Your next professor could be a robot. Bina48 became the first robot to co-teach a university class when she helped lead a course at West Point, the U.S. Military academy, according to Axios. The humanoid AI taught two sessions of a philosophy course, with topics ranging from ethics, just war theory and use of artificial intelligence in society, which is pretty meta. Bina48 (pictured) became the first robot to co-teach a university class when she helped lead a course at West Point, the U.S. Military academy. William Barry, who has been using Bina48 to teach for several years, decided to put the robot in front of students in the classroom to see if she could'support a liberal education model.'

Evaluating a machine learning model responsibly requires doing more than just calculating loss metrics. Before putting a model into production, it's critical to audit training data and evaluate predictions for bias. This module looks at different types of human biases that can manifest in training data. It then provides strategies to identify them and evaluate their effects.

Apple will hold its next big event at the end of the month, it has announced. The launch – to be held in New York City on 30 October – is widely expected to see the unveiling of a new iPad Pro and fresh Macs. It comes just a few weeks after Apple launched its new iPhones. And it will come just days after the release of the iPhone XR, a cheaper handset that Apple delayed despite launching alongside the XS in September. Phil Schiller, Apple's senior vice president of worldwide marketing, speaks about the Apple iPhone XS and Apple iPhone XS Max Philip W. Schiller, Senior Vice President, Worldwide Marketing of Apple, speaks about the new Apple iPhone XR Phil Schiller, Apple's senior vice president of worldwide marketing, speaks about the new Apple iPhone XS, iPhone XS Max Philip W. Schiller, Senior Vice President, Worldwide Marketing of Apple, speaks about the new Apple iPhone XR Phil Schiller, Apple's senior vice president of worldwide marketing, speaks about the Apple iPhone XS and Apple iPhone XS Max Philip W. Schiller, Senior Vice President, Worldwide Marketing of Apple, speaks about the new Apple iPhone XR Phil Schiller, Apple's senior vice president of worldwide marketing, speaks about the new Apple iPhone XS, iPhone XS Max Philip W. Schiller, Senior Vice President, Worldwide Marketing of Apple, speaks about the new Apple iPhone XR The company is expected to release a new iPad Pro that will include the Face ID facial recognition technology found in the iPhone X.

In this Book we argue that the fruitful interaction of computer vision and belief calculus is capable of stimulating significant advances in both fields. From a methodological point of view, novel theoretical results concerning the geometric and algebraic properties of belief functions as mathematical objects are illustrated and discussed in Part II, with a focus on both a perspective 'geometric approach' to uncertainty and an algebraic solution to the issue of conflicting evidence. In Part III we show how these theoretical developments arise from important computer vision problems (such as articulated object tracking, data association and object pose estimation) to which, in turn, the evidential formalism is able to provide interesting new solutions. Finally, some initial steps towards a generalization of the notion of total probability to belief functions are taken, in the perspective of endowing the theory of evidence with a complete battery of estimation and inference tools to the benefit of all scientists and practitioners.

I honestly can't understand the multiple 5 star reviews presented on this site about the course. I'm giving it a 1 star which is a bit harsh I know but I'm doing it to offset the number of 5 star reviews here. Honestly I think the course deserves something between 2 and 3 stars depending on your approach to it. Yes Prof. Hinton is a leading expert in the field but the course materials and the way they are presented are pretty bad! I honestly can't understand the multiple 5 star reviews presented on this site about the course.

Home robotics is quite popular because of the accessibility and ease-of-use of micro-controllers like Arduino, and the increasing popularity of IoT devices in smart homes has only expanded the hobby even further. With Arduino, you can light your home, control LCD screens, build robots, and more; this Complete Arduino Starter Kit & Course bundle has guides on how to do this and more for $89.99. If you're new to Arduino and programming in general, it's best to start out with levels one through three of Crazy About Arduino: End-to-End Workshop. These guides introduce the basics of Arduino, such as control statements, sketching, and variables. There are plenty of hands-on projects in levels one through three; these include controlling the speed and brightness of LEDs to make animation waves, programming an ultrasonic distance sensor, and creating a buzzer alarm.

We discuss deep reinforcement learning in an overview style. We draw a big picture, filled with details. We discuss six core elements, six important mechanisms, and twelve applications, focusing on contemporary work, and in historical contexts. We start with background of artificial intelligence, machine learning, deep learning, and reinforcement learning (RL), with resources. Next we discuss RL core elements, including value function, policy, reward, model, exploration vs. exploitation, and representation. Then we discuss important mechanisms for RL, including attention and memory, unsupervised learning, hierarchical RL, multi-agent RL, relational RL, and learning to learn. After that, we discuss RL applications, including games, robotics, natural language processing (NLP), computer vision, finance, business management, healthcare, education, energy, transportation, computer systems, and, science, engineering, and art. Finally we summarize briefly, discuss challenges and opportunities, and close with an epilogue.

Content marketing is one of the hottest areas of digital marketing, but content marketers are overwhelmed by demand. How will content marketers adapt and keep up with never-ending demands on their time and creativity? In this session by Trust Insights co-founder Christopher Penn, learn how AI will impact the future of content marketing. Fill out the short form below to obtain session materials.

If you're at all interested in Artificial Intelligence (AI), it's unlikely to be news to you that there is an AI skills shortage. Businesses are increasingly looking to invest in AI and are on the hunt for suitably skilled workers since traditional software teams without the experience of AI often encounter a number of challenges, as I described in a recent article over on DZone. Anyone thinking about joining the AI workforce will want to learn the subject, initially by doing some reading and research, but without committing to paying too much. As the need to recruit skilled AI staff has grown, so a number of businesses and individuals have set out to provide training courses, books, and e-learning, and the price and quality of these vary, as you would expect. As with all education, if you commit a chunk of your time, you don't want to find it wasted on out-of-date or incorrect information or to find that you are missing out on key skills after spending time and money on a course that promises to equip you appropriately.

Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification, localization and detection. Recent developments in neural network (aka "deep learning") approaches have greatly advanced the performance of these state-of-the-art visual recognition systems. This course is a deep dive into details of the deep learning architectures with a focus on learning end-to-end models for these tasks, particularly image classification. During the 10-week course, students will learn to implement, train and debug their own neural networks and gain a detailed understanding of cutting-edge research in computer vision.