By Robert McMillan 

Baidu Inc. recently crowed about besting rivals such as Google Inc. and Microsoft Corp. in a closely watched standard test of artificial intelligence. On Tuesday, the Chinese technology giant apologized for misleading the public about its accomplishment.

Baidu's gaffe is a sign of the increasingly high stakes as the world's top tech companies race to develop technologies that allow computers to recognize photographs, control robots, understand spoken language and perform other tasks that until recently required human attention. Big Internet companies, which have committed massive computing resources to AI, are under pressure to assert leadership in the field, both for prestige and the potential commercial payoff.

In addition to Baidu, Google, and Microsoft, tech powerhouses including Apple Inc., Facebook Inc. and International Business Machines Corp. have been heavily recruiting AI researchers and vying for bragging rights.

In mid-May, Baidu said it scored a record low 4.58% error rate on the ImageNet test of image recognition. Microsoft's software had a 4.94% error rate, and Google achieved 4.8% in their latest tests. With practice, humans can achieve an error rate of about 5%.

On Tuesday, however, the volunteer computer scientists who administer the test reported that Baidu had stacked the deck by taking the test far more frequently than allowed. ImageNet allows contestants to submit two sets of test results a week. Baidu made more than 40 submissions over a five-day period in March, ImageNet organizers said in a blog post Tuesday. They said the company set up 30 accounts to submit about 200 test results over a six-month period.

The ImageNet test is based on a database of about one million photographs sorted into about 1,000 categories. Researchers typically use one portion of the database to tune their image-recognition software and another to test it. By taking the test so many times, Baidu's engineers could have gained an advantage by tuning their software to information that was supposed to be unfamiliar.

"This is pretty bad, and it is exactly why there is a held-out test set for the competition that is hosted on a separate server with limited access," said Matthew Zeiler, chief executive of AI company Clarifai Inc. and a past winner of the ImageNet competition. "If you know the test set, then you can tweak your parameters of your model however you want to optimize the test set."

The organizers have asked Baidu to stop submitting ImageNet results for the next year.

Baidu declined to answer questions about the incident, but in a statement posted on the ImageNet website, Baidu scientist Ren Wu apologized for what he called a mistake. "We have added a note to our research paper...and will continue to provide relevant updates as we learn more," he wrote. The statement offered no further explanation.

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