"I think that the most unicorn company in the next decade will definitely be an artificial intelligence company.
Li Kaifu, Chairman and CEO of Innovation Works, said at the "WISE•2016 Unicorn Congress" on December 6th: "In the next decade, 50% of the world's work will be replaced by artificial intelligence. In particular, some of the things listed here: assistants, translators, security guards, these jobs are really replaced. â€
Li Fukai said that he had done artificial intelligence more than 30 years ago, but it is a pity that entrepreneurship must be born at the right time, so I do a lot of work, no matter in the game, speech recognition, natural language understanding, unfortunately Nothing is happening at the right time.
Li Fukai said that deep learning, simple understanding, is to give very very large neurons, with a lot of data to fill in training. It can be in a certain field, in terms of identification, classification, or prediction, far more than any past algorithm.
Li Fukai believes that in all areas, we believe that the biggest area should be unmanned. Although this may be a goal for a decade, when the three things happen simultaneously with electric vehicles, sharing economy, and driverlessness, the human economy will produce the biggest and biggest improvement and change.
Attached to Li Kaifu's speech
Today, it seems that Chengcheng’s arrangement is a relay race. From 40 to 50, I will be the next speaker after the 60s. Since today is the Unicorn Forum, I would like to talk about my views on the future unicorn.
I think that the most unicorn company in the next decade will definitely be an artificial intelligence company. In addition, I believe that every unicorn here, or a company that wants to be a unicorn, must understand artificial intelligence in the development of your company.
This is the same as the Internet 20 years ago and the mobile Internet 10 years ago. It is an advantage as a prophet. Today I want to talk about it: artificial intelligence.
I believe that in the next decade, 50% of the world's work will be replaced by artificial intelligence. In particular, some of the things listed here: assistants, translators, security guards, these jobs are really replaced. You think, today's face recognition, in some scenes, has been able to identify faces more accurately than people 20 times. So, do security still need to recognize the face again? Frontier defense, the front desk, these jobs can be replaced by machines. This is just an example. Of course, we see why AlphaGO is so powerful? Because it has played a lot of chess with itself.
Why is face recognition so powerful? Because they read hundreds of millions of faces and then learn from them. Machine learning, in any narrow field, seeing a lot of data, the human brain can't compete with it at all.
Therefore, this is not a problem of replacing humans with machines. It is a problem in which humans only need 5 seconds to think. There are a lot of data problems. In a problem with narrow fields, people will never be opponents of machines. Moreover, one area, one will be surpassed by the machine, not just replaced.
Look at past developments, from AlphaGO's chess, to perception, cognition, to decision making, and even to feedback (that is, letting the machine itself have hands or feet or wheels, you can move), these four things in the past five years There is a very, very big improvement.
There are many examples here, because time is not much to say today. We can see that the game has AlphaGO, and there is Microsoft Xiaobing. There is an example here. Google has a technology that can automatically help you to reply to Gmail (but there may not be much Gmail in the room, so I don’t have the opportunity.) Use this feature). Cars, from the recent Tesla, and GoogleCar, are all very, very fast. Because, in the past five years, there have been many technological breakthroughs.
In fact, I have been doing artificial intelligence more than 30 years ago, but it is a pity that entrepreneurship must be born at the right time, so I do a lot of work, no matter in the game, speech recognition, natural language understanding, unfortunately Nothing is happening at the right time. Because the machine was not fast enough at the time, the data was not enough, and the algorithm was not advanced enough. However, today is advanced enough.
Therefore, I would like to introduce that the most important breakthrough in machine learning is deep learning.
Deep learning, a simple understanding, is to give very very large neurons, with a lot of data to fill in training. It can be in a certain field, in terms of identification, classification, or prediction, far more than any past algorithm. This is the result of the past five years.
This learning algorithm is especially suitable for a particularly large amount of data. So, when you have a large amount of data, you can make things that you couldn't do before.
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