Using the ImageNet object classification benchmark, Baidu’s Minwa supercomputer scanned more than 1 million images and taught itself to sort them into about 1000 categories and achieved an image identification error rate of just 4.58 percent, beating humans, Microsoft and Google. Baidu's Minwa scored 95.42%, Google's system scored a 95.2%, and Microsoft's, a 95.06%, Baidu said.
“Our company is now leading the race in computer intelligence,” said Ren Wu, a Baidu scientist working on the project. “I think this is the fastest supercomputer dedicated to deep learning,” he said. “We have great power in our hands—much greater than our competitors.
A paper released Monday [May 11, 2015] is intended to provide a taste of what Minwa’s extra oomph can do. It describes how the supercomputer was used to train a neural network that set a new record on a standard benchmark for image-recognition software. The ImageNet Classification Challenge, as it is called, involves training software on a collection of 1.5 million labeled images in 1,000 different categories, and then asking that software to use what it learned to label 100,000 images it has not seen before.
(Score: 2, Insightful) by Anonymous Coward on Sunday May 17 2015, @12:01AM
When it comes to just about anything each percentage of perfection is more expensive than the last. Take purified water. You can never really get completely pure water but 99.9 percent pure is (making up numbers) maybe half as expensive as 99.99 percent pure. 99.999 percent pure is probably four times as expensive as 99.99 percent pure. The cost rises exponentially with each degree of perfection.
(Score: -1, Troll) by Anonymous Coward on Sunday May 17 2015, @12:15AM
This inability to completely purify water is why homeopathy works. The homeopathic element keeps its imprint on the treated water.
(Score: 1) by JNCF on Sunday May 17 2015, @02:41PM
Troll, troll, troll your boat, gently down the stream...