At present, the most concerned technology is non-artificial intelligence, but Apple, the world's most market-worthy company, seems to be indifferent to this. It is considered to be seriously behind in the field of artificial intelligence. There seems to be no more than the voice assistant Siri. But the real situation may be completely different from the outside speculation. Backchannel editor Steven Levy recently visited Apple and found that the company actually used fashionable deep learning technology before the industry and used it in all aspects except Siri. Read this article to quickly understand which Apple products have been invaded by machine learning, why it can secretly develop new technologies for many years, what challenges does machine learning bring to its culture and principles, and how it is “opposite†with the mainstream industry...
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On June 30, 2014, Siri ushered in a brain transplant.
Three years ago, Apple was the first mainstream company to integrate an assistant into its operating system. Siri is Apple's improvement of an independent application acquired, and it swallowed the development team in 2010. For Siri, the initial evaluation was gratifying, but in the months and years to a few years, users became increasingly impatient with its shortcomings. It often misunderstands the instructions, and there is no improvement in how to adjust.
So on the date mentioned above, Apple ported Siri's speech recognition to a neural network-based system. This service was first targeted to US users and was launched globally on August 15. Some early technologies are still useful, including hidden Markov models, but now the system uses machine learning techniques, including DNN (deep neural network), convolutional neural networks, long- and short-term memory units, and closed recurrent units. , as well as n-grams and so on. After the user upgrades, Siri still looks the same, but has been enhanced by deep learning.
As with other underlying improvements, Apple did not disclose Siri's progress due to its reluctance to expose itself to competitors. If the user notices something, it is only that it has made fewer mistakes. Apple also said that the improvement in accuracy is shocking.
Eddy Cue
Eddy Cue, senior vice president of Apple's Internet Software and Services Division, said, "The effect of this improvement is so obvious that it has been retested to make sure that no one is wrong."
The story of Siri's transformation will make people in the field of artificial intelligence frown, not because the neural network is improving the system, but because Apple is so skilled and so low-key. Until recently, although Apple has increased its recruitment in the AI ​​field and made some high-profile acquisitions, it is still considered to be slightly behind in the most intense AI competition. Because Apple has always kept a tight mouth, even AI experts do not know what it does in machine learning. Jerry Kaplan, who teaches the history of artificial intelligence in Stanford, said, "Apple is not part of the community, like the NSA (National Security Agency) in the AI ​​field." It is generally believed that if Apple's efforts are as serious as Google and Facebook, it should be known to the outside world.
Oren Etzioni of the Allen AI Institute said, "Google, Facebook and Microsoft have top-notch machine learning talent. Apple does hire some people, but who among the top five machine learning leaders work for Apple? Apple has speech recognition technology, but Besides, machine learning can help."
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However, just earlier this month, Apple secretly demonstrated the use of machine learning in its own products. But it was not shown to Oren Etzioni, but was shown to me. On the same day, I stayed in the Apple Copitino spacecraft headquarters building most of the time. Accompanied by Apple executives, I felt the close integration of Apple products in artificial intelligence and machine learning. (Executives include Eddy Cue, Vice President and Marketing Director Phil Schiller, and Software Director and Senior Vice President Craig Federighi) Also present are experts responsible for developing Siri. When we were all seated, they showed me a machine learning application full of two pages, some of which were already in use, and some of which were still under discussion.
If you are an iPhone user, you probably have benefited from the improved user experience brought by machine learning. But contrary to intuition, machine learning is not just applied to Siri. Identify unfamiliar calls, list the apps you use most often after unlocking, or mark an appointment in a reminder (but you don't put it in the calendar), and automatically show nearby hotels with tags, these are in Apple After fully embracing machine learning and neural networks, you can do even more perfect.
Yes, this is the legendary "Apple Brain", which is already built into your iPhone.
Facial recognition using neural networks
"Machine learning," an expert said, "is now ubiquitous in Apple's products and services." The Apple store uses deep learning to identify fraudulent behaviors, and the feedback received by the beta operating system is also filtered using artificial intelligence to find useful feedback reports. There is also Apple's News app, which uses machine learning to pick out news sources that may be of interest to you. Apple Watch also takes advantage of machine learning to detect whether a user is exercising or just hanging out. There is also a well-known camera face recognition, the iPhone has already been equipped with this technology. In the case of weak Wi-Fi signals, iOS will also recommend you to use cellular networks for power reasons. It can even tell the difference between shooting a video and quickly snap a group of related videos together after clicking a button. Of course, these Apple competitors are not bad, but executives emphasize that Apple is the only company that balances user privacy and user experience. Of course, to achieve this standard on iOS devices, only Apple can do it.
For Apple, artificial intelligence is not new. As early as the 1990s, when Apple introduced the Newton tablet, the matching stylus used a certain degree of artificial intelligence to recognize the characters entered by the user. The research results are still glowing for the Apple Empire, the Chinese character recognition system on the Apple Watch. This system allows the user to enter extremely scribbled strokes that are still accurately identified. (These functions have been developed by a unified machine learning team for decades. Of course, early machine learning was extremely primitive, and the current deep learning is still in its infancy. Nowadays, artificial intelligence and machine learning have become the hallmarks of human beings. Apple has been criticized in this regard. In recent weeks, TIm Cook has finally spoken that Apple is not focusing on artificial intelligence, just less publicity. Now, executives have finally changed their way of doing things, and made Apple's achievements in artificial intelligence public.
Machine Learning for Health Applications for Apple Watch
"Apple has grown rapidly over the past five years," said Phil Schiller. "Our products are also improving at a very fast rate. The A-series processing chips have a lot of performance breakthroughs every year, which gives us more performance. More and more machine learning techniques are applied to end products. There are many good things in machine learning, and we have the ability to use it."
Even though Apple embraces machine learning as much as any Silicon Valley technology company, their use of machine learning is still restrained. The geniuses of Cupertino do not think that machine learning is a panacea for solving all problems. Artificial intelligence is the way of interaction in the future, but touch screens, tablets, and object-oriented programming play the same role in a specific period of time. In Apple's view, machine learning is not what other companies say, it is the ultimate answer to human-computer interaction. “Artificial intelligence is not fundamentally different from the various media that have changed human-computer interaction in the past,†says Eddy Cue. Apple is also not interested in the old-fashioned discussion of whether machines will replace humans. As expected, Apple did not recognize the car-making plan, nor did it talk about the rumors of homemade TV dramas, but Apple's engineers made it clear that they would not create something like "Skynet."
"We use technology to solve things we couldn't do before, and we've improved the old paradigm," Schiller said. "We make sure that every technology can be applied to the product in the most Apple way."
Later, they further explained the above viewpoints. For example, the extent to which artificial intelligence reshapes Apple's ecosystem. The original intention of Apple to develop artificial intelligence is to make up for the lack of user experience caused by the lack of search engines. (Search engines can train neural networks to make them mature quickly.) Here, executives once again emphasize Apple's determination to ensure user privacy. (Even if this would limit the use of user data, thereby hindering the effects of machine learning) executives stressed that these obstacles are not insurmountable.
How big is this "brain"? How many user data caches are available on the iPhone for machine learning calls? The engineers' answers surprised me: "The average is 200Mb, depending on the amount of user information." (To save storage space, the cache will be cleaned up from time to time). This information includes the usage habits of the application, interaction with others, neural network processing, and "natural language models." There are also object recognition, face recognition, scene recognition, etc. for neural network learning.
For Apple, this data is your private information and will not be uploaded to the network and the cloud.
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