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Senior Data Scientist (Lyon)

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Contentsquare is a global SaaS technology startup that empowers brands to build better digital experiences for all. We've been experiencing tremendous growth within the past few years as our team has grown from 300 to 750 employees, and have recently raised a $190M Series D funding in 2020. In addition, we have 7 main offices across the world (Paris, NYC, London, Tel Aviv, Munich, Tokyo, Singapore) with 700 clients globally including many accounts from the global Fortune 100. We can tell you that this growth is not going to stop here, we still are looking for great talent like you to join our family! Not to brag but… we have been recognized by Gartner as one of the four most innovative ecommerce technologies in the world, and featured in Wired Magazine as one of Europe's hottest startups.


An AI has disproved five mathematical conjectures with no human help

#artificialintelligence

An artificial intelligence has disproved five mathematical conjectures – unproven theorems – despite not being equipped with any information about the problems. Adam Zsolt Wagner at Tel Aviv University in Israel used an AI approach to search for examples that would disprove a range of long-standing conjectures in graph theory, an area of mathematics that involves studying objects made of nodes and links. Mathematicians thought these conjectures were true, but hadn't been able to prove them. For each conjecture, Wagner created a measure of how close an example was to disproving it.


An AI has disproved five mathematical conjectures with no human help

New Scientist

An artificial intelligence has disproved five mathematical conjectures – unproven theorems – despite not being equipped with any information about the problems. Adam Zsolt Wagner at Tel Aviv University in Israel used an AI approach to search for examples that would disprove a range of long-standing conjectures in graph theory, an area of mathematics that involves studying objects made of nodes and links. Mathematicians thought these conjectures were true, but hadn't been able to prove them. For each conjecture, Wagner created a measure of how close an example was to disproving it.


Tel Aviv University And Google Launch 'AI For Social Good' - Zenger News

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A technology enabling the hearing-impaired to conduct phone conversations. Studies on the use of artificial intelligence (AI) to enhance disease diagnosis. These are just a few of the projects initiated by Google Israel intended to make the world a better place using artificial intelligence. Now those projects have a formal home: the "AI for Social Good" program established by Google and Tel Aviv University. The new three-year program, housed at the TAU Center for Artificial Intelligence and Data Science, launched in February under the direction of professor Meir Feder of TAU's Iby and Aladar Fleischman Faculty of Engineering.


Top 25 Machine Learning Startups To Watch In 2021 Based On Crunchbase

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Throughout 2020, venture capital firms continued expanding into new global markets, with London, New York, Tel Aviv, Toronto, Boston, Seattle and Singapore startups receiving increased funding. Out of the 79 most popular A.I. & ML startup locations, 15 are in the San Francisco Bay Area, making that region home to 19% of startups who received funding in the last year. Israel's Tel Aviv region has 37 startups who received venture funding over the last year, including those launched in Herzliya, a region of the city known for its robust startup and entrepreneurial culture. Please see the Roundup Of Machine Learning Forecasts And Market Estimates, 2020 for additional market research on A.I. and machine learning. The following graphic compares the top 10 most popular locations for A.I. & ML startups globally based on Crunchbase data as of today: Augury – Augury combines real-time monitoring data from production machinery with AI and machine learning algorithms to determine machine health, asset performance management (APM) and predictive maintenance (PdM) to provide manufacturing companies with new insights into their operations.


AI InsurTech Enables Pizza Hut Israel's eBikes

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Over the past 13 months, consumers have grown used to the flexibility and convenience of a lifestyle that is more online than ever before. With the rapid progress of this digital shift, businesses are gaining access to more and more consumer data, and the tools for leveraging this data to personalize consumers' experiences are becoming more refined. As consumers grow used to on-demand services and experiences, so do businesses, expecting solutions that meet their specific needs on a moment-to-moment basis. Demandoo, an on-demand insurance provider based in Tel Aviv, Israel, is taking this mindset to the insurance industry, using artificial intelligence (AI) to provide case-by-case risk assessment and offer insurance solutions that meet the specific needs of each customer. Now, the company has partnered with Pizza Hut Israel to insure the company's eBike delivery fleet, a vehicle overlooked by traditional insurance providers.


The Top 20 Machine Learning Startups To Watch In 2021

#artificialintelligence

Throughout 2020, venture capital firms continued expanding into new global markets, with London, New York, Tel Aviv, Toronto, Boston, Seattle and Singapore startups receiving increased funding. Out of the 79 most popular A.I. & ML startup locations, 15 are in the San Francisco Bay Area, making that region home to 19% of startups who received funding in the last year. Israel's Tel Aviv region has 37 startups who received venture funding over the last year, including those launched in Herzliya, a region of the city known for its robust startup and entrepreneurial culture. The following graphic compares the top 10 most popular locations for A.I. & ML startups globally based on Crunchbase data as of today: Augury – Augury combines real-time monitoring data from production machinery with AI and machine learning algorithms to determine machine health, asset performance management (APM) and predictive maintenance (PdM) to provide manufacturing companies with new insights into their operations. The digital machine health technology that the company offers can listen to the machine, analyze the data and catch any malfunctions before they arise.


The Limits of Political Debate

The New Yorker

In February, 2011, an Israeli computer scientist named Noam Slonim proposed building a machine that would be better than people at something that seems inextricably human: arguing about politics. Slonim, who had done his doctoral work on machine learning, works at an I.B.M. Research facility in Tel Aviv, and he had watched with pride a few days before as the company's natural-language-processing machine, Watson, won "Jeopardy!" Afterward, I.B.M. sent an e-mail to thousands of researchers across its global network of labs, soliciting ideas for a "grand challenge" to follow the "Jeopardy!" It occurred to Slonim that they might try to build a machine that could defeat a champion debater. He made a single-slide presentation, and then a somewhat more elaborate one, and then a more elaborate one still, and, after many rounds competing against many other I.B.M. researchers, Slonim won the chance to build his machine, which he called Project Debater.


Decision Trees, Random Forests & Gradient Boosting in R

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Would you like to build predictive models using machine learning? That s precisely what you will learn in this course "Decision Trees, Random Forests and Gradient Boosting in R." My name is Carlos Martínez, I have a Ph.D. in Management from the University of St. Gallen in Switzerland. I have presented my research at some of the most prestigious academic conferences and doctoral colloquiums at the University of Tel Aviv, Politecnico di Milano, University of Halmstad, and MIT. Furthermore, I have co-authored more than 25 teaching cases, some of them included in the case bases of Harvard and Michigan. This is a very comprehensive course that includes presentations, tutorials, and assignments. The course has a practical approach based on the learning-by-doing method in which you will learn decision trees and ensemble methods based on decision trees using a real dataset.


Datagen emerges from stealth to create synthetic datasets for computer vision models

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Datagen, a Tel Aviv, Israel-based startup offering a platform to create synthetic computer vision system training data, today emerged from stealth with $18.5 million in funding from TLV Partners and Viola Ventures. The company says the proceeds will be put toward growing its R&D lab while it expands into new markets globally. Datagen, which Ofir Chakon and Gil Elbaz founded in 2018, leverages computer graphics and data generation to simulate the real world with datasets that include 2D and 3D annotations. By combining generative adversarial networks (GANs) with reinforcement learning-driven humanoid motion algorithms within a physical simulator, Datagen says it can deliver photorealistic, scalable datasets suitable for augmented and virtual reality, internet of things, smart store, robotics, and smart car use cases. GANs are two-part AI models consisting of a generator that creates samples and a discriminator that attempts to differentiate between the generated samples and real-world samples.