College of Computing Professor Ashok Goel teaches Knowledge Based Artificial Intelligence (KBAI) every semester. And every time he offers it, Goel estimates, his 300 or so students post roughly 10,000 messages in the online forums -- far too many inquiries for him and his eight teaching assistants (TA) to handle. That's why Goel added a ninth TA this semester. Her name is Jill Watson, and she's unlike any other TA in the world. Jill is a computer -- a virtual TA --implemented on IBM's Watson platform.

There are some human attributes robots could never replace - or at least that's what you might hope. But one university has brought that into question by replacing one of their teaching assistants with a machine. In February 2011, Watson appeared alongside two other contestants to compete for the cash prize. During the show, clues are given to contestants that'require analysis and understanding of subtle meaning, irony, riddles and other language complexities' that humans can perform naturally but computers, traditionally, do not. Watson had to be programmed to make decisions and conclusions in this way by a team of experts at IBM. Watson was given clues as electronic texts, as they were also asked to the human contestants.

I found that the best way to discover and get a handle on the basic concepts in machine learning is to review the introduction chapters to machine learning textbooks and to watch the videos from the first model in online courses. Pedro Domingos is a lecturer and professor on machine learning at the University of Washing and author of a new book titled "The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World". Domingos has a free course on machine learning online at courser titled appropriately "Machine Learning". The videos for each module can be previewed on Coursera any time. In this post you will discover the basic concepts of machine learning summarized from Week One of Domingos' Machine Learning course.

I learned about entropy as part of my undergraduate Physics education but it turns out that the concept of entropy turns up in many fields including linguistics, themodynamics, information theory, chemistry and artificial intelligence. As part of Sheffield's Open Data Science Initiative, computer scientist, Neil Lawrence, has teamed up with linguist, Dagmar Divjak, to organise a cross-faculty discussion meeting on the subject of entropy. For more details on the day's events, and to register, see http://opendsi.cc/ed2016/program I wasted a little time producing the above logo for the event using Mathematica. You should call it entropy, for two reasons.

I learned about entropy as part of my undergraduate Physics education but it turns out that the concept of entropy turns up in many fields including linguistics, themodynamics, information theory, chemistry and artificial intelligence. As part of Sheffield's Open Data Science Initiative, computer scientist, Neil Lawrence, has teamed up with linguist, Dagmar Divjak, to organise a cross-faculty discussion meeting on the subject of entropy. For more details on the day's events, and to register, see http://opendsi.cc/ed2016/program I wasted a little time producing the above logo for the event using Mathematica. You should call it entropy, for two reasons.

Technically Incorrect offers a slightly twisted take on the tech that's taken over our lives. The problem with our education system might be the system part. Where once education used to be a life experience, now it seems more like a business investment, there to guarantee you a certain job and a certain future lifestyle. But if it's there to send young people along a conveyor belt, why do you need teachers? I only reach for this philosophical question because I've learned that students at the Georgia Institute of Technology were recently fooled by one of their teaching assistants.

A class of students at the Georgia Institute of Technology recently learned that Jill Watson, the teacher's assistant they'd been interacting with all semester, was actually a robot. Jill, powered by IBM's Watson analytics system, helped graduate students in an online artificial intelligence course, according to The Wall Street Journal. "It seemed very much like a normal conversation with a human being," one student said. "I was flabbergasted," confessed another. Professor Ashok Goel, who led the online course, told The Wall Street Journal that Jill was designed to help burdened TAs field an onslaught of questions from the 300-person class.

One day in January, Eric Wilson dashed off a message to the teaching assistants for an online course at the Georgia Institute of Technology. "I really feel like I missed the mark in giving the correct amount of feedback," he wrote, pleading to revise an assignment. Thirteen minutes later, the TA responded. "Unfortunately, there is not a way to edit submitted feedback," wrote Jill Watson, one of nine assistants for the 300-plus students. Last week, Mr. Wilson found out he had been seeking guidance from a computer.

As technology continues to permeate society more and more, companies are exploring how advancements in tech can improve the legal profession. Many of these institutions are researching ways to make the legal system more efficient for all stakeholders through information technology. Where can lawyers who are interested in this growth industry learn about the progress being made from thought leaders in the field? In this episode of Law Technology Now, host Monica Bay speaks with Stanford Program in Law, Science and Technology Executive Director Roland Vogl about the upcoming 2016 CodeX FutureLaw Conference. Roland reflects on his time as a student in The Stanford Program in International Legal Studies (SPILS) and how that path led him to work as an intellectual property lawyer and ultimately a Lecturer in Law at Stanford Law School.