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Protecting computer vision from adversarial attacks

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Advances in computer vision and machine learning have made it possible for a wide range of technologies to perform sophisticated tasks with little or no human supervision. From autonomous drones and self-driving cars to medical imaging and product manufacturing, many computer applications and robots use visual information to make critical decisions. Cities increasingly rely on these automated technologies for public safety and infrastructure maintenance. However, compared to humans, computers see with a kind of tunnel vision that leaves them vulnerable to attacks with potentially catastrophic results. For example, a human driver, seeing graffiti covering a stop sign, will still recognize it and stop the car at an intersection.


Could Artificial Intelligence Prepare U.S. Pilots for War Against China and Russia?

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The U.S. Navy and U.S. Air Force are working on a new generation of training technologies to prepare their fighter aircraft for new Russian and Chinese air threats posed by the Su-57 fighter and J-20 fifth-generation stealth aircraft, respectively. Over the next two years, the U.S. Air Force plans to use a cutting-edge computer technology called the P5 Combat Training System (P5CTS), made by a firm called Cubic Mission and Performance Solutions. Information from Cubic describes the P5 as an encryption solution intended to improve U.S. Air Force and U.S. Navy pilot training for advanced, high-threat combat scenarios using advanced computer simulations, wireless networks, and artificial intelligence (AI)-enabled data organization. Interestingly, the P5 pod can be seen in the now-famous Top Gun Maverick movie on a F/A-18 fighter. "Over the course of the last 13 years, we've learned some critical lessons about integrating fast movers with virtual environments to provide a realistic presentation to the aircrew in their cockpits. Having a wireless network that allows you to sustain that environment without interruptions. In other words, a low, flat latency is a very important feature," said Cubic's training expert, Paul Averna.


Swaayatt Robots: Pioneering Reinforcement Learning in Autonomous Driving

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The startup focuses on developing self-driving technology for unstructured environment conditions and India's road network is full of such environments. In the thick of it is founder and CEO Sanjeev Sharma, whose interest in the field of robotics was born way back in 2009, when he watched the videos of Team MIT at the 2007 DARPA Urban Challenge. With time, he knew that he wanted to hone in on research to enable autonomous driving in the most difficult traffic environmental scenarios, but it wasn't until 2014, when Sharma deferred his PhD at the University of Massachusetts for a year, that he established Swaayatt Robots. Fast forward eight years and, despite knowing much more about autonomous mobility than in 2014, safety continues to be a huge challenge. Even before we think of the purchasing and operational cost, we're quite some time away from solving for driver safety in an uncontrolled and unstructured environment -- but Swaayatt Robots is trying to fix that.


Intuit: Credit Karma And Mailchimp Integration A Game Changer (NASDAQ:INTU)

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Many of us are familiar with Intuit's (NASDAQ:INTU) industry-leading products in personal taxes (Turbo Tax) and small business accounting (QuickBooks). However, the company has expanded well beyond these two areas and assembled a portfolio of products that have improved and will continue to improve the financial lives of its customers. On Intuit's website, CEO Sasan Goodarzi described their mission statement as follows: We are a purpose-driven, values-driven company. Our mission to power prosperity around the world is why we show up to work every single day to do incredible things for our customers. Our values guide us and define what we stand for as a company.


AI Makes Strides in Virtual Worlds More Like Our Own

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In 2009, a computer scientist then at Princeton University named Fei-Fei Li invented a data set that would change the history of artificial intelligence. Known as ImageNet, the data set included millions of labeled images that could train sophisticated machine-learning models to recognize something in a picture. The machines surpassed human recognition abilities in 2015. Soon after, Li began looking for what she called another of the "North Stars" that would give AI a different push toward true intelligence. She found inspiration by looking back in time over 530 million years to the Cambrian explosion, when numerous land-dwelling animal species appeared for the first time.


The Go-To-Market Strategy For Autonomous Vehicles: "Launch Somewhere"

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ENGLAND: Two autonomous, delivery robots pass on the pavement as they make home deliveries of ... [ ] groceries. Created by two of the co-founders of Skype in 2014, Starship has developed the self-driving pods for various, logistical tasks. Much more complicated than originally thought. Several manufacturers expected the first self-driving cars to hit the market 3-4 years ago. In fact, Johann Jungwirth of Volkswagen met with Focus Magazine in April of 2016 amongst beanbags, blue suede shoes and skateboards to report the first autonomous vehicles (AVs) will be on the market by 2019.


Artificial Intelligence and Industry 4.0 - (Intelligent Data-Centric Systems) by Aboul Ella Hassanien & Jyotir Moy Chatterjee & Vishal Jain

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Estimated ship dimensions: 1 inches length x 7.5 inches width x 9.25 inches height We regret that this item cannot be shipped to PO Boxes. This item cannot be shipped to the following locations: United States Minor Outlying Islands, American Samoa (see also separate entry under AS), Puerto Rico (see also separate entry under PR), Northern Mariana Islands, Virgin Islands, U.S., APO/FPO, Guam (see also separate entry under GU)


CO2 emissions dataset in USA: a statistical analysis, using Python

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Disclaimer: This notebook has not been written by a climate scientist! Everything is exclusively analyzed by a data scientist point of view. All the statistical analysis are meant to be used as tools for a time series analysis of any kind. Let's start by stating the obvious: The job of a data scientist is to extract insights. The complexity of the tool that you are using is not really relevant.


Artificial intelligence

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Deep learning[133] uses several layers of neurons between the network's inputs and outputs. The multiple layers can progressively extract higher-level features from the raw input. For example, in image processing, lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as digits or letters or faces.[134] Deep learning has drastically improved the performance of programs in many important subfields of artificial intelligence, including computer vision, speech recognition, image classification[135] and others. Deep learning often uses convolutional neural networks for many or all of its layers.


Artificial Intelligence in Accounting Market Size Analysis, Current Status and Forecast 2022-2028 : IBM, Google, Deloitte - Digital Journal

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New Jersey, NJ -- (SBWIRE) -- 06/24/2022 -- Latest survey on Artificial Intelligence in Accounting Market is conducted to provide hidden gems performance analysis of Artificial Intelligence in Accounting to better demonstrate competitive environment . The study is a mix of quantitative market stats and qualitative analytical information to uncover market size revenue breakdown by key business segments and end use applications. The report bridges the historical data from 2016 to 2021 and forecasted till 2028*, the outbreak of latest scenario in Artificial Intelligence in Accounting market have made companies uncertain about their future outlook as the disturbance in value chain have made serious economic slump. Some are the key & emerging players that are part of coverage and profiled in the study are Microsoft (US), AWS (US), Xero (New Zealand), Intuit (US), Sage (England), OSP (US), UiPath (US), Kore.ai (US), AppZen (US), YayPay (US), IBM (US), Google (US), EY (UK), Deloitte (US), PwC (UK), KPMG (Netherlands), SMACC (Germany), OneUp (US), Vic.ai (US), Hyper Anna (Australia), Botkeeper (US) & MindBridge Analytics (Canada). If you are part of the Artificial Intelligence in Accounting industry or intend to be, then study would provide you comprehensive outlook.