Omron's table tennis robot is getting smarter Forpheus, the mighty table tennis robot developed by Japan's Omron, is getting smarter. An updated version on show at the Ceatec electronics show this week has artificial intelligence to become a tougher opponent. In the new version, the robot attempts to rank a player according to their perceived skill as a beginner, intermediate player or advanced. It does this by looking at the speed of the served ball, its trajectory, rotation and the body motion of the player with cameras, and does so with 90 percent accuracy, according to Omron. The machine uses that information to customize its return ball, softer and easy for beginners, faster and more unpredictable for advanced players. The use of artificial intelligence has also improved the robot's game.

Like many of the students around them, robots at Carnegie Mellon University are constantly learning -- learning how to think, how to move, and how to be more like humans. "It's sort of this wonderland of innovation," says 60 Minutes producer Nichole Marks in the video above. "Everywhere you go, every corner of the campus, there are robots -- robots in the hallways, robots picking things up, robots talking to you." Marks and correspondent Charlie Rose visited the Carnegie Mellon campus in Pittsburgh while reporting their two-part story on artificial intelligence, or A.I., for this week's episode of 60 Minutes. What they found in the old steel town was a glimpse into the future, says Rose.

The following script is from "Artificial Intelligence," which aired on Oct. 9, 2016. Charlie Rose is the correspondent. The search to improve and eventually perfect artificial intelligence is driving the research labs of some of the most advanced and best-known American corporations. They are investing billions of dollars and many of their best scientific minds in pursuit of that goal. All that money and manpower has begun to pay off. In the past few years, artificial intelligence -- or A.I. -- has taken a big leap -- making important strides in areas like medicine and military technology. What was once in the realm of science fiction has become day-to-day reality. You'll find A.I. routinely in your smart phone, in your car, in your household appliances and it is on the verge of changing everything. On 60 Minutes Overtime, Charlie Rose explores the labs at Carnegie Mellon on the cutting edge of A.I. See robots learning to go where humans can'... It was, for decades, primitive technology.

Tom Fawcett is Principal Data Scientist at Silicon Valley Data Science. Co-author of the popular book Data Science for Business, Tom has over 20 years of experience applying machine learning and data mining in practical applications. He is a veteran of companies such as Verizon and HP Labs, and an editor of the Machine Learning Journal. A basic mantra in statistics and data science is correlation is not causation, meaning that just because two things appear to be related to each other doesn't mean that one causes the other. This is a lesson worth learning.

TensorFlow is a framework created by Google for creating Deep Learning models. Deep Learning is a category of machine learning models that use multi-layer neural networks. The idea of deep learning has been around since 1943 when neurophysiologist Warren McCulloch and mathematician Walter Pitts wrote a paper on how neurons might work and they modeled a simple neural network using electrical circuits. Many, many developments have occurred since then. These highly accurate mathematical models are extremely computationally expensive.

It is possible to introduce neural networks without appealing to brain analogies. In the section on linear classification we computed scores for different visual categories given the image using the formula \( s W x \), where \(W\) was a matrix and \(x\) was an input column vector containing all pixel data of the image. In the case of CIFAR-10, \(x\) is a [3072x1] column vector, and \(W\) is a [10x3072] matrix, so that the output scores is a vector of 10 class scores. An example neural network would instead compute \( s W_2 \max(0, W_1 x) \). Here, \(W_1\) could be, for example, a [100x3072] matrix transforming the image into a 100-dimensional intermediate vector. The function \(max(0,-) \) is a non-linearity that is applied elementwise.

The challenge The display algorithms team manages the machine-learning and optimization internals of Adobe's suite of online advertising products. We're looking for a Python Engineer who will be building the next generation of data driven products. You will be hands-on, which means you will be writing code in Python to implement various machine learning tools and setting an example for the team in terms of your ability to produce production-quality software. Ideal candidates will have a strong academic background as well as technical skills including applied statistics, machine learning, data mining, and software development. Familiarity working with large-scale data-sets and big data techniques would be a plus.

Education technology has a public relations problem. In a space where words carry wide currency, our choice of language matters. That's why I'm troubled by Artificial Intelligence (AI). At a time when educators need assurances that digital innovations will work for them, the fundamental premise of this technology may imply just the opposite. The term evokes the awkward connotation of machines displacing human capabilities.

This overview article is devoted to the study of a trend which is growing rapidly in popularity in the IT industry - chatbots, and the role of Microsoft in their development process. The article will cover the history of chatbots, peculiar properties of bots, the main, and also some unexpected spheres of their application, perspectives and technology limits. We have deliberately chosen Microsoft as the main platform for comparative research. The company does a lot of work in the field of promotion and development of intelligent bots. One of the main steps in this direction is a framework for creation of custom bots Microsoft Bot Framework platform - independent and open source; Microsoft presented it at the Build 2016 exhibition. Generally, a chatbot is a program that can imitate a meaningful dialogue with the user via text or speech in the language known to the user. The goal of such a dialogue, is often to answer the user requests and execute bot commands. Not being something substantially new, chatbots however, are positioned in the marketplace as a sort of know-how activity.

I teach a 5-step process that you can use to get your start in applied machine learning. The traditional way to teach machine learning is bottom-up. Start with the theory and math, then algorithm implementations, then send you off to figure out how to start solving real-world problems. The traditional approach to getting started in machine learning has a gap on the path to practitioner. The Machine Learning Mastery approach flips this and starts with the outcome that is most valuable.