How is the future of artificial intelligence in the near future?

“In 2017 and even for a long time, the key developments in the field of artificial intelligence will focus on the application of weak artificial intelligence in the high degree of specialization and vertical.” On December 25, the CEO of the company, former Intel China Research Wu Gansha, chief engineer of the hospital, told the 21st Century Business Herald.

Looking back on the development track of artificial intelligence in 2016, the "AlphaGo" victory over Li Shishi at the beginning of the year led the limelight of this year's artificial intelligence technology. Also standing on the upper vents are vertical applications such as driverless. At the chip level, NVIDIA also introduces GPUs for deep learning. At the same time, more and more technology companies are advocating artificial intelligence, and companies such as Xiaomi and NetEase have joined the camp in the past year.

In Silicon Valley, the competition between artificial intelligence talents by Facebook, Google and Microsoft has been a landscape in the past two or three years. At the end of each year, Zuckerberg, who will challenge and learn one thing in the second year, re-coded the code at the end of the year: he spent 100 hours writing an artificial intelligence algorithm and will "manual "Intelligence" is the one that I personally challenged in 2017.

Even so, Zuckerbeck personally acknowledged the current bottleneck of artificial intelligence, and still can not build an artificial intelligence system that can completely learn new skills. At the same time, big companies like Facebook and Baidu have already collided with startups on the artificial intelligence track.

The future of artificial intelligence that is “near and far away”

Wu Gansha told the 21st Century Business Herald reporter that futurists are willing to exaggerate the progress of artificial intelligence in the short term, such as optimistic estimation of artificial intelligence technology can subvert everything. Wu Gansha was a former Intel chief engineer and currently serves as CEO of the autopilot company.

The optimism of futurists is not without reason. Li Shishi lost under the "AlphaGo", and the ability of artificial intelligence seems to once again crush the human IQ. However, if one considers that the "dark blue" at the end of the last world has defeated the chess champion, "AlphaGo" has only repeated the victory over humans in a certain type of quiz.

So far, the two concepts that need to be explained are “weak artificial intelligence” and “strong artificial intelligence”. The former is generally considered to be a smart machine that cannot really reason and solve problems. Strong artificial intelligence is the existence of enemy intelligence. In short, weak artificial intelligence is now ubiquitous: for example, through the siri arrangement in the iPhone, or the e-commerce website to answer questions through the customer service robot.

Similar expressions include "special artificial intelligence field" and "universal artificial intelligence." In terms of improving the operational efficiency of a certain field, "weak artificial intelligence" and "dedicated artificial intelligence" are already playing their own capabilities, which is already a consensus in the industry.

Zuckerberg recently spent 100 hours writing a set of AI program "Jarvis", but he also admitted that even if he spent 1000 hours, he could not build a system that can completely learn new skills independently - - Unless there is a fundamental change in artificial intelligence technology.

"In some ways, artificial intelligence is farther and closer than we think," Zuckerberg said. But in the next year, he will share his personal exploration of artificial intelligence.

On the one hand, there is a constant emphasis on and even advocating the current golden age of “artificial intelligence”. Even in industry forums, it is more than enough to discuss how artificial intelligence will replace human voice. On the other hand, it is more prudent for artificial intelligence. Attitudes, such as Tan Tieniu, vice chairman of the China Artificial Intelligence Society, publicly stated in the middle of the year that artificial intelligence-related technologies are in the period of expected expansion, and then may be "disillusionment."

Despite this, artificial intelligence technology has become popular in many vertical industries. Specifically, smart driving, security, medical health and finance have become the industry of artificial intelligence technology fermentation in the past year. Applications such as security and smart customer service have been in progress for several years.

Feng Rui Capital Technology Partner Yu Chao told the 21st Century Business Herald that artificial intelligence technology has been applied to some mature technology products in the past year. For example, the iPhone directly searches for the photo content in the mobile phone through text, and Jingdong intelligent customer service. Yan Chao believes that the difficulty lies not in the application of artificial intelligence, but in how to improve the accuracy of the intelligent customer service response. “Generally, the large platform will be launched to the market when the accuracy is raised to a certain level.”

Big company PK small company

Many industry insiders told reporters that the focus of artificial intelligence will still be a highly specialized market segment. For example, there are also opportunities in the medical field: this market is costly, and quality medical resources are still scarce in many parts of the country. This also means that “weak artificial intelligence” and “narrow artificial intelligence” are still prominent areas of artificial artificial intelligence fermentation in the future.

In this regard, Sogou CEO Wang Xiaochuan's judgment is that in the future, in the medical field, robot-assisted diagnosis will bring about a major change. In the financial sector, or in financial technology (Fintech), there are also a large number of uses. Secondly, for speech-like, image-related processing, including translation, there will be considerable progress in these human-computer interaction issues.

"We believe that there will be some more practical applications and landings in smart driving in 2017." Wu Gansha told reporters that smart driving has a higher threshold in the entire field of artificial intelligence. At the same time, Wu Gansha believes that the smart voice applications accumulated over the past two years may have explosive developments in the next year.

In 2016, the contest between large companies and small companies in the field of artificial intelligence is still slowly and continuously changing.

According to the fourth quarter of 2016, the artificial intelligence released by the venture scanner reported that the scale of venture capital in the field of artificial intelligence reached 8.9 billion US dollars, involving nearly 1,500 companies in 13 fields related to artificial intelligence. In addition, venture capital funds continue to enter this market. The reporter found through the official website of the venture scanner that as of the end of December, the investment funds reached 9.79 billion US dollars, and the global fund investment in this field exceeded 700.

Large companies have applied artificial intelligence technology to the improvement of existing mature products. For example, Google has launched a neural translation system in the field of translation. Tesla chose to land unmanned technology in its models. At present, HKUST is involved in the education industry, government industry, automotive industry, customer service industry, and Xunfei open platform and to C products. However, from a technical perspective, in all of the above-mentioned industries, the University of Science and Technology is involved in the field of perceived intelligence and cognitive intelligence.

The University of Science and Technology News told the 21st Century Business Herald reporter that in the next 5 to 10 years, artificial intelligence will enter every industry like water and electricity, and profoundly change the world.

But in this process, how should artificial intelligence be commercialized or industrialized? The answer to the question from CEO and former Google headquarters scientist Li Zhifei is that the path of large-scale companies and small companies is not the same in the commercialization of artificial intelligence.

“There are three roads that are relatively clear at the moment.” Li Zhifei told 21st Century Business Herald reporters that the first is AI priority: applying artificial intelligence technology to existing products, such as Google using AI technology to improve Google translation; second, The AI ​​technology is developed to the outside world in the form of API interface. This is also the practice of a large number of entrepreneurial artificial intelligence technology companies that lack a product. The third is, for example, going out and asking about this kind of software and hardware at the same time. Artificial intelligence technology is added to the watch.

“Most startups are doing +AI.” Face++ co-founder and CEO Inch believes that in essence, artificial intelligence does not “from 0 to 100” in industry applications, but extends 100 to 130. : Essentially you are optimizing industry efficiency. At the same time, Inch believes that compared with the previous wave of mobile Internet entrepreneurship, the difficulty of entrepreneurship in the field of artificial intelligence is relatively greater.

The barriers to artificial intelligence entrepreneurship include barriers to talent, technology, data, and computing power. These barriers are particularly evident in startups.

Wu Gansha told 21st Century Economic Reporter that large companies tend to build a basic ecology, while small companies focus on product applications. The infrastructure includes chips, big data, and cloud computing infrastructure. Small companies are either doing very well at a certain technology point, seeking to be acquired by a large company in the future, or exerting a force on a vertical application, but overall Large companies and small companies can achieve ecological win-win.

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