Cybersecurity is a cat-and-mouse game. And the mouse always has the upper hand. That’s because it’s so easy for new malware to go undetected. Eli David, an expert in computational intelligence, wants to use AI to change that. He’s CTO of Deep Instinct, a security firm with roots in Israel’s defense industry, that is bringing the GPU-powered deep learning techniques underpinning modern speech and image recognition to the vexing world of cybersecurity.
“It’s exactly like Tom and Jerry, the cat and the mouse, with the difference being that, in this case, Jerry the mouse always has the upper hand,” David said in a conversation on the AI Podcast with host Michael Copeland. He notes that more than 1 million new pieces of malware are created every day. Neural networks — which have long been a passion of his — promise to even the odds. “We have seen a revolution in deep neural networks,” David said, crediting GPUs with making them practical. “It takes us about 24 hours in one day to train our artificial brain, had we not run it on GPUs it would have taken three months,” he said.
