Nuria Oliver is a computer scientist and is also a Fellow of the European Association of Artificial Intelligence and ACM Fellow. She has over 20 years of research experience in the areas of human behaviour modelling and prediction from data and human-computer interaction. Her passion is to improve people's quality of life, both individually and collectively, through technology. Oliver speaks to SciTech Europa Quarterly about the importance of preparing future generations for what's next to come in the world of technology. I think one of the biggest challenges is the profound transformation that will be needed in the educational system and the massive investment in teacher education that would entail.

Greg LaBlanc has been teaching at the Haas School of Business and Berkeley Law since 2005. He teaches primarily in the areas of finance and strategy in the MBA and MFE programs and in Executive Education. He has also worked in competitive intelligence and litigation consulting and has advised consulting teams in finance, marketing, and strategy. His research interests lie at the intersection of law, finance, and psychology, in the area of business strategy and risk management. He is the recipient of teaching awards including the Earl F. Cheit Award for Outstanding Teaching, 2009; and the Haas EWMBA Graduate Instructor of the year, 2004-2005.

Artificial Intelligence (AI), defined as a system's ability to correctly interpret external data, to learn from such data, and to use what it learns to achieve specific goals and tasks through flexible adaptation, will doubtlessly lead to a multitude of changes in today's world. Given the significant uncertainties around artificial intelligence, it is not astonishing that the opinions on it reach from highly euphoric like the vision of best-selling author Raymond Kurzweil to straight out alarmist as frequently expressed by tech entrepreneur and investor Elon Musk. Theoretical physicist Stephen Hawking called AI "either the best, or the worst thing, ever happen to humanity". For at least three reasons, ethics as well as a human approach to AI and its progress are an absolute imperative. First, an AI system will do whatever assignment it has been asked to do, independent of whether these tasks are illegal, unethical, or simply produce negative outcomes.

This program will prepare you for one of the world's most exciting technology frontiers.

This program will prepare you for one of the world's most exciting technology frontiers.

This introduces a new high-performance, high capacity, reduced cost inference choice for data centers and machine learning service providers. It is the purpose-designed, open PCIe architecture of the DSS 8440 that enables us to readily expand accelerator options for our customers as the market demands. This latest addition to our powerhouse machine learning server is further proof of Dell EMC's commitment to supporting our customers as they compete in the rapidly emerging AI arena. The DSS 8440 is a 4U 2-socket accelerator-optimized server designed to deliver exceptionally high compute performance for both training and inference. Its open architecture, based on a high performance switched PCIe fabric, maximizes customer choice for machine learning infrastructure while also delivering best-of-breed technology.

Concepts in data science would be training and education which are prerequisites for data science. These include a solid foundation in mathematics (statistics, probability, linear algebra, and calculus), programming, machine learning, and AI, and business analysis. Facts in data science will then be the textbook stuff involved in data science, such as the facts in mathematics and machine learning that you have to deeply understand to the point where you can teach it to other people. Facts involved should not be memorized as formal education has brainwashed us to do but should be comprehended at the atomic level, where you can translate jargon into an easier language for the masses to understand. Procedures involved are the fundamentals in data science -- business understanding, data acquisition, and preparing (mining and cleaning), deployment, modeling, and visualization.

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.

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 ...