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New study digs deep into neural networks to improve AI security

By intentionally exposing their system to potentially confusing data, researchers build resilience to protect against malicious attacks ....

Jumpei Ukita , Kenichi Ohki , University Of Tokyo , University Of Tokyo Graduate School Medicine , Tokyo Graduate School ,

Brain inspires more robust AI

Brain inspires more robust AI
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Jumpei Ukita , Kenichi Ohki , University Of Tokyo Graduate School Medicine , Department Of Physiology , Professor Kenichi Ohki , Tokyo Graduate School ,

Brain inspires more robust AI

Most artificially intelligent systems are based on neural networks, algorithms inspired by biological neurons found in the brain. These networks can consist of multiple layers, with inputs coming in one side and outputs going out of the other. The outputs can be used to make automatic decisions, for example, in driverless cars. Attacks to mislead a neural network can involve exploiting vulnerabilities in the input layers, but typically only the initial input layer is considered when engineering a defense. For the first time, researchers augmented a neural network’s inner layers with a process involving random noise to improve its resilience. ....

Bunkyo Ku , Jumpei Ukita , Kenichi Ohki , Rohan Mehra , Ohki Lab , Department Of Physiology , Public Relations Group , Takeda Science Foundation , School Of Medicine , Japan Agency For Medical Research , University Of Tokyo Is Japan , Method Of Research , University Of Tokyo , Neural Networks , University Of Tokyo Graduate School Medicine , International Research Center , Masayoshi Son Foundation , Professor Kenichi Ohki , Tokyo Graduate School , Brain Mapping , Integrated Neurotechnologies , Disease Studies , Japan Agency , Medical Research , Research Center , Graduate School ,

Brain inspires more robust AI

Brain inspires more robust AI
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Kenichi Ohki , Jumpei Ukita , University Of Tokyo Graduate School Medicine , Department Of Physiology , Professor Kenichi Ohki , Tokyo Graduate School ,