Machine learning makes the phone unique.
Editor’s note: Has the iPhone really stopped improving? No, what we see may progress slowly, but the technology behind it is evolving rapidly, and machine learning is the main representative of progress. This article was compiled from an original article titled “iPhone Evolution Hasn’t Stunted, It’s On A (Machine) Learning Curve”.
In the past many years, smartphones have evolved rapidly, now? The speed is slower than the snail. At the beginning, the progress was visible to the naked eye, the HD screen came, 3G came, the front camera came, and the bigger phone came. Hardware has become a hallmark of technological advancement. We always set super-high goals, let manufacturers go beyond, and slowly develop habits.
We look forward to “just-in-time functionality.” Apple (and competitors) knows that mobile phone functions are scarce and not very attractive. Therefore, when upgrading the mobile phone every year, only the pixel is increased a little (the buyer’s eyes are difficult to distinguish), the number of cameras is increased, and the battery life is extended.
Look at the iPhone 11 Pro official product introduction page, three-quarters of the space to introduce the camera, display. Progress is not great.
Face to reality! In recent years, the most sensational change in the iPhone is not Liu Haiping, nor is it a price increase.
Unknown hero
Go back to the iPhone 11 Pro product introduction page, the first three quarters introduce the camera, display, and then talk about the new A13 Bionic processor. Apple obviously values the next generation of chips and publicly praises it. The average consumer is concerned with the following things:
Sounds like it? There is indeed Bionic in the name. Can A13’s graphics technology make the background look cool? Yes. As an ordinary consumer, what can it bring to us? Faster, more cores, AR… and longer battery life. Then Apple spent some time talking about the battery life.
Then what? Nothing then.
Like the past
Apple’s description may be a bit exaggerated, but not far from reality. At the press conference, I saw people watching the watch many times and said, “Is it already the best part?”
We want equipment to improve every year. butAs an average consumer, it is difficult to figure out how progress is related to the functions they understand. In my opinion, because consumers can’t connect the two, they are numb with the progress of the past few years, and they don’t know how the progress of the past few years has affected the function of today’s mobile phones.
Like an athlete, using the entire off-season training and training in new ways, it demands all aspects of the athlete. However, in the eyes of fans, only when the athlete wins the game, with the results prove, we can see progress.
Two years ago, Apple introduced the A-series Bionic processor, which is what most consumers feel. Apple introduced a new and better architecture that enhances the iPhone’s capabilities. Not only that, it also launched the Neural Engine, a mobile engine for machine learning and AI. With the Neural Engine, Face-ID can become a reality.
Bionic achievements
The Bionic Revolution brings some visible achievements to the naked eye, as follows:
——Camera: Apple introduced on the website that the A series Neural Engine is the “driving force” of the 3-camera system. The number of cameras has increased and the quality has improved. With it, portrait mode, night scene mode, and SmartHDR will appear.
——Videos and games: Increased screen resolution, popular 4K streaming, and mobile game quality to gaming level, all require powerful computing power. The A13 CPU is 20% faster and consumes 40% less power.
——Speed and battery life: The Bionic architecture is quite complex. Let’s make another analogy. When we do group activities in schools, if we split the tasks and hand them over to several people, the speed will be much faster. If the people who do it are good at it, it will be faster. If we let a person do it, he has to deal with all kinds of things, even if they are good at it, they will reduce the quality when they do it, because he has to invest more time and energy in things that are not good at it. The situation with the processor is a bit similar.
The future is learning
The industry is always looking for “The Next Big Thing.” The iPhone is a catalyst for the mobile phone and the App revolution. It has changed everything in the technology industry, and people who joined early earned money. what’s next?
The machine learning station came out. Machine learning is everywhere, such as Alexa, IBM Watson, and portrait mode. The application potential of machine learning is endless, and it is used in industries such as finance, medical care, construction, and security.
Why is it now
The reason why the machine learning industry is advancing by leaps and bounds today is that machine learning technology is more approachable, more powerful, more time efficient, and more expensive. In the beginning, the mainframe was as big as a room. Later, a cloud remote control machine appeared. Through the network connection, now there is a mobile phone Neural Engine, which can be put into the pocket.
For iOS, machine learning/data science developers, this is an exciting time. With the help of Apple, it is easier to get machine learning technology, mainly through two ways. First, Apple provides developer tools, which makes it easier for developers to introduce machine learning technology into their apps. Second, Apple has put machine learning hardware in the user’s pocket. This was not the case. Developers who want AI to run on the mobile side must cut AI functionality. When they collect user data and process it on a remote server, they have to pay an expensive rental fee and maintain the machine. In essence, Apple is investing in machine learning for developers.
Investment pays off, as more and more developers realize the fact that even a little integration of machine learning techniques can bring new and stronger features. With the increasing number of machine learning technologies introduced by third-party and first-party apps, Apple can build a stronger App Store ecosystem. In the end, the profits and revenues of developers and App Store will increase.
Expect
Mobile phone manufacturers are working hard to introduce innovative technologies, but sometimes these technologies are flashy and immature, such as folding screen phones.
Consumers should pay more attention to the progress of the underlying technology and pay attention to their value. If I suggest that everyone learn machine learning techniques, then I will be stupid. But machine learning has indeed arrived, right in front of you.
Translator: Xiaobing Hand