AMI Labs raises $1.03 billion for real-world AI

Machine Learning


Advanced Machine Intelligence (AMI) is building a new kind of AI system that understands the world, has persistent memory, can reason and plan, and is controllable and secure.

The company has raised US$1.03 billion from investors around the world. The round was co-led by Cathay Innovation, Greycroft, Hiro Capital, HV Capital, Bezos Expeditions, and other investors and angels from around the world.

AMI is also supported by a group of long-term global investors and strategic supporters, including Toyota Ventures, New Legacy Ventures, Temasek, SBVA, NVIDIA, Mark Cuban, Association Familiale Mulliez, Groupe industriel Marcel Dassault, Sea, and Alpha Intelligence Capital.

Eric Schmidt also has an important participation, Aglaé Lab, ZEBOX Ventures, Artémis, Xavier Niel, Publicis Groupe, Samsung, Bpifrance Digital Venture, Jim Breyer, Tim and Rosemary Berners-Lee, Mark Leslie.

“We are a growing team of researchers and builders, active in Paris, New York, Montreal and Singapore since our inception,” the company said.

The main goal of AMI is to build intelligent systems that understand the real world, where data is continuous, high-dimensional, and noisy, regardless of whether the data is acquired through cameras or other sensor modalities.

Generative architectures trained through self-supervised learning to predict the future have shown remarkable success in language understanding and production. However, much of the real-world sensor data is unpredictable, and generative approaches do not work well.

AMI develops world models that learn abstract representations of real-world sensor data and make predictions in the representation space, ignoring unpredictable details.

Action-conditional world models allow agent systems to predict the outcomes of actions and plan sequences of actions to accomplish tasks, subject to safety guardrails.

AMI will advance AI research to develop applications where reliability, control, and safety are truly critical, especially in industrial process control, automation, wearable devices, robotics, and healthcare.

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