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Startup Machine Learning Companies: The Top 10 Machine Learning Startups

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Machine learning (ML) is one of the hottest and most lucrative tech trends. According to a survey on the state of AI conducted by McKinsey in 2021, 67 percent of companies that adopted AI-related technologies saw increases in revenue. Increased adoption of ML technology has given rise to some of the best machine learning startups, all of which are leading the digital transformation in the 21st Century. These machine learning startup companies are located around the globe, including San Francisco, Santa Clara, San Jose, San Mateo, Redwood City, and the rest of Silicon Valley, as well as places like London and Tel Aviv. This article will explore exciting startups in the private sector and public sector, looking at their innovative ideas, funding, and expected growth.


Recommender Systems Handbook: Ricci, Francesco, Rokach, Lior, Shapira, Bracha: 9781071621967: Amazon.com: Books

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Lior Rokach is a computer scientist. He is a professor and the former chair of the Department of Software and Information Systems Engineering (SISE) at Ben-Gurion University of the Negev (BGU). Lior was born in 1972 in Holon, Israel. He completed his B.Sc., M.Sc., and Ph.D. in 1998,1999, and 2004 respectively at Tel-Aviv University. His research interests lie in designing and analyzing Machine Learning and Data Mining algorithms and their applications in Recommender Systems, Cyber Security, and Medical Informatics.


Traffic jams just a math problem, says Israeli AI firm

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Israel's traffic congestion ranks near the worst among developed economies, but an algorithm can help, says one of the country's IT firms engaged in the auto and mobility sector. ITC, or Intelligent Traffic Control, was one of the artificial intelligence players at Tel Aviv's recent EcoMotion showcase where high-tech and AI firms hope to make transport more efficient and cleaner. Its AI software collects real-time data from road cameras and then sends instructions to manipulate traffic lights based on vehicle flows. "ITC managed to prove mathematically that many traffic jams can be prevented –- if you intervene early enough," said its co-founder and chief technology officer Dvir Kenig, citing a 30 percent drop in traffic at the two junctions using their system. The company says road congestion is a global scourge, calculating that the average driver spends three days a year stuck in traffic, also pumping out greenhouse gas emissions.


La veille de la cybersécurité

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Israel's traffic congestion ranks near the worst among developed economies, but an algorithm can help, says one of the country's IT firms engaged in the auto and mobility sector. ITC, or Intelligent Traffic Control, was one of the artificial intelligence players at Tel Aviv's recent EcoMotion showcase where high-tech and AI firms hope to make transport more efficient and cleaner. Its AI software collects real-time data from road cameras and then sends instructions to manipulate traffic lights based on vehicle flows. "ITC managed to prove mathematically that many traffic jams can be prevented –- if you intervene early enough," said its co-founder and chief technology officer Dvir Kenig, citing a 30 percent drop in traffic at the two junctions using their system. The company says road congestion is a global scourge, calculating that the average driver spends three days a year stuck in traffic, also pumping out greenhouse gas emissions.


AI on the Ball: Startup Shoots Computer Vision to the Soccer Pitch

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Eyal Ben-Ari just took his first shot on a goal of bringing professional-class analytics to amateur soccer players. The CEO of startup Track160, in Tel Aviv, has seen his company's AI-powered sports analytics software tested and used in the big leagues. Now he's turning his attention to underserved amateurs in the clubs and community teams he says make up "the bigger opportunity" among the world's 250 million soccer players. "Almost everyone in professional sports uses data analytics today. Now we're trying to enable any team at any level to capture their own data and analytics, and the only way to do it is leveraging AI," he said.


Traffic jams just a maths problem, says Israeli Artificial Intelligence firm

#artificialintelligence

Israel's traffic congestion ranks near the worst among developed economies but an algorithm can help, says one of the country's IT firms engaged in the auto and mobility sector. ITC, or Intelligent Traffic Control, was one of the artificial intelligence players at Tel Aviv's recent EcoMotion showcase where high-tech and AI firms hope to make transport more efficient and cleaner. Its AI software collects real-time data from road cameras and then sends instructions to manipulate traffic lights based on vehicle flows. "ITC managed to prove mathematically that many traffic jams can be prevented -- if you intervene early enough," said its co-founder and chief technology officer Dvir Kenig, citing a 30 percent drop in traffic at the two junctions using their system. The company says road congestion is a global scourge, calculating that the average driver spends three days a year stuck in traffic, also pumping out greenhouse gas emissions.


A Deeper Understanding of Deep Learning

Communications of the ACM

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.


Here's how AI, computer vision will change driving - EcoMotion 2022

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Earlier this month, the EcoMotion 2022 conference took place, where companies and experts from across the automotive technology industry gathered to showcase the latest innovations defining the sector. Autonomous vehicles were also present at the conference, with new technologies showcased by companies such as the driving system verification platform Foretellix. The company's platform is used by companies like Volvo, MobilEye and Amazon Web Services to verify the safety and viability of the software used to direct Autonomous Vehicles and Advanced Driver-Assistance Systems. The company recently closed a $32m investment round, with its overall capital raised reaching $50m since it was established in 2018. The Renault-Nissan-Mitsubishi Innovation Lab in Tel Aviv was present at the conference, looking for the latest innovations to utilize in future cars and services offered by the alliance members' companies. The lab's mission statement is to advance state-of-the-art mobility, with the main focus on vision sensors, cybersecurity, EV and data & AI.


The World's Most Powerful Deepfake Model was Just Released by Google

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I explain Artificial Intelligence terms and news to non-experts. This new model by Google Research and Tel-Aviv University is incredible. MyStyle is a very powerful deepfake model that can do basically anything. Take a hundred pictures of any person and you have its persona encoded to fix, edit or create any realistic picture you want. This is both amazing and scary, if you ask me, especially when you look at the results.


Your Personal Photoshop Expert with AI!

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This new model by Google Research and Tel-Aviv University is incredible. You can see it as a very, very powerful deepfake that can do anything. Take a hundred pictures of any person and you have its persona encoded to fix, edit or create any realistic picture you want. This is both amazing and scary if you ask me, especially when you look at the results. The model simply uses a pertained StyleGAN architecture, which I covered in numerous videos so I won't enter into the detail of this network.