Whether you're a hobbyist, ML researcher, or large robotics company,
Mbodi AI dramatically reduces time, costs, and engineering efforts, while ensuring your robot operates just as reliably and accurately in new environments as it does in the lab.
End To End Learning
Seamless Integration and Speed
Seamless Integration and Speed
Every visual observation and action taken is pipelined to continually train your Agent or World Model. Iterate through experiments faster, so you can dedicate your time to what matters.
Seamless Integration and Speed
Seamless Integration and Speed
Seamless Integration and Speed
Start training your own world model in as little as 10 lines of code! Integrate seamlessly with NumPy, PyTorch, OpenAI's Gym, and DSPY. Run GPT-4, Claude or your custom VLMs without sacrificing latency.
Diffusion Based Augmentation
Diffusion Based Augmentation
Diffusion Based Augmentation
Even SOTA models can face up to a 50% failure rate in unfamiliar settings. Early research indicates that generative data augmentation can decrease this failure rate by 80%, significantly improving both reliability and accuracy in unfamiliar settings.
Unique Human-Robot Interface
Diffusion Based Augmentation
Diffusion Based Augmentation
Through powerful intra-context learning and the marvel of LLMs, Mbodi AI enables non-ML experts to teach new skills, provide oversight, and even diagnose problems using only voice and demonstration.
Meet the Team
Sebastian Peralta Co-founder and CEO
Roboticist, ML Researcher, and designer of the Serve Stale feature of Google's Public DNS
Xavier (Tianhao) Chi Co-founder
Previous tech lead at Google and "Secret Guardian" of the whole internet
FAQ
Are large language models inherently too slow for robotics?
While Large Language Models (LLMs) are traditionally associated with slower processing times, Mbodi AI's compositional semantic caching, quantization, and model distillation techniques ensure your robot remains rapid and responsive, even in complex analytical tasks.
How does Mbodi AI lead to cost savings?
Mbodi AI streamlines the data collection process, enabling both lower ML expertise and volume of task-specific data requirements to match in-distribution performance. This efficiency allows teams to devote more resources to iterating on experiments and refining outputs, ultimately saving costs and accelerating the development cycle.
Why Not Solely Rely on Simulations?
Real-world experience provides the richest data for refining AI models. Mbodi AI prioritizes actual operational data, utilizing data augmentation only to build upon this foundation. This process effectively filters out inconsequential variations between environments, focusing instead on meaningful data that drives precision and relevance in outcomes.
What We Believe
End-to-end continual learning is crucial to realize the full potential of generative AI. This enables rapid learning and minimal catastrophic forgetting for all multimodal applications during production and streamlined iteration during research.
Our Partners
We're Hiring!
Join Our Team
If you're interested in one of our open positions, start by applying here and attaching your resume.
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