If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
These days, pundits galore are proselytizing about the Future of Work. Depending on who you ask, the robots may or may not be taking over, leaving us mere humans pondering how work fits into our lives and whether we're going to be eventually rendered obsolete. Just look at the stark contrast in tone between these two headlines: the Wall Street Journal's White-Collar Robots Are Coming For Jobs versus Wired's Chill: Robots Won't Take All Our Jobs. Who should we *really* believe?! The truth is there isn't one easy answer.
Autonomous vehicle development is a time and resource-intensive business, requiring dozens of test vehicles, thousands of hours of data collection and millions of miles of driving to hone the artificial brains of the cars of tomorrow. What if you could do most of that in the cloud? That's the question Nvidia hopes to answer with the release of its Nvidia Drive Constellation testing platform for self-driving cars. The announcement came during the keynote address at Nvidia's 2019 GPU Technology Conference in San Jose Monday. Drive Constellation is, basically, a simulation and validation platform that allows automakers and developers to test their autonomous vehicles and technologies in a virtual environment that lives in a specially-designed cloud server.
Access to skilled workers is already a key factor that sets successful companies apart from failing ones. In an increasingly data-driven future - the European Commission believes there could be as many as 756,000 unfilled jobs in the European ICT sector by 2020 - this difference will become even more acute. Skills gaps across all industries are poised to grow in the Fourth Industrial Revolution. Rapid advances in artificial intelligence (AI), robotics and other emerging technologies are happening in ever shorter cycles, changing the very nature of the jobs that need to be done - and the skills needed to do them - faster than ever before. At least 133 million new roles generated as a result of the new division of labour between humans, machines and algorithms may emerge globally by 2022, according to the World Economic Forum.
On Feb 27, 2019 at the "New Era, New Education, and Creating the Future" conference in Shanghai organized by the iTutorGroup, announced that Sophia the Robot is their new ambassador and future AI tutor. A new strategic partnership with Hanson Robotics was also announced at the same time. At the "New Era, New Education, and Creating the Future" conference, CEO Dr. Eric Yang delivered these key messages: Conference attendees included a group of teachers and students from a primary school that iTutorGroup donated RMB 500,000. Toby, one of the iTutorGroup's students and recent speech contest winner, appeared on stage and had a fun chat with Sophia. Founded in 1998, and led by Dr. Eric Yang, Founder, Chairman, and CEO, the iTutorGroup offers a range of e-learning solutions for adults and K-12 including TutorABC, vipJr, vipABC, TutorJr and TutorMing.
The course "Machine Learning Basics: Building a Regression model in R" teaches you all the steps of creating a Linear Regression model, which is the most popular Machine Learning model, to solve business problems. Machine Learning is a field of computer science which gives the computer the ability to learn without being explicitly programmed. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. What is the Linear regression technique of Machine learning? Linear Regression is a simple machine learning model for regression problems, i.e., when the target variable is a real value.
One of the main challenges of advancing task-oriented learning such as visual task planning and reinforcement learning is the lack of realistic and standardized environments for training and testing AI agents. Previously, researchers often relied on ad-hoc lab environments. There have been recent advances in virtual systems built with 3D physics engines and photo-realistic rendering for indoor and outdoor environments, but the embodied agents in those systems can only conduct simple interactions with the world (e.g., walking around, moving objects, etc.). Most of the existing systems also do not allow human participation in their simulated environments. In this work, we design and implement a virtual reality (VR) system, VRKitchen, with integrated functions which i) enable embodied agents powered by modern AI methods (e.g., planning, reinforcement learning, etc.) to perform complex tasks involving a wide range of fine-grained object manipulations in a realistic environment, and ii) allow human teachers to perform demonstrations to train agents (i.e., learning from demonstration). We also provide standardized evaluation benchmarks and data collection tools to facilitate a broad use in research on task-oriented learning and beyond.
With strong roots in statistics, Machine Learning is becoming one of the most interesting and fast-paced computer science fields to work in. There's an endless supply of industries and applications machine learning can be applied to to make them more efficient and intelligent. Chat bots, spam filtering, ad serving, search engines, and fraud detection, are among just a few examples of how machine learning models underpin everyday life. Machine learning is what lets us find patterns and create mathematical models for things that would sometimes be impossible for humans to do. Unlike data science courses, which contain topics like exploratory data analysis, statistics, communication, and visualization techniques, machine learning courses focus on teaching only the machine learning algorithms, how they work mathematically, and how to utilize them in a programming language.
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You may have heard the old parable about a group of blind men and an elephant. The men heard that a strange animal had been brought to town, and they wanted to touch it so they could understand what it was. The first man, whose hand landed on the trunk, decided that the elephant was like a thick snake. The second, whose hand reached the elephant's ear, thought it seemed like a kind of fan. The third man felt the leg and said the animal was like a tree.