Reka

@RekaAILabs • 21,599 subscribers

Research and development of foundational intelligence for the physical world.

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Together with NVIDIA , we've built a real-time version of our video generation model: 30B parameters, steerable mid-stream in natural language, 720p at 24fps. 11.8x faster on a single H100, no major quality drop in our blind eval. We're one step closer to World Language Action Models: AI that doesn't just generate the physical world, it acts within it. Closed beta open now, contact us for access. #RekaLabs #NVIDIA #AIResearch #VideoGeneration #WorldModels

Together with NVIDIA , we've built a real-time version of our video generation model: 30B parameters, steerable mid-stream in natural language, 720p at 24fps. 11.8x faster on a single H100, no major quality drop in our blind eval. We're one step closer to World Language Action Models: AI that doesn't just generate the physical world, it acts within it. Closed beta open now, contact us for access. #RekaLabs #NVIDIA #AIResearch #VideoGeneration #WorldModels

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Today, we are releasing a research preview of Rho-1, our 19B omni model that understands and generates text, images, video and robot actions, all inside a single neural network.

Today, we are releasing a research preview of Rho-1, our 19B omni model that understands and generates text, images, video and robot actions, all inside a single neural network.

159,432 просмотров • 9 дней назад

Excited to introduce Reka Vision, an agentic visual understanding and search platform. Transform your unstructured multimodal data into insights and actions.

Excited to introduce Reka Vision, an agentic visual understanding and search platform. Transform your unstructured multimodal data into insights and actions.

485,949 просмотров • 1 год назад

Meet Reka Core, our best and most capable multimodal language model yet. 🔮 It’s been a busy few months training this model and we are glad to finally ship it! 💪 Core has a lot of capabilities, and one of them is understanding video --- let’s see what Core thinks of the 3 body trailer.👇

Meet Reka Core, our best and most capable multimodal language model yet. 🔮 It’s been a busy few months training this model and we are glad to finally ship it! 💪 Core has a lot of capabilities, and one of them is understanding video --- let’s see what Core thinks of the 3 body trailer.👇

758,197 просмотров • 2 лет назад

We are excited to announce the 1st version of our multimodal assistant, Yasa-1, a language assistant with visual and auditory sensors that can take actions via code execution 🪄. Yasa-1 can understand text, images, videos, sounds & more! 🚀 Check out more details below👇

We are excited to announce the 1st version of our multimodal assistant, Yasa-1, a language assistant with visual and auditory sensors that can take actions via code execution 🪄. Yasa-1 can understand text, images, videos, sounds & more! 🚀 Check out more details below👇

814,375 просмотров • 3 лет назад

Training world models needs egocentric video and dense action signals, synchronized. That data is genuinely hard to find. We built it from Counter-Strike 2 demos. CS2-10k: 600K+ player-round videos, 10K+ hours, per-frame annotations — keyboard state, mouse delta, 3D position, camera yaw/pitch. All paired to the visual stream. Why CS2 demos? Matches are deterministic replays. We can reconstruct first-person video and extract the exact control inputs that caused every visual change. No labeling, no estimation. We're also releasing cs2-dem-renderer — the open-source pipeline we used to build it. Give it a .dem file, it outputs .mp4 + .parquet. Run your own dataset at whatever scale you need.

Training world models needs egocentric video and dense action signals, synchronized. That data is genuinely hard to find. We built it from Counter-Strike 2 demos. CS2-10k: 600K+ player-round videos, 10K+ hours, per-frame annotations — keyboard state, mouse delta, 3D position, camera yaw/pitch. All paired to the visual stream. Why CS2 demos? Matches are deterministic replays. We can reconstruct first-person video and extract the exact control inputs that caused every visual change. No labeling, no estimation. We're also releasing cs2-dem-renderer — the open-source pipeline we used to build it. Give it a .dem file, it outputs .mp4 + .parquet. Run your own dataset at whatever scale you need.

95,620 просмотров • 3 месяцев назад

Meet Reka Edge – Our next-generation vision language model for physical AI. Uses 3x fewer input tokens and achieves 65% faster throughput compared to leading 8B models. Image understanding, video analysis, object detection, and tool use. Built for Action. Fast enough for production, deployable anywhere. Read more:

Meet Reka Edge – Our next-generation vision language model for physical AI. Uses 3x fewer input tokens and achieves 65% faster throughput compared to leading 8B models. Image understanding, video analysis, object detection, and tool use. Built for Action. Fast enough for production, deployable anywhere. Read more:

54,146 просмотров • 7 месяцев назад

🤔What does it take to train an omni world model from scratch? 📽️Petabytes of video. 6⃣pipeline stages. And every improvement in data quality pays off twice when you're training a model that both generates and understands video. Our Reka Labs' data team on how it works → #PhysicalAI #WorldModels #AI #RekaLabs

🤔What does it take to train an omni world model from scratch? 📽️Petabytes of video. 6⃣pipeline stages. And every improvement in data quality pays off twice when you're training a model that both generates and understands video. Our Reka Labs' data team on how it works → #PhysicalAI #WorldModels #AI #RekaLabs

15,316 просмотров • 3 месяцев назад

Most evaluations of world models ask, "Does this look right?" 🌎 We built WorldModelGym to ask a different question: if an agent actually uses this model to make decisions, does it still choose well? 🏋️🏃‍♂️🏁🦾 A simulation can look physically plausible and still lead an agent completely astray. 📉⚠️ Stay tuned. More tomorrow at 👀

Most evaluations of world models ask, "Does this look right?" 🌎 We built WorldModelGym to ask a different question: if an agent actually uses this model to make decisions, does it still choose well? 🏋️🏃‍♂️🏁🦾 A simulation can look physically plausible and still lead an agent completely astray. 📉⚠️ Stay tuned. More tomorrow at 👀

16,398 просмотров • 3 месяцев назад

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