Deep learning should not work as well as it seems to: according to traditional statistics and machine learning, any analysis that has too many adjustable parameters will overfit noisy training data, and then fail when faced with novel test data. In clear violation of this principle, modern neural networks often use vastly more parameters than data points, but they nonetheless generalize to new data quite well. The shaky theoretical basis for generalization has been noted for many years. One proposal was that neural networks implicitly perform some sort of regularization--a statistical tool that penalizes the use of extra parameters. Yet efforts to formally characterize such an "implicit bias" toward smoother solutions have failed, said Roi Livni, an advanced lecturer in the department of electrical engineering of Israel's Tel Aviv University.
A research team has proposed non-contrast thoracic chest CT scans as an effective tool for detecting, quantifying, and tracking COVID-19. As of March 16, the COVID-19 pandemic had a confirmed infection total of more than 170,000 people around the globe. The speed of transmission of COVID-19 has surprised the world and had a massive impact on people's daily lives and the global economy. To accelerate COVID-19 detection and support efforts to combat the epidemic, researchers from RADLogics, Tel-Aviv University, New York Mount Sinai Hospital and University of Maryland School of Medicine developed an AI-based approach designed to help identify infected patients and quantify disease burden by analyzing thoracic CT (Computer Tomography, aka CAT) exams. Data sources for new epidemic diseases such as COVID-19 remain limited, as does expertise.
The internationally renowned Dan David Prize, headquartered at Tel Aviv University, annually awards three prizes of $1 million each to globally inspiring individuals and organizations. The total purse of $3 million makes the prize not only one of the most prestigious, but also one of the highest-value prizes internationally. Laureates are selected on the basis of their outstanding achievements and contributions in the year's chosen fields, each representing a time category. This year's fields are Cultural Preservation and Revival (Past category), Gender Equality (Present category) and Artificial Intelligence (Future category). Professor Amnon Shashua, co-founder and CEO of Mobileye, and Dr. Demis Hassabis, co-founder and CEO of DeepMind, have been named the 2020 Dan David Prize laureates in the field of artificial intelligence (AI).
Abeja: This Japanese startup, founded in 2012, creates AI software for retailers and manufacturers and is backed by Salesforce and NTT DOCOMO, among others. Deepgram: This Mountain, View, Calif., startup has created AI that understands human speech. Deepgram's goal: help computers understand what you mean, communicate in real time and leave you satisfied, not frustrated. Deep Instinct: This Tel Aviv startup pioneered the use of AI zero-day attack protection -- using deep learning to identify attacks on vulnerabilities that haven't yet been made public. Entropix: You know those crime shows that show computer-equipped sleuth's enhancing grainy images?
MedyMatch Technology, a company based in Tel Aviv, Israel, leverages artificial intelligence, deep learning, and computer vision technologies to offer patient-specific clinical decision support. Their application helps radiologists and emergency room physicians to detect signs of intracranial hemorrhages, which are difficult to diagnose by standard analysis of imaging data alone. The Medgadget team recently had an opportunity to speak with Gene Saragnese, Chairman and Chief Executive Officer of MedyMatch, to discuss their technology and its significance in depth. Prior to joining MedyMatch in January of 2016, Gene was the Chief Executive Officer of Philips Imaging and a member of Philips Healthcare's Executive Team. A graduate of Rutgers College of Engineering in New Jersey, he has also previously served as GE Healthcare's Chief Technology Officer and has held management roles with GE, RCA, Martin Marietta, and Lockheed Martin.