Baidu fires researcher who told subordinates to break rules in image-recognition competition

Chinese search giant Baidu has fired Ren Wu, the lead author of the Deep Image paper documenting the company’s latest image-recognition technology, for breaking the rules in a recent competition, the ImageNet Large Scale Visual Recognition Challenge.

The news comes one week after the organizers of the competition announced that people affiliated with Baidu used at least 200 submissions when just two per week were permitted. Baidu issued an apology and vowed to conduct a review.

[aditude-amp id="flyingcarpet" targeting='{"env":"staging","page_type":"article","post_id":1748160,"post_type":"story","post_chan":"none","tags":null,"ai":false,"category":"none","all_categories":"big-data,business,","session":"B"}']

Today, Baidu revealed the findings of that review.

“We found that a team leader had directed junior engineers to submit more than two submissions per week, a breach of the current ImageNet rules,” the company wrote in a blog post today.

Baidu did not name that team leader. VentureBeat confirmed that the person is Ren Wu, who came to Baidu in 2013 and previously worked at HP. (Hat tip to the New York Times for reporting the detail.)

Wu arrived before Baidu announced the arrival of Andrew Ng, a luminary in deep learning, an increasingly popular type of artificial intelligence. Deep learning — which involves training systems called artificial neural networks on lots of data, like pictures, and then giving them a new piece of data to receive an inference about it in response — lies at the heart of the Deep Image paper and has been used extensively across several Baidu applications.

Now Baidu is taking action to limit the impact of the incident — which makes sense, because Baidu needs to protect its reputation as it strives to recruit engineers alongside other major tech companies.

“We have put in place new company-wide policies to ensure that teams and individuals understand and adhere to the highest standards,” the company wrote in today’s blog post. “The new policies include employee training sessions and the establishment of a scientific advisory panel that will serve as a resource to our worldwide engineering teams moving forward.”