IBM Research Tokyo

Real-Time Sequential Decision-Making by Autonomous Agents

A new approach to real-time sequential decision-making represents a step towards autonomous agents that can make critical decisions in real time.

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Bio-inspired machine learning goes open source

Since our bio-inspired machine learning technology “Dynamic Boltzmann Machine (DyBM)” debuted in the fall of 2015, we received many comments on the music demo and human evolution image that we used to show how an artificial neural network learns about different topics in different formats. Many developers expressed interest in using the code to let […]

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Realizing a barrier-free society

Field experiment at a busy shopping district in Tokyo Tokyo’s underground consists of miles of pedestrian walkways, extensive shopping arcades and a subway network. It stretches for hundreds of kilometers between more than 200 subway stations. Even with a map and a good sense of direction, it is not necessarily an easy place to navigate. […]

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