Education
An Ethical Approach to AI is an Absolute Imperative Olbios
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.
DSS 8440: Flexible Machine Learning for Data Centers Direct2DellEMC
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.
How To "Ultralearn" Data Science -- Part 1
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 โ Icarus
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.
NUS Law Launches New Centre for Technology, Robotics, Artificial Intelligence & the Law - dotlah!
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.
120 AI Predictions For 2020
Me: "Alexa, tell me what will happen in 2020." Amazon AI: "Here's what I found on Wikipedia: The 2020 UEFA European Football Championshipโฆ[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 ...
What is Machine Learning? Types of Machine Learning Algorithms
Machine learning is the concept of using the different sample data model to create a mathematical model to understand the specific task. As machine learning deals with business problems the other name for machine learning is predictive analysis. The Supervised machine learning algorithm, unsupervised algorithm, Semi-supervised algorithm, and reinforcement machine learning algorithm are the algorithms of machine learning which are used to make the computers to learn by experience. There are UG courses, PG courses and online courses for cloud computing. Some of the courses are offered with no eligibility criteria whereas some degree programs with cloud computing demand for entrance exams like JEE Main, JEE Advanced, VITEEE, IPU CET, SRMJEEE, and MHT CET. Machine learning and Artificial Intelligence are two different concepts used for training machines and learning data from machines with algorithms. Machine learning is one of the applications and a subset of artificial intelligence. An automated learning system with the experience or patterns of examples initiates the process of automated predictions.
Preparing employees for jobs of the future will require leaders in business, government, and higher education to work together
Preparing employees for jobs of the future will require leaders in business, government, and higher education to work together. That was a major takeaway from a conference at Northeastern's Toronto campus to discuss the results of a Northeastern-Gallup poll on attitudes toward artificial intelligence in the U.S., the U.K and Canada. "We have to do more partnering with universities on that note," Helena Gottschling, the chief human resources officer at the Royal Bank of Canada, told an audience comprised of the three sectors gathered for a conference at Northeastern's Toronto campus this week. She added that employers need to do more to communicate "what we need in our workforce through the universities, so that we're helping to inform the skills and capabilities that the universities are growing through the student populations." The conference follows the publication of a survey conducted by Northeastern and Gallup that revealed an international cross-section of opinions about artificial intelligence as economies around the world undergo the transformative move to automation.