Beyond Limits is a pioneering Artificial Intelligence company created to commercialize cutting edge IP developed by Caltech/Jet Propulsion Laboratory (JPL). With technologies proven in the unknown and extreme environment of space, Beyond Limits adapts, enhances, develops, and delivers AI software that tackles industrial and enterprise challenges here on earth. We leverage this existing R&D investment along with many of our own technologies to produce commercial products and solutions that are capable of addressing the emerging problems of AI today and beyond.
Beyond Limits provides advanced intelligence solutions that go far beyond conventional AI. Our cognitive computing technology mimics human thought processes and provides autonomous reasoning to aid human-like decision-making.
Beyond Limits is a unique AI company, with proud Caltech/JPL heritage in our leadership team, and proven technology from the NASA space program. Founded in 2014, the company licensed software systems from Caltech/JPL, to achieve an extraordinary head start in AI innovation. We further enhance these technologies, giving them additional capabilities and hardening them to industrial strength. Beyond Limits 42+ unique IP building blocks represent one of the most comprehensive, cognitive reasoning technology portfolios in the world. Beyond Limits is on a mission to bring our advanced intelligence technology to solve commercial applications here on Earth.
BEYOND CONVENTIONAL AI
Our breakthrough cognitive technology goes beyond conventional AI, blending deep learning and machine learning tools together with symbolic AI that emulates human intuition to produce our cognitive intelligence. Unlike “black box” machine learning solutions that cannot explain their results, a Beyond Limits system provides clear explanations of its cognitive reasoning in transparent, evidence-based audit trails. Our systems are both educated and trained, which greatly reduces the amount of data that is needed to make them intelligent. This means we can solve problems that deep learning approaches alone cannot do.