CVML Live Web Lecture Series Concept Artificial Intelligence and Information analysis (AIIA) Lab, AUTH is proud to launch the live CVML Web lecture series that will cover very important topics Computer vision/machine learning. Top scientists internationally will deliver these lectures, aiming at providing in-depth knowledge on various CVML topics. The 1-hour lectures will take place on Saturdays, to avoid conflicts with other intended registrant schedules/duties: a) Saturdays 11:00 EET (17:00 Beijing time) and b) Saturdays 20:00 EET (13:00 EST, 10:00 PST for NY/LA, respectively) for audience in the Americas. Each lecture will be announced at least 1 week in advance in various relevant email lists and in this page. Lectures will consist primarily of live lecture streaming and PPT slides.

New centre aspires to be an international think-tank that promotes inter-disciplinary research into the interactions between technology and the law. The new Centre for Technology, Robotics, Artificial Intelligence & the Law (TRAIL), a research unit under the National University of Singapore Faculty of Law (NUS Law), was launched today by Mr Edwin Tong, Senior Minister of State for Law and Health, at the 8th Asian Privacy Scholars Network (APSN) Conference. Leveraging NUS Law's preeminent position amongst the top law schools in the world, TRAIL aspires to be an international think-tank that enables inter-disciplinary communities to research into legal, ethical, policy, philosophical and regulatory questions associated with the use and development of information technology (IT), artificial intelligence (AI), data analytics and robotics in the practice of law. The Centre plans to conduct research into the interactions between technology and the law in a more integrated and holistic manner. TRAIL also aims to provide a forum for legal and non-legal scholars interested in various aspects of technology law, to collaborate and advance inter-disciplinary research.

Russian researchers have developed new artificial intelligence (AI) capable of reading a person's brain activity in real time and simultaneously visualise it in the form of an image. Their research could be the first step towards the development of a real-time brain-computer interface. The discovery could lead to the development of new non-invasive methods for post-stroke rehabilitation. Researchers from the Moscow Institute of Physics and Technology (MIPT) in Russia have developed artificial intelligence capable of reading a person's neural activity in real time, as reported by the website Developpez.com. The work was conducted in collaboration with the Russian company Neurobotics, which specialises in the design of algorithms based on brain activity.

Over the years, artificial intelligence has amazed everyone with numerous breakthroughs, and this year it was no different. The whole year, we witnessed awe-inspiring innovations in reinforcement learning, neural networks, among others. Tech companies from across the world benchmarked various leaps in artificial intelligence to further eliminated the doubts people had about achieving true AI. As a chronicler of the technological progress in the space of analytics, artificial intelligence, data science and big data, among others, Analytics India Magazine was on top of every jaw-dropping development. We bring to you the top 7 amazing AI advancements that changed the world forever.

In this longish post, I have tried to explain Deep Learning starting from familiar ideas like machine learning. This approach forms a part of my forthcoming book. You can connect with me on Linkedin to know more about the book. I have used this approach in my teaching. It is based on'learning by exception,' i.e. understanding one concept and it's limitations and then understanding how the subsequent concept overcomes that limitation. We thus develop a chain of thought that starts with linear regression and extends to multilayer perceptron (Deep Learning).

Me: "Alexa, tell me what will happen in 2020." Amazon AI: "Here's what I found on Wikipedia: The 2020 UEFA European Football Championship…[continues to read from Wikipedia]" Me: "Alexa, give me a prediction for 2020." Amazon AI: "The universe has not revealed the answer to me." Well, some slight improvement over last year's responses, when Alexa's answer to the first question was "Do you want to open'this day in history'?" As for the universe, it is an open book for the 120 senior executives featured here, all involved with AI, delivering 2020 predictions for a wide range of topics: Autonomous vehicles, deepfakes, small data, voice and natural language processing, human and augmented intelligence, bias and explainability, edge and IoT processing, and many promising applications of artificial intelligence and machine learning technologies and tools. And there will be even more 2020 AI predictions, in a second installment to be posted here later this month. "Vehicle AI is going to be ...

If you want them to do something, you need to give them extremely specific instructions. Imagine learning to kick a football. You could probably learn this by seeing a few examples of how your friends do it. If you want a computer to do this, you would need to tell it exactly how to move every single muscle fiber. Instead of doing this, we just give the computer lots of examples, and tell it to figure it out itself.

When it comes to AI (Artificial Intelligence), VCs (venture capitalists) continue to be aggressive with their fundings. During the third quarter, 965 AI-related companies in the US raised a total of $13.5 billion. In fact, this year should see a record in total fundings (last year's total came to $16.8 billion). Some of the deals have been, well, staggering. Just look at the $1 billion that Microsoft shelled out for an equity stake in OpenAI (the company is one of the few that is pursuing Strong AI). So what has been the result of all this activity? What have been the breakthroughs for AI this year?

The global market intelligence firm predicts that about 51.3 percent of China's GDP will be digitalization-related by 2023 as the country's enterprises step up digitalizing their businesses.

At the last Democratic presidential debate, the technologist candidate Andrew Yang emphatically declared that "we're in the process of potentially losing the AI arms race to China right now." As evidence, he cited Beijing's access to vast amounts of data and its substantial investment in research and development for artificial intelligence. Yang and others--most notably the National Security Commission on Artificial Intelligence, which released its interim report to Congress last month--are right about China's current strengths in developing AI and the serious concerns this should raise in the United States. But framing advances in the field as an "arms race" is both wrong and counterproductive. Instead, while being clear-eyed about China's aggressive pursuit of AI for military use and human rights-abusing technological surveillance, the United States and China must find their way to dialogue and cooperation on AI.