New Florence. New Renaissance.

Essay-Grading Software

Imagine taking a college exam, and, instead of handing in a blue book and getting a grade from a professor a few weeks later, clicking the “send” button when you are done and receiving a grade back instantly, your essay scored by a software program.

EdX, the nonprofit enterprise founded by Harvard and the Massachusetts Institute of Technology to offer courses on the Internet, has just introduced such a system and will make its automated software available free on the Web to any institution that wants to use it. The software uses artificial intelligence to grade student essays and short written answers, freeing professors for other tasks.

The EdX assessment tool requires human teachers, or graders, to first grade 100 essays or essay questions. The system then uses a variety of machine-learning techniques to train itself to be able to grade any number of essays or answers automatically and almost instantaneously.

The New York Times

The Big Data of Ancient Languages

The (UC Berkeley) research team’s computational model uses probabilistic reasoning – which explores logic and statistics to predict an outcome – to reconstruct more than 600 Proto-Austronesian languages from an existing database of more than 140,000 words, replicating with 85 percent accuracy what linguists had done manually. While manual reconstruction is a meticulous process that can take years, this system can perform a large-scale reconstruction in a matter of days or even hours, researchers said.

Not only will this program speed up the ability of linguists to rebuild the world’s proto-languages on a large scale, boosting our understanding of ancient civilizations based on their vocabularies, but it can also provide clues to  how languages might change years from now.

UC Berkeley News Center

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Kinect+Coke machine+AI+2PM = Japan's Got Talent

"But adding Kinect to a (Coke) vending machine planted in a high traffic area opens up endless possibilities for interaction, assuming that people are interested in whatever is being promoted. Like the dance games (with the band 2 PM) though, the machine must assess the behaviors of the participants to gauge whether they deserve a free Coke. Though the AI involved in the Coke machine may not be that advanced, or even what is used in video games, the potential to make a much more sophisticated system is there."

Singularity Hub

 

Google, Kurzweil and AI frontiers

SingularityHub

“It’s not surprising Google is interested in Kurzweil’s services. A few years back, Google cofounder Larry Page told Esquire, “We have some people at Google who are trying to build artificial intelligence, and to do it at a large scale…I don’t think it’s that far off.” In his latest book, How to Create a Mind, Kurzweil says humans can reverse engineer the brain to create artificial intelligence—and similarly says we’ll do it much sooner than anyone thinks. A good match, no?

Kurzweil specializes in machine learning and language processing and will focus on new projects at Google involving both. Some of those skills may help further hone Google’s learning search algorithm, language translation application, and speech recognition software.

But Google has plenty of talent already well versed in those technologies and the firm is known to invest in more ambitious undertakings. The special projects team, Google X, is working on self-driving cars, augmented-reality glasses, and a slew of projects outside the public’s purview. Kurzweil says he will work on AI, and one imagines that may include an attempt to reverse engineer the brain.”

How do you know when a politician is lying?

The old wisecrack goes “when he is moving his lips” :)

But Purdue Professor Chris Kowal shows off facial recognition software which analyzes emotions and moves the science forward on reading politicians and others.

BTW – VP Biden was so expressive in yesterday’s debate you didn’t need software to tell his emotions!

Algorithms and equations that run our lives

From a BusinessWeek review of Christopher Steiner’s new book “Automate This”

Math majors may enjoy even more a previous post Seven Equations that Rule our World

Click to enlarge.

Rio Tonto’s “Mine of the Future”

The movie Avatar on earth?

Rio Tonto is investing hundreds of million on mining robots, 3D visualization among other innovations described in video below

Google and Microsoft Talk Artificial Intelligence

Peter Norvig, Google's head of research, and Eric Horvitz, a distinguished scientist at Microsoft Research talk AI with MIT Technology Review

Horvitz: You don't need it to be completely labeled. An area known as semi-supervised learning is showing us that even if 1 percent or less of the data is tagged, you can use that to understand the rest.

But a lack of labels is a challenge. One solution is to actually pay people a small amount to help out a system with data it can't understand, by doing microtasks like labeling images or other small things. I think using human computation to augment AI is a really rich area.

Norvig: You don't have to tell a learning system everything. There's a type of learning called reinforcement learning where you just give a reward or punishment at the end of a task. For example, you lost a game of checkers and aren't told where you went wrong and have to learn what to do to get the reward next time.

Google: Big Data, Simple Algorithms

New Scientist (subscription required for full text) has a really interesting interview with Google’s Director of Research, Peter Norvig

“His big idea is that if you can amass sufficient data, a few relatively simple statistical algorithms are enough to solve some of the most vexing problems in machine learning, such as automated language translation.”

“Google's translation tools are the most mature product of this approach. "In the past, people had thought of this as being a linguistics problem," says Norvig, which meant designing software that could replicate a human translator's understanding of the languages involved, including their grammatical rules.

Instead, Norvig's team has compiled texts that have already been translated, and applies statistical techniques to train the system to learn translations of unfamiliar words and how they are used in context. "Essentially we are just building this big model of probabilities," Norvig says.”

“Speech recognition is a tougher nut to crack. Because of the almost infinite variety in accent, timbre and other characteristics of human speech, the conventional approach has been to train systems to learn individual users' vocal tics. That's fine if you want a personal dictation machine, but useless for allowing computers to interpret anything that's said to them, by anyone.

Norvig is convinced that speech recognition will fall to the "big data, simple algorithms" approach. The problem is finding enough data, as the spoken word is not represented online as comprehensively as text and images. As we discuss this issue, Norvig makes a revealing admission about the launch of Google Voice, which among other things transcribes phone messages and sends them to your email inbox: "One of the reasons we had this phone service is that we wanted to capture lots of interactions; hear different accents and different voices saying different things."”

What is “Jeopardy”?

“But chess is a game of limits, with pieces that have clearly defined powers. “Jeopardy!” requires a program with the suppleness to weigh an almost infinite range of relationships and to make subtle comparisons and interpretations. The software must interact with humans on their own terms, and fast.

Indeed, the creators of the system — which the company refers to as Watson, after the I.B.M. founder, Thomas J. Watson Sr. — said they were not yet confident their system would be able to compete successfully on the show, on which human champions typically provide correct responses 85 percent of the time. “

New York Times