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.
1:00
Reka
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Research and development of foundational intelligence for the physical world.
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Standard simulated environments lack real-world physics and noise. Interactive World Models get closer, but training them needs video labelled with low-level actions, and real footage rarely has those labels.
Today, we’re releasing the Reka Inverse Dynamics Model (RIDM), a compact model that extracts low-level camera/motor commands directly from raw video.
🕹️Trained entirely on video games
🌐Generalizes to real-world footage
🔐 Weights open-sourced under Apache 2.0
Read the research note and grab the weights on 🤗Hugging Face: reka.ai/news/reka-inve…
#MachineLearning #Robotics #WorldModels #AIResearch #OpenSource
Today, we’re releasing the Reka Inverse Dynamics Model (RIDM), a compact model that extracts low-level camera/motor commands directly from raw video.
🕹️Trained entirely on video games
🌐Generalizes to real-world footage
🔐 Weights open-sourced under Apache 2.0
Read the research note and grab the weights on 🤗Hugging Face: reka.ai/news/reka-inve…
#MachineLearning #Robotics #WorldModels #AIResearch #OpenSource
0:20
Deploying physical AI on wearables and phones requires real-time perception inside extreme thermal and battery limits.
Reka EdgeQ is an optimized on-device VLM running natively on @Qualcomm #Snapdragon 8 Elite’s Hexagon NPU.
⚡️ 0.73s Time to First Token (Image)
📹 +34 pts over Gemma 4 E4B on MLVU video benchmarks
🔋 6.9 mWh energy per inference (~3x lower heat overhead)
By custom-tuning our ConvNeXt V2 vision encoder and decoder directly for the #NPU, EdgeQ keeps the GPU completely idle, minimizing thermal throttling under sustained continuous load.
🔗Our technical breakdown: reka.ai/labs/research/…
#Multimodal #ComputerVision #VLM
Reka EdgeQ is an optimized on-device VLM running natively on @Qualcomm #Snapdragon 8 Elite’s Hexagon NPU.
⚡️ 0.73s Time to First Token (Image)
📹 +34 pts over Gemma 4 E4B on MLVU video benchmarks
🔋 6.9 mWh energy per inference (~3x lower heat overhead)
By custom-tuning our ConvNeXt V2 vision encoder and decoder directly for the #NPU, EdgeQ keeps the GPU completely idle, minimizing thermal throttling under sustained continuous load.
🔗Our technical breakdown: reka.ai/labs/research/…
#Multimodal #ComputerVision #VLM
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VLMs: language, image → language.
Omni: language, image, video, actions → language, image, video, actions.
🚪 Same doors in. It is the way out that changes.
New #AIresearch from Reka Labs on omni-world models shares why unifying VLA and world-model (WAM) approaches under one backbone matters for physical-world intelligence.
reka.ai/labs/research/…
#MultimodalAI #WorldModels #PhysicalAI
Omni: language, image, video, actions → language, image, video, actions.
🚪 Same doors in. It is the way out that changes.
New #AIresearch from Reka Labs on omni-world models shares why unifying VLA and world-model (WAM) approaches under one backbone matters for physical-world intelligence.
reka.ai/labs/research/…
#MultimodalAI #WorldModels #PhysicalAI
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📊 Update: RekaDaily-10k is now complete.
The raw tier finished at 10,865 hours. The processed and captioned tier is live for the first time: 10,200 hours, 6,373,064 clips, 74.2 TB.
Both tiers are on Hugging Face now, fully open under Apache 2.0.
🔗 Read the updated post: reka.ai/labs/research/…
🔗 Get the dataset on Hugging Face 🤗: huggingface.co/datasets/RekaA…
#PhysicalAI #WorldModels #OpenSource #EgocentricData
The raw tier finished at 10,865 hours. The processed and captioned tier is live for the first time: 10,200 hours, 6,373,064 clips, 74.2 TB.
Both tiers are on Hugging Face now, fully open under Apache 2.0.
🔗 Read the updated post: reka.ai/labs/research/…
🔗 Get the dataset on Hugging Face 🤗: huggingface.co/datasets/RekaA…
#PhysicalAI #WorldModels #OpenSource #EgocentricData
reka.ai RekaDaily-10k: Collecting 10,000+ Hours of Egocentric Household Manipulation Data RekaDaily-10k: 10,000+ hours of unscripted first-person household recordings from paid collectors, released under Apache 2.0 in a raw tier and a captioned tier. To train physical AI, synthetic environments and polished, tripod-mounted footage aren't enough. You need the actual mess of the real world.
🚀Releasing RekaDaily-10k: 10,312 hours of unscripted, first-person household footage as collected, recorded by paid collectors in real homes across the US, LatAm, Asia, and Africa, with roughly 1,670 hours in native 4K.
Raw tier available now on @huggingface🤗, full set live by early next week. Apache 2.0. huggingface.co/datasets/RekaA…
Read more reka.ai/news/rekadaily…
This is what Claru, our data engine, produces daily from 100,000+ paid collectors.
#RekaDaily10k #PhysicalAIView quoted post on X