Computers can already hold a massive amount of instantly retrievable data in a manner that puts most humans to shame, but getting them to actually display intelligence is an entirely different challenge. A team of researchers from Northwestern University just made a huge stride toward that goal with a computational model that actually outperforms the average American adult in a standard intelligence test. Don't miss: Apple new 2017 iPad models reportedly have been delayed As PhysOrg reports, the witty computer system utilizes an AI platform called CogSketch that gives it the power to solve visual problems just by looking at them, which is something that has traditionally held back many examples of artificial intelligence. Being able to visually understand, interpret, and then use that data to come to a solution brings the computer system closer to the functioning of the human brain than many before it, and so the team pitted its creation against a popular standardized test called Raven's Progressive Matrices. The Raven's test (or RPM for short) is composed of 60 multiple-choice questions that measure the taker's ability to reason, using visual puzzles.

Computers can already hold a massive amount of instantly-retrievable data in a manner that puts most humans to shame, but getting them to actually display intelligence is an entirely different challenge. A team of researchers from Northwestern University just made a huge stride towards that goal with a computational model that actually outperforms the average American adult in a standard intelligence test. As PhysOrg reports, the witty computer system utilizes an AI platform called CogSketch that gives it the power to solve visual problems just by looking at them, which is something that has traditionally held back many examples of artificial intelligence. Being able to visually understand, interpret, and then use that data to come to a solution brings the computer system closer to the functioning of the human brain than many before it, and so the team pitted its creation against a popular standardized test called Raven's Progressive Matrices. The Raven's test (or RPM for short) is comprised of 60 multiple choice questions that measure the taker's ability to reason, using visual puzzles.

Computers and robots can be biased too and it likely stems from the majority-focused photos used to train them. Researchers at the Massachusetts Institute of Technology are helping to pinpoint why facial recognition software is not accurate across all races -- and the issue likely stems from both recycled code and a Caucasian-dominated computer engineering field. Joichi Ito, MIT's Media Lab director, said during an artificial intelligence panel held this week at the World Economic Forum Annual Meeting that the software's apparent trouble with recognizing diversity is likely because the engineers, and the faces used to train the software, are mostly white. More: Google Photos' 'racist' error highlights facial recognition's limits The issue goes back to the basics of artificial intelligence. Machine learning programs are based on teaching a computer with a set of data.

A new app can give you the answers to your math homework and even explain how to solve it just by taking a picture. Called Socratic, the free app uses artificial intelligence to determine what information you need, and returns'explainers' and videos to give you step-by-step help. The firm says it's like having a'digital tutor in your pocket,' generating answers from a community of teachers and students. A new app can give you the answers to your math homework and even explain how to solve it just by taking a picture. The tutor app can also help with questions in science, history, English, economics.

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How can I become a data scientist? A quick search yields a plethora of possible resources that could help -- MOOCs, blogs, Quora answers to this exact question, books, Master's programs, bootcamps, self-directed curricula, articles, forums and podcasts. Their quality is highly variable; some are excellent resources and programs, some are click-bait laundry lists. Since this is a relatively new role and there's no universal agreement on what a data scientist does, it's difficult for a beginner to know where to start, and it's easy to get overwhelmed. Many of these resources follow a common pattern: 1) Here are the skills you need and 2) Here is where you learn each of these.

The Knoxville R Users Group is presenting a workshop on text analysis using R by Bob Muenchen. The workshop is free and open to the public. A description of the workshop follows. When analyzing text using R, it's hard to know where to begin. There are 37 packages available and there is quite a lot of overlap in what they can do.

Yesterday, during DLD Conference, Demis Hassabis, founder and CEO of DeepMind, discussed AlphaGo beating Go-champion with machine learning, and what the collaboration between humans and machines will be bringing in the future. He highlighted the importance of staying creative and follow our own intuitions when working with AI, forecasting 10 exciting years ahead of us. We also hosted our own panel on "Fixing Education for the A.I. age" where our panelists discussed the shifts in education that will push towards a computational knowledge economy. Conrad Wolfram introduced us to the need to teach students the skills to solve problems with the support of computers, instead of learning how to do specific things (particularly in maths) ourselves. Jurgen Schmidhuber instead observed how we are only thinking of short-term improvements in the education system, while we should be looking decades ahead.

There are some truly fascinating jobs out there. What Do You Do? aims to highlight unique jobs and the interesting men and women behind them. To encourage the next generation to pursue work that inspires them through relatable role models. Can you describe your job? What do you do for a living?

Teacher tested and approved by educators across the United States, Quantum's AI software is proven in research studies to improve comprehension, problem solving skills and test scores by as much as 50%. Quantum's intelligent tutoring engines are integrated with existing web-based learning products, providing a strong competitive edge for distributing partners. A "technology think tank," Quantum is funded and supported by the U.S. Department of Education, the National Science Foundation and the National Institutes of Health.