This Harvard Professor And His Students Have Raised $14 Million To Make AI Too Smart To Be Fooled By Hackers

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A Harvard professor and his students have raised $14 million to quash adversarial AI attacks

By adding a few pixels to a legitimate check, fraudsters can trick artificial intelligence models into mistaking a $401 check for one worth $701. Undetected, the exploit could lead to large-scale financial fraud.Yaron Singer climbed the tenure track ladder to a full professorship at Harvard in seven years, fueled by his work on adversarial machine learning, a way to fool artificial intelligence models using misleading data.

Enter Robust Intelligence, a new startup led by CEO Singer with a platform that the company says is trained to detect more than 100 types of adversarial attacks. Though its founders and most of the team hold a Cambridge pedigree, the startup has established headquarters in San Francisco and announced Wednesday that it had raised $14 million in a seed and Series A round led by Sequoia.

Fraudsters and other bad actors can exploit the relative inflexibility of artificial intelligence models in processing unfamiliar data. For example, Singer says, a check for $401 can be manipulated by adding a few pixels that are imperceptible to the human eye yet cause the AI model to read the check erroneously as $701. “If fraudsters get their hands on checks, they can hack into these apps and start doing this at scale,” Singer says.

 

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