Sign in to report inappropriate content. Video with transcript included: http://bit.ly/37yYBaD Matt Ranney explains the architecture of Uber ATG's self-driving cars and takes a look at how the software is developed, tested, and deployed. This presentation was recorded at QCon San Francisco 2019: http://bit.ly/38sivWf The next QCon is QCon London 2020 – March 2-4, 2020: http://bit.ly/2VfRldq

Virginia Commonwealth University School of the Arts in Qatar (VCUarts Qatar) is hosting a lecture by Dr James She from Hong Kong University of Science and Technology (HKUST), titled, 'AI and Smartphone Technologies for New Artwork Creation, Interaction and Definition'. The lecture will take place this Tuesday, 18 February, 12:30 pm, at the VCUarts Qatar Atrium. The event is open to everyone. Emerging Artificial Intelligence (AI) and smartphone technologies are making disruptive changes and new possibilities for people in business, manufacturing, travel, education and even art. In this talk, examples of AI and smartphone technologies will be selected to show how recent developments in those technologies could facilitate the creation of, and interaction with, artworks.

Arguably, Artificial intelligence or AI debuted at a conference at Dartmouth University in 1956. At the time, there was a lot of optimism. Some people at the conference believed robots and AI machines would be doing the work of humans by the mid-1970s. Of course, that didn't happen -- what happened instead was that funding dried up and a period called "The AI Winter" began. That ostensibly lasted into the 2000s, when IBM's Watson peaked a lot of interest in artificial intelligence again.

The world never changes quite the way you expect. But at The Verge, we've had a front-row seat while technology has permeated every aspect of our lives over the past decade. Some of the resulting moments -- and gadgets -- arguably defined the decade and the world we live in now. But others we ate up with popcorn in hand, marveling at just how incredibly hard they flopped. This is the decade we learned that crowdfunded gadgets can be utter disasters, even if they don't outright steal your hard-earned cash. It's the decade of wearables, tablets, drones and burning batteries, and of ridiculous valuations for companies that were really good at hiding how little they actually had to offer. Here are 84 things that died hard, often hilariously, to bring us where we are today. Everyone was confused by Google's Nexus Q when it debuted in 2012, including The Verge -- which is probably why the bowling ball of a media streamer crashed and burned before it even came to market.

Artificial intelligence--code that learns--is likely to be humankind's most important invention. It's a 60-year-old idea that took off five years ago when fast chips enabled massive computing and sensors, cameras, and robots fed data-hungry algorithms. We're a couple of years into a new age where machine learning (a functional subset of AI), big data and enabling technologies are transforming every sector. In every sector, there is a big data set behind every question. Every field is computational: healthcare, manufacturing, law, finance and accounting, retail, and real estate.

AI has been one of the biggest buzzwords in the technology industry over the past few years, given its immense potential to transform our world. With more tasks being performed with AI, the enterprise adoption of this nascent technology is rapidly evolving. From business planning and forecasting to predictive maintenance and customer service, AI is now an intrinsic part of an enterprise ecosystem. The potential of AI is limitless, but certain barriers are holding traditional large enterprises back from embracing AI in a big way. These include factors such as the absence of a clear strategy, lack of data, skills shortage, and functional silos within the organization.

Heather Culbertson is a Gabilan Assistant Professor of Computer Science at the University of Southern California. Her research focuses on the design and control of haptic devices and rendering systems, human-robot interaction, and virtual reality. Particularly she is interested in creating haptic interactions that are natural and realistically mimic the touch sensations experienced during interactions with the physical world. Previously, she was a research scientist in the Department of Mechanical Engineering at Stanford University where she worked in the Collaborative Haptics and Robotics in Medicine (CHARM) Lab. She received her PhD in the Department of Mechanical Engineering and Applied Mechanics (MEAM) at the University of Pennsylvania in 2015 working in the Haptics Group, part of the General Robotics, Automation, Sensing and Perception (GRASP) Laboratory.

India is currently the hotbed for emerging technologies like AI & machine learning. But the need of the hour is "Deep Tech" which fundamentally is a connection of different types of technologies, not just AI & ML but also computer vision, image processing, blockchain, and AR/VR, to come up with a solution that is not trivial but a revolutionary one. However, there are a few limitations such as the skills of the engineering graduates in India to meet this demand, the quality of data in India continues to be an issue because of the diversity of demographics, languages etc. in the Indian market which could slow the momentum. With a passion for solving such issues in India, Bangalore-based Dhiyo is utilising AI and machine learning to help the folks to solve job market inefficiencies for the blue-collar sector by building a quick prototype using Google Assistant. Founded by Santhosh SS in 2018, Dhiyo is a Conversational AI interface for the job seekers in the informal sector who can create their profile or resume just by speaking to their smartphone through a series of voice commands in their own native language.

Employees toil at lines, doing the same task, repeatedly, in order to assemble a final product. A line stoppage or bottleneck can cost a fortune. What if the manufacturer could see what was going on, in real time, and fix any issues before they become real problems? Or come up with ways to make the process run smoother and more efficiently? That's the basic idea behind Drishti Technologies, a four-year-old startup cofounded by Prasad Akella, a 57-year-old Indian entrepreneur who's best known for leading the General Motors team that developed collaborative robots in the 1990s.

Dave Aitel is the founder and CTO of Immunity. You can follow him @daveaitel. Export control on AI and machine learning algorithms is becoming a more important part of national security strategy as the world moves to a great-power competition landscape and technological changes force accommodation and rapid change to many national interests. However, like security software before it, AI presents unique challenges to how export control has traditionally worked, and these should be considered before being codified into international regulatory frameworks. As an example, on January 6, 2020, The Bureau of Industry and Security (BIS) in the U.S. Department of Commerce released the following rule, which imposed a license requirement on a particular kind of software useful for automatically identifying objects from drone or other imagery: "Geospatial imagery "software" "specially designed" for training a Deep Convolutional Neural Network to automate the analysis of geospatial imagery and point clouds, and having all of the following: Technical Note: A point cloud is a collection of data points defined by a given coordinate system. A point cloud is also known as a digital surface model."