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2017 development review of artificial intelligence AI
2017 development review of artificial intelligence AI
AI is like today's "wild west". Tim Leland, the graphic director of Qualcomm, told me earlier this month that the company launched the latest high-end mobile chip. The design of Snapdragon 845 is designed to better handle the task of Artificial Intelligence Computing. This is the latest achievement in the technology industry that is obsessed with artificial intelligence. No company wants to be left behind, either by optimizing the hardware to stop AI disposal, or by machine learning to speed up the task. Every main brand has invested a lot of money in AI. However, although artificial intelligence had soaked in all aspects of our life in 2017, the reactionary was just beginning.
This may be a very useful time point and can be used to clarify the general name of a variety of different technologies. Our digital assistants have artificial intelligence, such as Siri, Alexa, Cortana, and Google Assistant. You'll find artificial intelligence on Facebook's Messenger chat tool, like the automatic response function of Facebook. It is defined as "the intelligence that is displayed by the machine", but it also means that the computer stops operating without human instruction. Then it is machine learning, that is, computer self - learning how to do what human beings do. For example, recently, the Massachusetts Institute of Technology's face recognition system has learned how to identify humans, like humans, without the help of the creators.
The important thing is not to confuse these concepts - machine learning is a subset of artificial intelligence. Let's use the term "machine learning". When we specifically discuss neural networks and models like Google TensorFlow library, AI refers to robots, devices and software, which can accomplish tasks they once learned.
This year, AI has become so intelligent that the computer has defeated the human race, and has won a successful "Pac Man" score, so as to keep pace with the super star game players. People are beginning to use artificial intelligence to predict disease in medicine and to discover suicidal users on social networks. Artificial intelligence also begins to write music and write movie scripts.
No matter where you are, there are always some people who want to apply artificial intelligence to something. All this is due to the neural network that Google, Microsoft and its peers continue to invest in this year. They bought AI business and launched or expanded the AI department. The progress of machine learning is very fast, and it will continue to improve next year.
One of the biggest changes at the time of 2018 is the transformation of machine learning from cloud computing to the mobile phone. This year, Google, Facebook and Apple launched a mobile version of the machine learning framework, allowing developers to accelerate AI based tasks in their applications. Chip manufacturers are also numerous for machine learning to design mobile processors. HUAWEI, apple and Qualcomm have adjusted their latest chipsets this year, providing special "nerve center" to better manage the workload related to AI. However, apart from the Microsoft translation of "iPhone face ID" and "HUAWEI Mate 10 Pro", we haven't seen any detailed examples of the benefits of AI chips.
At the root, the artificial intelligence technology has been improved for many years, but the large part is based on the cloud. The image recognition system is taken as an example. At the beginning, it may distinguish between very different men and women. However, as the project continues to stop more image exercises in the cloud, it can better distinguish users, and these improvements will be sent to your phone. In 2018, we will put real artificial intelligence in our pockets. You can execute models on mobile devices, not only faster AI, but also store data on the phone instead of sending it to the cloud, which is more beneficial to your privacy.
Obviously, this industry is working for our smart phones and other devices, enabling them to learn autonomously, improving translation and image recognition technologies, and providing more personalized services. But as the available hardware is getting better and better in disposing machine learning and computing, developers are still trying to find the best way to add AI to applications. No one in the industry really knows what the killer application case is.
In the end, every industry and every aspect of our life - from the shopping center to the autopilot - will be transformed by artificial intelligence. Stores will understand our tastes, sizes and habits, and use these information to provide services for us, or to tell us where we can find what we want. When you enter a store, wholesalers will know who you are, what you bought in the past, what allergies you are, and whether you have been to a doctor recently. What's your favorite color? The AI of the system will understand what you purchase in a specific period of time, and recommend similar or competing products to you, and provide corresponding information on the display screen on the shelf.
Cars will be able to avoid obstacles, use machine learning techniques to better identify risks, and stop navigation at risk. Your doctor will soon rely on artificial intelligence to classify X - ray, MRI and other medical images, so as to reduce the time of diagnosing patients.
Artificial intelligence has been very popular in the category of image identification, and it will soon become more and more improved. Home safety cameras have been getting better and better in identifying humans, dogs, cats and cars. If this ends up
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