ThoughtForge AI’s Post

At Robobusiness? Stop by our booth and say Hi!

https://lnkd.in/gWa2hRBC

🚀 Excited to announce that ThoughtForge, in partnership with Siemens and Magna, has been selected by the ARM Institute to tackle the challenge of adaptive robotic insertion of automotive parts using multi-modal artificial Intelligence! 🎉 https://lnkd.in/gk4znmYy This groundbreaking project aims to revolutionize industries like automotive, aerospace, and consumer electronics by developing an autonomous system capable of inserting asymmetrical and oddly shaped parts with the precision and adaptability that currently only humans can achieve. By integrating cutting-edge ML algorithms, real-time sensor data, and innovative edge computing techniques, we're pushing the boundaries of what robotics can do. Stay tuned as we pave the way for a new era of intelligent robotics across multiple industries! #Robotics #AI #Manufacturing #Innovation #TechForGood

There’s a lot of AI hype these days. There is a lot of really great technology coming out everyday. It’s hard to understand what to use, when and why if you’re not AI nerds like us. Active Inference (AIF) is still a relatively new field in neuroscience and there are only three companies using the approach for modeling AI (that we know of) and one (us) with publicly available models to test. And we made a number of innovations to traditional approaches (NetAIF) which enable us to use less data to train our models, making them very small (less than 1 CPU) and able to continue learning post-deployment in real-time (1-2 milliseconds) for on going accuracy. A lot of people ask us how we’re different than LLMs, LAMs, Diffusion Models and other approaches to AI. For the non-engineers and non-scientists in the audience, the way we like to explain the difference is like this: Imagine solving a Rubix cube: - LLMs are great for identifying the instructional path to solve the cube - LAMs would translate those instructions into physical actions - Diffusion models would imitate what a human would do - ThoughtForge’s NetAIF would be what you’d use when the cube gets stuck and you need to jiggle it to turn - for those unpredictable scenarios when you need real time adaptive dexterous control and responsiveness If you’re curious and want to learn more shoot any of us a note, we love talking about it and are happy to share.

At Automate in Chicago? Stop by our booth to see two interactive demos. Robotic AI with no WiFi!! Booth #4490