The focus of this book is not to predict the future of AI, but rather to describe what tasks AI can accomplish and which tasks it cannot perform. According to Hendler, the problem is that many people see AI as a "terminator" or a Utopian dream, without considering human factors. He said: "People like to portray AI as a black and white technology. But in reality, it needs human participation. Humans are better at dealing with the problem of the 'grey' zone." Borrowing from the more common political slogans of the past: we - humans And artificial intelligence - uniting will be more powerful. This is an important point of view expressed by Hendler when he discusses the future of AI. AI is used for large-scale programming. Hendler said: "I think what I'm really excited about for a short time is that for programmers, AI technology is becoming simpler and easier to use. It is no longer necessary. Professions are just areas for fun.â€ An AI cognition calculation course currently taught by Hendler highlights this point. Undergraduates are also engaged in AI-related projects, such as developing chatbots in a matter of weeks to answer questions related to Harry Potter. If it was a few years ago, such research should be the subject of a doctoral dissertation. What happened to the AI? There is no need to develop deep learning, computer vision or natural language components from scratch. Just download an open source package, integrate it into your system, and make some changes. This is a bit like playing "WordPress", but Hendler prefers to compare it to the early days of the Internet. In the early 1990s, thanks to a variety of pre-packaged code that could be installed on a machine, simply create a website with a simple understanding of HTML. Hendler said: "AI has already completed the packaging process in a usable way. It is more like splicing components and finding out which way to maximize their effectiveness, rather than basic research on these components. At least This is indeed the case in the more practical technical areas.â€ Opening the door to innovation Hendler stated that in the short term, AI technology will open its doors to industry participants of all sizes. He said: "We will see small businesses using existing deep learning, visual and language technologies to start a lot of innovation. Microsoft, Google, Facebook and other technology giants will also make a significant investment in this technology, but they will target new directions. At the same time, academic institutions and governments will play an important role in the evolution of AI-related technologies. Hendler took the driverless car as an example. This technology was first developed by universities such as Stanford University and won the Grand Challenge held by the US Department of Defense Advanced Research Projects Agency (DARPA). Google then further pushed this technology to maturity. Now, it seems that all car manufacturers are developing driverless cars. Although it is still necessary to develop new AI technology to solve the problem, Hendler said that the short-term focus will be on business cases that can be achieved using existing tools. He said: "I think entrepreneurs and start-up companies will also focus on this type of innovation, and the number of innovations will be enormous." Solving Problems in Developed Countries and Developing Countries After 2017, ordinary technology users will see progress in the AI â€‹â€‹field. In this case, more may mean less because the technology will be seamlessly integrated into the background of the user. Hendler said: "Someone may be looking forward to buying something, the whole world will become completely different. But in fact, there may not be such a clear change." Take Apple virtual assistant Siri as an example. The ability of Siri to perform complex tasks is constantly improving, but it still can't find answers. It can only provide web search results by default. Perhaps in the near future, we can give orders to Siri or similar services: Show me pictures of the children eating lunch today, and the latter can give the results quickly and accurately. In fact, many startup companies mentioned by Hendler have already achieved this goal. A company called Snips uses a technique called context aware to filter various data such as contacts, emails, calendars, photos, etc., to create short-term memory on the user's mobile device. Over time, it can understand what is really important to the user and eventually become the only interface for various applications and information on the user's device. Sninds founder and CEO Rand Hindi (Rand Hindi) said in his TEDx speech in 2015: "The key to using AI is to make this technology disappear invisible. You just have to live your life every day without Pay attention to it.â€ Of course, â€œletting technology disappear invisibleâ€ is a problem faced by developed countries. Hendler optimistically believes that those projects aimed at improving the status quo in developing countries will soon be integrated into AI technology. Hendry and others are working with IBM to plan to help one billion people in the next five years. He said: "What we are talking about is a big improvement in the lives of many people, especially in those countries where the literacy rate is still relatively low. Under such circumstances, people will suddenly see technology entering their lives in an unprecedented way. Education is the key, albeit both good and bad, but AI will drive more and more large-scale disruptive technologies in the future. On the one hand, 1.8 million truck drivers may be replaced by driverless cars in less than a generation. On the other hand, the aviation industry such as pharmaceuticals may save huge costs. In fact, IBM's famous artificial intelligence platform Watson has been deployed to the pharmaceutical industry on a large scale. According to the data released by the US Medical Insurance and Medicaid Center, the medical industry accounts for approximately 17.5% of the total US GDP. Hendler said that the government needs to initiate these changes rather than create obstacles to innovation. He insists that education will become the key to the "AI revolution" and help people understand the areas where computers are better at and the deficiencies they can't do. He said: "People need to be smarter in this area, and technical staff should help decision makers understand these differences. This is a crucial issue."
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