From a game of chess to assessing MRIs, AI has been learning to match, sometimes even beat, human experts.
However, if a new report is anything to go by, machines still have a lot to learn to solve a 16-year-old level Math problem.
Google's DeepMind recently tested its algorithms on a high school Math test but found they couldn't even translate the problems.
In a bid to analyze the capability of its AI in the domain of Mathematics, DeepMind trained a neural network on the Math curriculum of a 16-year-old UK student.
They synthesized the data and trained the machine on Algebra, Arithmetic, Calculus, Comparisons, Measurement, Numbers, Manipulating Polynomials, and Probability.
However, disappointingly, the models they tried flunked the test.
DeepMind threw 40 questions at different algorithms but they could only solve some 35% of them.
Yes, one model did slightly better than others, but on most occasions, they failed to translate the questions, complete with words, symbols, numbers, and functions, into actual operations for getting the results.
And, as we know, 14 out of 40 is a failure anywhere in the world.
As Mathematics requires a number of cognitive skills we humans have and can use automatically, machines need to be enhanced for the job.
They'd not just have to be trained to make sense of a problem, with all the numbers, variables, arithmetic operators, and words, but also to plan an operation and apply the knowledge of rules, transformations, and processes to get the result.
While the Math test was a bummer, DeepMind's AI has done pretty well in the past.
Among other things, DeepMind algorithms can even beat doctors at detecting diseases and create their own images from random data.
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