Nanotechnology - Grenoble, Auvergne-Rhône-Alpes, France
The glorious era of von Neumann computer architectures is behind us. This type of machine has reached its limits, both in terms of technology and applications. There is a lot of excitement (rebooting computing) in the world of information processing to try to imagine and develop alternative concepts. We propose with the startup HawAI.tech an original way whose objective is to develop and promote mathematical methods, algorithms, electronic components, circuits, integrated devices and MACHINES FOR PROBABILISTIC ARTIFICIAL INTELLIGENCE. Three development axes are planned: 1. (B)ASIC : The short-term objective (3 years) is to propose specific probabilistic circuits (Bayesian-ASIC), very low power consumption, suitable for integration into intelligent objects to process sensor information and time series to PERCEIVE and SYNTHESIZE. 2. (B)PU : The medium-term objective (5 years) is to design a Bayesian Processing Unit architecture to increase a computer's ability to perform Monte Carlo simulations in order to PREDICT, ANTICIPATE and DECIDE. 3. (B)LEARN : The longer-term objective (7 years) is to enrich previous architectures by placing mechanisms for LEARNING and ADAPTATION AT THE very heart of their material conceptions.While we have long defended the vision that probabilities are the foundation of the AI of the future as an extension of logic and complement to neural networks and deep learning, we have very recently been joined by Intel, including the CTO, Mike Mayberry, who states that probabilities will be the 3rd wave of AI1. He has just launched a probabilistic computing program at Intel whose objective is "to develop technology that integrates probabilistic models and Monte Carlo inference into programming languages, compilers, runtime systems, and microarchitecture".
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