[link] Baidu cheats in an AI contest in order to gain a 0.24% advantage

Wei Dai

Some of you may already have seen this story, since it's several days old, but MIT Technology Review seems to have the best explanation of what happened: Why and How Baidu Cheated an Artificial Intelligence Test

Such is the success of deep learning on this particular test that even a small advantage could make a difference. Baidu had reported it achieved an error rate of only 4.58 percent, beating the previous best of 4.82 percent, reported by Google in March. In fact, some experts have noted that the small margins of victory in the race to get better on this particular test make it increasingly meaningless. That Baidu and others continue to trumpet their results all the same - and may even be willing to break the rules - suggest that being the best at machine learning matters to them very much indeed.

(In case you didn't know, Baidu is the largest search engine in China, with a market cap of $72B, compared to Google's $370B.)

The problem I see here is that the mainstream AI / machine learning community measures progress mainly by this kind of contest. Researchers are incentivized to use whatever method they can find or invent to gain a few tenths of a percent in some contest, which allows them to claim progress at an AI task and publish a paper. Even as the AI safety / control / Friendliness field gets more attention and funding, it seems easy to foresee a future where mainstream AI researchers continue to ignore such work because it does not contribute to the tenths of a percent that they are seeking but instead can only hinder their efforts. What can be done to change this?

Such is the success of deep learning on this particular test that even a small advantage could make a difference. Baidu had reported it achieved an error rate of only 4.58 percent, beating the previous best of 4.82 percent, reported by Google in March. In fact, some experts have noted that the small margins of victory in the race to get better on this particular test make it increasingly meaningless. That Baidu and others continue to trumpet their results all the same - and may even be willing to break the rules - suggest that being the best at machine learning matters to them very much indeed.

(In case you didn't know, Baidu is the largest search engine in China, with a market cap of $72B, compared to Google's $370B.)

Take a look at this image.

Is 'pure AI startups' the relevant category here?

Stuart Russell said recently "The commercial investment in AI the last five years has exceeded the entire world wide government investment in AI research since it's beginnings in the 1950's."

That would be astonishing if true, but I have to be doubtful. Does Russell provide sources for this? The last 5 years is not much time to outspend the cumulative total of MIT AI Lab, the Fifth Generation Project, a fair number of DARPA's projects, the AI Winter, and all AI groups for half a century.

It's not pure AI startups. But pure AI startups are a subset of them and have probably grown along the same trend.

That would be astonishing if true, but I have to be doubtful.

All the big tech companies have created big machine learning teams and hired tons of researchers. Google, Facebook, Baidu, IBM, and I think Apple. And beyond that there are a ton of smaller companies and startups.

Peter Norvig commented that "his company [Google] already employed 'less than 50 percent but certainly more than 5 percent' of the world’s leading experts in machine learning".

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[link] Baidu cheats in an AI contest in order to gain a 0.24% advantage

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[link] Baidu cheats in an AI contest in order to gain a 0.24% advantage

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