Joel Dapello News Today : Breaking News, Live Updates & Top Stories | Vimarsana

Here’s how neuroscience can protect AI from cyberattacks Shares Deep learning has come a long way since the days it could only recognize hand-written characters on checks and envelopes. Today, deep neural networks have become a key component of many computer vision applications, from photo and video editors to medical software and self-driving cars. Roughly fashioned after the structure of the brain, neural networks have come closer to seeing the world as we humans do. But they still have a long way to go and make mistakes in situations that humans would never err. These situations, generally known as adversarial examples, change the behavior of an AI model in befuddling ways. Adversarial machine learning is one of the greatest challenges of current artificial intelligence systems. They can lead machine learning models failing in unpredictable ways or becoming vulnerable to cyberattacks.

Joel dapelloTiago marquesJames dicarloDavid coxWatson ai labLudwig maximilian universityUniversity of munichPhrma foundation postdoctoralUniversity of augsburgPostdoctoral fellowதியகோ மார்க்ஸ்ஜேம்ஸ் திக்கறிலோடேவிட் காக்ஸ்வாட்சன் ஐ ஆய்வகம்லுட்விக் மாக்ஸிமிலியன் பல்கலைக்கழகம்பல்கலைக்கழகம் ஆஃப் முனிச்