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Partners to develop AI hardware and software for autonomous vehicles -- Softei.com

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Videantis, which provides automotive deep learning, computer vision and video coding solutions, has announced that it will partner with the Fraunhofer Institute for Integrated Circuits IIS, Infineon and other leading companies and universities to develop an artificial intelligence (AI) ASIC and software development tools specifically for intelligent autonomous vehicles. The Videantis AI multi-core processor platform and tool flow has been selected for the KI-Flex autonomous driving chip project. Autonomous driving relies on fast and reliable processing and merging of data from several lidar, camera and radar sensors in the vehicle. This data can provide an accurate picture of the traffic conditions and environment to allow the vehicle to make intelligent decisions when driving. The process of intelligently analysing these volumes of sensor data requires high-performance, efficient, and versatile compute solutions.


NXT – Data Engineer ai-jobs.net

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Citadel is a global investment firm built around world-class talent, sound risk management, and innovative leading-edge technology. For a quarter of a century, Citadel's hedge funds have delivered meaningful and measurable results to top-tier investors around the world, including sovereign wealth funds, public institutions, corporate pensions, endowments and foundations. With an unparalleled ability to identify and execute on great ideas, Citadel's team of more than 675 investment professionals, operating from offices including Chicago, New York, San Francisco, London, Hong Kong and Shanghai, deploy capital across all major asset classes, in all major financial markets.


A marriage of microscopy and machine learning

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With a dish of cells as a canvas, Anne Carpenter's collaborators apply layers of color. Each one highlights a different cellular feature: A fluorescent blue dye to stain the nuclei. Orange to label the cell membranes. This approach, called "Cell Painting," uses six biological dyes to stain eight major cell structures. Together, they create not just beautiful images, but also a detailed portrait of the cells' size, shape or morphology, and--if you can read the signs--physiological state.


[Interview] How AI, robotics and digital technologies are transforming healthcare

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New Delhi: Advances in technology and medical research could mean seismic changes in the healthcare industry. Soon, cancer, heart disease, diabetes and other debilitating illnesses could be defeated - perhaps, 20 years from now (unbelievable as it may sound) - thanks to scientists, medical doctors and researchers who are working vigorously, making stupendous progress on all these fronts. Over the last decade, healthcare is one of the industries that has evolved the most, yet, we're going to see changes in the way diseases are being treated. It's evident that we're going to witness drastic changes in a number of dimensions - from robots in the role of healthcare professionals to smart technology and artificial intelligence tools that will improve the quality of care and population health. Dr Sanjay Pandey, Head - Andrology and Reconstructive Urology - Kokilaben Dhirubhai Ambani Hospital, Mumbai, spoke on how digital technology, robotics and AI are transforming the face of medicine.


Fintech profile: Lemonade, the AI-driven insurtech

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As of December 2019, there are more than 400 unicorns worldwide - that's according to the aptly named Global Unicorn Club report from CB Insights. A significant number of those, private companies valued at more than $1bn for the uninitiated, are firmly entrenched in the financial services sector. One such company is Lemonade. The New York-based business uses artificial intelligence, chatbots and other innovative technologies to disrupt the home and rental insurance sectors. It recently appeared in FinTech magazine's Top 10 Unicorns list, which provided a comprehensive snapshot of those most innovative companies to achieve this coveted status.


From local explanations to global understanding with explainable AI for trees

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Tree-based machine learning models such as random forests, decision trees and gradient boosted trees are popular nonlinear predictive models, yet comparatively little attention has been paid to explaining their predictions. Here we improve the interpretability of tree-based models through three main contributions. We apply these tools to three medical machine learning problems and show how combining many high-quality local explanations allows us to represent global structure while retaining local faithfulness to the original model. These tools enable us to (1) identify high-magnitude but low-frequency nonlinear mortality risk factors in the US population, (2) highlight distinct population subgroups with shared risk characteristics, (3) identify nonlinear interaction effects among risk factors for chronic kidney disease and (4) monitor a machine learning model deployed in a hospital by identifying which features are degrading the model's performance over time. Given the popularity of tree-based machine learning models, these improvements to their interpretability have implications across a broad set of domains.


How to build ethical AI

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You've likely already encountered artificial intelligence several times today. But for most people, the term AI still conjures images of The Terminator. We don't need to worry about hulking armed robots terrorizing American cities, but there are serious ethical and societal issues we must confront quickly -- because the next wave of computing power is coming, with the potential to dramatically alter -- and improve -- the human experience. Full disclosure: I am general counsel and chair of the AI Ethics Working Group at a company that is bringing AI to processor technology in trillions of devices to make them smarter and more trustworthy. Enabled by high-speed wireless capacity and rapid advances in machine learning, new applications for artificial intelligence are created every day.


Why digital transformation is now on the CEO’s shoulders

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When science and technology meet social and economic systems, you tend to see something akin to what the late Stephen Jay Gould called "punctuated equilibrium" in his description of evolutionary biology. Something that has been stable for a long period is suddenly disrupted radically--and then settles into a new equilibrium.1 1.See Stephen Jay Gould, Punctuated Equilibrium, Cambridge, MA: Harvard University Press, 2007. Gould pointed out that fossil records show that species change does not advance gradually but often massively and disruptively. After the mass extinctions that have occurred several times across evolutionary eras, a minority of species survived and the voids in the ecosystem rapidly filled with massive speciation. Gould's theory addresses the discontinuity in fossil records that puzzled Charles Darwin.


What Smart Cities Are Learning From Smart Farms

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Cities around the world are getting smarter. Already, street lights in places like San Diego are turning off, and conserving energy, when vehicles and pedestrians aren't around. Soon, connected garbage cans will tell waste haulers when they need to be emptied, optimizing collection routes. Smart buildings will notify maintenance staff of impending repair needs. And parking spots will find you, instead of the other way around.


Whoever leads in artificial intelligence in 2030 will rule the world until 2100

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A couple of years ago, Vladimir Putin warned Russians that the country that led in technologies using artificial intelligence will dominate the globe. He was right to be worried. Russia is now a minor player, and the race seems now to be mainly between the United States and China. But don't count out the European Union just yet; the EU is still a fifth of the world economy, and it has underappreciated strengths. Technological leadership will require big digital investments, rapid business process innovation, and efficient tax and transfer systems.