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What is artificial intelligence
What is artificial intelligence
Now, artificial intelligence has been very hot, it seems that people in science and technology, whether or not, have to talk about a few artificial intelligence in their mouth to show how much time they are.
The definition of AI is to let machine realize the task that only human can finish. The core is AI algorithm.
For example, the following figure is the schematic diagram of artificial intelligence that enables machine to simulate human abilities.
What is artificial intelligence? At last, it's white.
On the one hand, AI is indeed the future direction. On the other hand, AI is probably the next black swan in science and technology circles. I'm not sure when a unicorn will be born.
What is artificial intelligence? At last, it's white.
But before that, we must recognize correctly what is AI.
Pseudo artificial intelligence
Most AI nowadays belong to pseudo artificial intelligence. Why can I say this? It can be explained from the following two aspects.
First, AI can not be done at any time, it will take time and accumulation of experiments.
And those who make artificial intelligence are the same, they need to get into real artificial intelligence, but there are only a few hundred in the world.
But it seems that in the instant, there are tens of thousands of artificial intelligence talents selected in China. Can it be conceivable that such a person is a real artificial intelligence expert?
These talents are often crowned by big companies with annual salary of 300 thousand or 500 thousand, though there are many excellent talents, but this is rather too urgent. From the perspective of talent cultivation, there are still lots of bubbles in the field of AI.
What is artificial intelligence? At last, it's white.
Second, many projects are simply changed into waistcoat.
Many start-up companies like to label their projects, which can not only attract eyeballs, but also get investors' favor.
Though it can not be said that such a practice is wrong, it is obviously not real AI, or even misleading other people's cognition of AI.
For example, many projects are very simple before labeling artificial intelligence, just like robots, or algorithmic research, all of which are now artificial intelligence.
What is real artificial intelligence?
We are neither experts nor scholars specializing in this field. Are there any simple ways to directly identify artificial intelligence, and what is pseudo artificial intelligence?
The answer is.
For a simple example, people tried to teach computers to play chess before. After learning, computers still win the battle with people. When they finally win the battle, they have already passed for 10 years.
And Google's AlphaGo will never go to the invincible presence in go, just in a year.
From this, we can see that the real AI is reflected in its excellent learning ability.
What is artificial intelligence? At last, it's white.
If you take a period of about 3 months to see an algorithmic progress, such as facial recognition, such as speech recognition, if the algorithm advances only in an algebraic level and does not reach an exponential level, the algorithm may be more machine learning, and it has not yet reached the level of artificial intelligence.
Now that we have identified what is AI, what is the most important for AI?
Maybe some people will say algorithm, some people will talk about equipment, some people will say programming technology. Though they constitute an important part of AI, they are not the most important ones.
For real AI, the most important is always big data. Only with complete data, AI can really develop. It's like a treasure knife. It needs a good sharpening stone to make it sharper, and big data is just the best grindstone.
Like Google AlphaGo, why do some people say that AlphaGo not to play chess, but only in the field of chess roost.
AlphaGo experts say they do not want to do this, but they cannot do so. Because in weiqi, the Japanese have always had the habit of preserving the chess spectrum. On each score, what is the first hand, and what is the 100th hand, is easily learned by the AlphaGo.
But for chess, most of them are endgame since ancient times. Although the situation is very wonderful, but for AlphaGo, it does not know the cause of the formation of the residual situation, no knowledge of the previous steps, which will cause obstacles to its cognition.
It also shows how important the complete data is for AI. Anyone who throws data on AI is all a hooligan.
Unicorns in artificial intelligence
At present, most of China's data are controlled by BAT, and abroad are Facebook, Google, Amazon and so on. For entrepreneurs, breaking the monopoly of data has considerable challenges, but it is not without opportunities.
For example, medical data, BAT has not yet formed monopoly. Financial data are more in the hands of financial companies than those of Internet companies.
In these two areas, regardless of your technical level, at least on the same line of data, it is a rare opportunity for an entrepreneur or a post - entering company. Meanwhile, the next giant is also likely to be born in these two areas.
What is artificial intelligence? At last, it's white.
The definition of AI is to let machine realize the task that only human can finish. The core is AI algorithm.
For example, the following figure is the schematic diagram of artificial intelligence that enables machine to simulate human abilities.
What is artificial intelligence? At last, it's white.
On the one hand, AI is indeed the future direction. On the other hand, AI is probably the next black swan in science and technology circles. I'm not sure when a unicorn will be born.
What is artificial intelligence? At last, it's white.
But before that, we must recognize correctly what is AI.
Pseudo artificial intelligence
Most AI nowadays belong to pseudo artificial intelligence. Why can I say this? It can be explained from the following two aspects.
First, AI can not be done at any time, it will take time and accumulation of experiments.
And those who make artificial intelligence are the same, they need to get into real artificial intelligence, but there are only a few hundred in the world.
But it seems that in the instant, there are tens of thousands of artificial intelligence talents selected in China. Can it be conceivable that such a person is a real artificial intelligence expert?
These talents are often crowned by big companies with annual salary of 300 thousand or 500 thousand, though there are many excellent talents, but this is rather too urgent. From the perspective of talent cultivation, there are still lots of bubbles in the field of AI.
What is artificial intelligence? At last, it's white.
Second, many projects are simply changed into waistcoat.
Many start-up companies like to label their projects, which can not only attract eyeballs, but also get investors' favor.
Though it can not be said that such a practice is wrong, it is obviously not real AI, or even misleading other people's cognition of AI.
For example, many projects are very simple before labeling artificial intelligence, just like robots, or algorithmic research, all of which are now artificial intelligence.
What is real artificial intelligence?
We are neither experts nor scholars specializing in this field. Are there any simple ways to directly identify artificial intelligence, and what is pseudo artificial intelligence?
The answer is.
For a simple example, people tried to teach computers to play chess before. After learning, computers still win the battle with people. When they finally win the battle, they have already passed for 10 years.
And Google's AlphaGo will never go to the invincible presence in go, just in a year.
From this, we can see that the real AI is reflected in its excellent learning ability.
What is artificial intelligence? At last, it's white.
If you take a period of about 3 months to see an algorithmic progress, such as facial recognition, such as speech recognition, if the algorithm advances only in an algebraic level and does not reach an exponential level, the algorithm may be more machine learning, and it has not yet reached the level of artificial intelligence.
Now that we have identified what is AI, what is the most important for AI?
Maybe some people will say algorithm, some people will talk about equipment, some people will say programming technology. Though they constitute an important part of AI, they are not the most important ones.
For real AI, the most important is always big data. Only with complete data, AI can really develop. It's like a treasure knife. It needs a good sharpening stone to make it sharper, and big data is just the best grindstone.
Like Google AlphaGo, why do some people say that AlphaGo not to play chess, but only in the field of chess roost.
AlphaGo experts say they do not want to do this, but they cannot do so. Because in weiqi, the Japanese have always had the habit of preserving the chess spectrum. On each score, what is the first hand, and what is the 100th hand, is easily learned by the AlphaGo.
But for chess, most of them are endgame since ancient times. Although the situation is very wonderful, but for AlphaGo, it does not know the cause of the formation of the residual situation, no knowledge of the previous steps, which will cause obstacles to its cognition.
It also shows how important the complete data is for AI. Anyone who throws data on AI is all a hooligan.
Unicorns in artificial intelligence
At present, most of China's data are controlled by BAT, and abroad are Facebook, Google, Amazon and so on. For entrepreneurs, breaking the monopoly of data has considerable challenges, but it is not without opportunities.
For example, medical data, BAT has not yet formed monopoly. Financial data are more in the hands of financial companies than those of Internet companies.
In these two areas, regardless of your technical level, at least on the same line of data, it is a rare opportunity for an entrepreneur or a post - entering company. Meanwhile, the next giant is also likely to be born in these two areas.
What is artificial intelligence? At last, it's white.