正在加载视频...

视频加载失败

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

147,396 次观看 • 2 个月前 •via X (Twitter)

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

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

62,252 次观看 • 5 个月前

7 repos that mass replace a $50,000/year sports analytics department. all free. all open source. -> replaces Hawkeye-level court analysis YOLO tracks players and ball from any broadcast. ResNet50 extracts court keypoints. homography converts pixels to real meters. speed, position, aggression - all from a TV feed. -> replaces paid sports data subscriptions ($500/mo) every ATP match since 1968. rankings, results, stats. 1.5K stars. the holy grail dataset that every tennis ML project is built on. -> replaces point-level data feeds ($200/mo) point-by-point data for every Grand Slam since 2011. the kind of granularity you need for live Bayesian models. -> replaces shot-by-shot scouting reports 5,000+ matches charted shot by shot. direction, depth, error type. crowdsourced and free. -> replaces pre-match and in-match prediction services ELO + serve/return stats → win probability. updates during the match. exactly what a live Bayesian engine needs. -> replaces ball trajectory prediction tools CV analysis + CatBoost bounce prediction + separate court detector neural net. most advanced open-source tennis CV pipeline. -> replaces traditional bookmaker APIs Polymarket CLOB API. real-time share prices, orderbook depth, bid/ask spreads. no margin, no bookmaker - just the crowd. trade positions mid-match, not just pre-match. total before: $50K/year sports analytics stack total now: $0 like + bookmark you'll need this when you build your first tennis bot

zostaff

35,652 次观看 • 2 个月前