actually slowly starting to look like the promised Need For Speed + Google Maps #threejs #gamedev #indiedev Single player mode: Just find a location, click anywhere on the map and click "Hop Here". After parachuting down hold X to call the car to the road. Multiplayer mode: Click on "Create race" and select start and finish points. A route will be plotted. Click on Share Race to get the link and start racing!
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Goodbye clicking on Google Street View to check out the route! In your browser, with you can actually drive anywhere in the world🚀 You can also create multiplayer races🚗🏎🚓 The world is generated ahead of you in real-time from OpenStreetMap data combined with satellite elevation data as you drive. Just added a WIP of night mode and replaced the placeholder terrain/road textures with some nicer physics-based textures. Also now anywhere you go a million street lights will be added too. This is actually slowly starting to look like the promised Need For Speed + Google Maps #threejs #gamedev #indiedev Single player mode: Just find a location, click anywhere on the map and click "Hop Here". After parachuting down hold X to call the car to the road. Multiplayer mode: Click on "Create race" and select start and finish points. A route will be plotted. Click on Share Race to get the link and start racing!

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What does skydiving have to do with AI sales? 🪂 We didn't want to build yet another AI agent focused on flooding inboxes with spam, so we built Ora. 🔮 Introducing Lavender Ora: our agent for thoughtful, effective selling. Ora is built for sellers who choose value over volume, modeling the best practices of top performers—researching, personalizing, and timing impactful and optimized emails. All built on Lavender's ACI - Augmented Communication Intelligence - and powered by our insights from analyzing nearly 2B sales emails. 💜 Saves 4+ hours/day by handling busywork. ✈️ Smart Sequences precisely time follow ups based on real-world news and market events. ✅ Protects deliverability—no spam, just trust. 50 well-researched, personalized, and optimized emails every day - just like the best human sellers. Whether you're team manual or autonomous, Ora adapts to your workflow with: 🧐 OCD Mode: Manually review, refine, and approve 50 emails in 5 min. 🚀 LFG Mode: Ora goes fully autonomous, building passive pipeline and freeing up more of your time. Time saved at work = more time to do fun stuff. Like flying. Join the waitlist:

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67 real production bugs. 10 different AI tools, same PRs, same standard. Entelligence benchmarked every major AI code reviewer on bugs that already shipped and broke things. They put 10 tools through race conditions, security vulnerabilities, breaking API changes, and logic errors across 5 real open-source repos (Cal[.]com, Sentry, Discourse, Keycloak, Grafana). The gap between top and bottom is not small. What separated them was not raw model power. It was whether the tool understood code relationships. How a function signature change ripples through a codebase, not just what's on the line being reviewed. Entelligence caught things every other tool missed. A breaking API change in Cal[.]com that every other tool flagged as clean. An interface change in Grafana that would have broken compilation across all existing Logger implementations. A cache race condition in Keycloak that allowed concurrent threads to corrupt a bidirectional mapping. They also published the full methodology and didn't hide where they underperformed. Ruby codebases, race conditions, CSS regressions. It's all in there. 1/2

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THIS IS INSANE — AN ANTHROPIC ENGINEER BUILT A CLAUDE CODE BOT THAT READS INSTITUTIONAL OPTIONS FLOW IN REAL TIME AND TURNED $200 INTO $14,300 TRADING ALONGSIDE THE BIGGEST ORDERS ON THE TAPE the bot doesn't predict. it stalks it reads thousands of institutional options orders streaming through SpotGamma — scores every block by size, direction, and how it historically moves price — then trades only when the heaviest hands on the tape are moving here's what's running on screen right now: → GEX Surface Analysis — 3D gamma exposure map rotating in real time, strike $8,168, GEX at 1.36B → MotiveWave footprint — ESU6 Range(20) with cumulative delta crashing to -9,500. every bid and ask printed at every level → SpotGamma Live Flow — institutional tape streaming tick by tick: SPX, QQQ, NVDA, AAPL, META, MSTR, NDX. strike, volume, premium — all live → GEXRadar — QQQ at $720.09, Hedging Pressure 53/100, Major Walls mapped, bullish flow → MNQU6 on mobile — Nasdaq 100 M1, bid 29,589 ask 29,591, TP set, P&L at +$109.50 when an institution drops $40K on SPX 7,740 calls or $28,639 on NDX puts — Claude sees it before FinTwit even screenshots it the bot makes only 10 trades per day not 50. not 100. ten. because Claude Code learned the edge isn't frequency — it's selectivity. large institutional block orders only and it exits early. before the institutions unwind. the same flow analysis that finds the entry also maps when large players historically take profit — the bot exits ahead of the crowd $200 in. $14,300 out. built by an engineer who used Claude Code to do what no dashboard can — read every institutional options order in real time and trade only when the biggest ones align you're watching one chart this bot is reading every block order on the tape to find the 10 setups that matter today save this — full setup breakdown below ↓

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Most traders don’t fail because of strategy. They fail because they don’t see what they’re doing wrong. In real time. After being on a real trading floor and competing at a high level, one thing became clear: Awareness beats strategy. That’s why we built a full system: - A journal that tracks every trade automatically - An AI coach that analyzes your behavior - A community with live analysis and full transparency - And the ability to run our strategy as a bot Everything connected. Everything based on real data. If you’re serious about improving, you should be inside. Free Telegram group:
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Most traders don’t fail because of strategy. They fail because they don’t see what they’re doing wrong. In real time. After being on a real trading floor and competing at a high level, one thing became clear: Awareness beats strategy. That’s why we built a full system: - A journal that tracks every trade automatically - An AI coach that analyzes your behavior - A community with live analysis and full transparency - And the ability to run our strategy as a bot Everything connected. Everything based on real data. If you’re serious about improving, you should be inside. Free Telegram group:

Merlijn The Trader

45,582 просмотров • 5 месяцев назад

At Avalon we are building "Real-time creating" - the ability to generate gameplay ready persistent worlds prompted from text. While others are building real-time video world models, Avalon is building real-time world generation inside a fully playable, persistent multiplayer engine. Internally running at 3840×2180 at 60 FPS. Built on Unreal Engine. Multiplayer by default. Persistent by default. Gameplay-ready by default. This is not a video latent replay. Not a simulation of interaction. It is a real 3D world with physics, logic, and authoritative multiplayer state. Avalon is trained on proprietary Avalon interaction data and powered by a hybrid system that combines language understanding, 3D model generation, procedural systems, and structured gameplay logic synthesis. Players can walk through a live world and generate environments, assets, mechanics, and entirely new gameplay modes using natural language. We accomplish this through a combination of 3D model generation, game logic generation based on our proprietary systems, and AI driven world creation. While other players are inside it. Changes persist instantly. State is synchronized in real time. Creation happens inside the world, not outside of it. Describe a biome. Spawn a civilization. Create a survival mode. Build a dungeon crawler. Launch a new game inside the world. Avalon interprets intent and integrates it directly into the live multiplayer environment. This is not a world model predicting video. This is a gameplay engine that understands language. If you can describe it, you can build it. And others can walk into it instantly.
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At Avalon we are building "Real-time creating" - the ability to generate gameplay ready persistent worlds prompted from text. While others are building real-time video world models, Avalon is building real-time world generation inside a fully playable, persistent multiplayer engine. Internally running at 3840×2180 at 60 FPS. Built on Unreal Engine. Multiplayer by default. Persistent by default. Gameplay-ready by default. This is not a video latent replay. Not a simulation of interaction. It is a real 3D world with physics, logic, and authoritative multiplayer state. Avalon is trained on proprietary Avalon interaction data and powered by a hybrid system that combines language understanding, 3D model generation, procedural systems, and structured gameplay logic synthesis. Players can walk through a live world and generate environments, assets, mechanics, and entirely new gameplay modes using natural language. We accomplish this through a combination of 3D model generation, game logic generation based on our proprietary systems, and AI driven world creation. While other players are inside it. Changes persist instantly. State is synchronized in real time. Creation happens inside the world, not outside of it. Describe a biome. Spawn a civilization. Create a survival mode. Build a dungeon crawler. Launch a new game inside the world. Avalon interprets intent and integrates it directly into the live multiplayer environment. This is not a world model predicting video. This is a gameplay engine that understands language. If you can describe it, you can build it. And others can walk into it instantly.

AVALON

65,243 просмотров • 7 месяцев назад

We’re launching a brand new, full-stack vibe coding experience in Google AI Studio, made possible by integrations with the Google Antigravity coding agent and Firebase backends. This unlocks: — Full-stack multiplayer experiences: Create complex, multiplayer apps with fully-featured UIs and backends directly within AI Studio — Connection to real-world services: Build applications that connect to live data sources, databases, or payment processors and the Antigravity agent will securely store your API credentials for you — A smarter agent that works even when you don't: By maintaining a deeper understanding of your project structure and chat history, the agent can execute multi-step code edits from simpler prompts. It also remembers where you left off and completes your tasks while you’re away, so you can seamlessly resume your builds from anywhere — Configuration of database connections and authentication flows: Add Firebase integration to provision Cloud Firestore for databases and Firebase authentication for secure sign-in This demo displays what can be built in the new vibe coding experience in AI Studio. Geoseeker is a full-stack application that manages real-time multiplayer states, compass-based logic, and an external API integration with Google Maps 🕹️
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We’re launching a brand new, full-stack vibe coding experience in Google AI Studio, made possible by integrations with the Google Antigravity coding agent and Firebase backends. This unlocks: — Full-stack multiplayer experiences: Create complex, multiplayer apps with fully-featured UIs and backends directly within AI Studio — Connection to real-world services: Build applications that connect to live data sources, databases, or payment processors and the Antigravity agent will securely store your API credentials for you — A smarter agent that works even when you don't: By maintaining a deeper understanding of your project structure and chat history, the agent can execute multi-step code edits from simpler prompts. It also remembers where you left off and completes your tasks while you’re away, so you can seamlessly resume your builds from anywhere — Configuration of database connections and authentication flows: Add Firebase integration to provision Cloud Firestore for databases and Firebase authentication for secure sign-in This demo displays what can be built in the new vibe coding experience in AI Studio. Geoseeker is a full-stack application that manages real-time multiplayer states, compass-based logic, and an external API integration with Google Maps 🕹️

Google AI

4,754,203 просмотров • 6 месяцев назад

INTRODUCING ELECTIONHUB 🔵🔴 A live war room for US elections. Powered by real money, not polls. 2028 is already shaping up to be one of the most competitive presidential races in modern history. 4 ways to see the race: -Treemap — candidates sized by win probability -US Shape — odds mapped onto the actual country -Chart — full price history for any candidate -2024 Timelapse — replay how odds moved in real time Plus live 2026 midterm maps: -Senate races, state by state -House districts, all 435 -Governor races + balance of power Live WebSocket — prices move the second the market moves. No refresh. Polymarket called 2024 correctly when every major poll was wrong. This is where you track what smart money says next.
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INTRODUCING ELECTIONHUB 🔵🔴 A live war room for US elections. Powered by real money, not polls. 2028 is already shaping up to be one of the most competitive presidential races in modern history. 4 ways to see the race: -Treemap — candidates sized by win probability -US Shape — odds mapped onto the actual country -Chart — full price history for any candidate -2024 Timelapse — replay how odds moved in real time Plus live 2026 midterm maps: -Senate races, state by state -House districts, all 435 -Governor races + balance of power Live WebSocket — prices move the second the market moves. No refresh. Polymarket called 2024 correctly when every major poll was wrong. This is where you track what smart money says next.

Pentagon Pizza Watch

41,871 просмотров • 5 месяцев назад

I BUILT A BOT THAT PREDICTS NBA GAMES BEFORE TIPOFF. IT RUNS EVERY DAY AT 5:00 PM. HERE'S WHAT'S INSIDE. Three data sources. Three probability layers. One automated pipeline. No manual input. Every evening the bot wakes up. Pulls today's NBA slate. Builds features from live data.Generates predictions. Sends them to me before the first whistle. The ML layer: XGBoost on three seasons of data. Four Factors. ELO ratings. Net rating. Pace. Back-to-back fatigue. Rest days. Travel distance. Every stat computed only from data available before the game. No future leakage. Ever. The sportsbook layer: spread and moneyline converted into implied probabilities. The spread alone contains the aggregated intelligence of an entire betting market. The bot doesn't fight it. It absorbs it. The Polymarket layer: live crowd-sourced probabilities from a decentralized prediction market. No vig. Prices shift in seconds when a star sits out. The bot pulls them through the Gamma API in real time. Then all three layers talk to each other. All three agree - high confidence bet. Polymarket diverges from the books - someone knows something. My model diverges from both - either I found edge or I found noise. The bot flags every disagreement automatically. The fourth layer: Claude API reads everything. Injury reports. Schedule context. Matchup history. Generates a written explanation for every single prediction. No black box. Every call has reasoning attached. The stack: Python. nba_api. pandas. XGBoost. scikit-learn. SHAP. Polymarket Gamma API. Claude API. Flask. GitHub Actions. It took mass of work to build. It takes zero effort to run. 5:00 PM ET. Every day. Predictions land before tipoff. Trading here: I didn't build a model. I built a machine.
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I BUILT A BOT THAT PREDICTS NBA GAMES BEFORE TIPOFF. IT RUNS EVERY DAY AT 5:00 PM. HERE'S WHAT'S INSIDE. Three data sources. Three probability layers. One automated pipeline. No manual input. Every evening the bot wakes up. Pulls today's NBA slate. Builds features from live data.Generates predictions. Sends them to me before the first whistle. The ML layer: XGBoost on three seasons of data. Four Factors. ELO ratings. Net rating. Pace. Back-to-back fatigue. Rest days. Travel distance. Every stat computed only from data available before the game. No future leakage. Ever. The sportsbook layer: spread and moneyline converted into implied probabilities. The spread alone contains the aggregated intelligence of an entire betting market. The bot doesn't fight it. It absorbs it. The Polymarket layer: live crowd-sourced probabilities from a decentralized prediction market. No vig. Prices shift in seconds when a star sits out. The bot pulls them through the Gamma API in real time. Then all three layers talk to each other. All three agree - high confidence bet. Polymarket diverges from the books - someone knows something. My model diverges from both - either I found edge or I found noise. The bot flags every disagreement automatically. The fourth layer: Claude API reads everything. Injury reports. Schedule context. Matchup history. Generates a written explanation for every single prediction. No black box. Every call has reasoning attached. The stack: Python. nba_api. pandas. XGBoost. scikit-learn. SHAP. Polymarket Gamma API. Claude API. Flask. GitHub Actions. It took mass of work to build. It takes zero effort to run. 5:00 PM ET. Every day. Predictions land before tipoff. Trading here: I didn't build a model. I built a machine.

zostaff

48,649 просмотров • 5 месяцев назад