On December 27th, Apple finally stopped obscuring and released its first artificial intelligence research report. According to industry insiders, this will be of great benefit to Apple's future promotion of its artificial intelligence applications. Apple said earlier this month that it will publish its own artificial intelligence research report. In less than a month, Apple fulfilled its promise. Recently, Apple released the first academic paper on artificial intelligence.
On the 22nd, he released his first research paper on machine learning, detailing how to use the computer to synthesize the recognition ability of image training algorithms. The paper explains that computer-generated images already contain markers and annotations compared to images captured directly in real life. When training computer artificial neural network algorithms, a lot of manpower is saved, and the programmer does not need to tell the computer one by one, what is shown in the figure. However, it is obvious that computer-composited images lack realism compared to the real world. In this paper, a method called “simulation + unsupervised learning†is proposed. Apple has also improved the existing generation-response network model to make the generated images more realistic. Apple's high-profile voice into the field of artificial intelligence, and then quickly published research results, enough to see its interest and ambitious.
The first author of this report is Apple researcher Ashish Shrivastava, who holds a Ph.D. in computer vision from the University of Maryland, College Park. According to industry insiders, for Apple, the publication of its first artificial intelligence research report is also a big step forward. Over the years, Apple has been keeping a tight eye on its research in the field of artificial intelligence, which has been criticized by the artificial intelligence research community. At the same time, this also affected Apple's recruitment of artificial intelligence talent.
So what happened to Apple’s process of entering the field of artificial intelligence?
The outside world has always believed that Apple is relatively low-key in the field of artificial intelligence, and its technology is also behind Google, Microsoft and other companies.
In fact, Apple has a two-page machine learning application, some of which are already in use, and others are still under discussion. Behind these applications is that Apple has quietly acquired 15 artificial intelligence companies over the past six years, including: speech recognition, natural language processing, image recognition, face recognition, motion capture, machine learning and other innovative technologies. the company.
It is interesting to note that every time Apple acquires an AI company, it will not announce the acquisition purpose and development plan, and will immediately close the products and services of the acquired company.
Speech, semantic recognition
Siri voice assistant
Siri is undoubtedly Apple's most important voice product. In 2010, it was a very cost-effective purchase at a price of 200 million US dollars. After that, Apple's acquisitions in the direction of voice recognition and NLP were based on Siri.
Novauris speech recognition
In April 2014, Apple acquired Novauris, an automated speech recognition technology company. Novauris was founded by the founder of Nuance's Dragon Systems, and Nuance was the provider of basic voice technology for Siri. Their core product is the server-based scalable speech recognition system NovaSystem, which features simultaneous access to multiple voice access requests. Although Apple declined to disclose how to use the Novauris team, but from the partnership between Siri and Nuance, Apple's acquisition is intended to get rid of Nuance's dependence, using the Novauris team to develop their own voice technology.
VocalIQ man-machine dialogue
Siri has always been able to identify the most basic instructions and cannot make a highly matching answer, which has made it an entertainment property entertainment product. In October 2015, Apple solved this problem by acquiring VocalIQ. VocalIQ is able to use deep learning to understand the language environment, making human-machine dialogue more natural. After embedding VocalIQ's artificial intelligence technology in Siri, developers use this platform to store and learn user communication information, to accurately identify user instructions and provide a smarter dialogue.
Machine learning
Apple has mentioned that they use AI technology to test some micro-functions: such as identifying strange incoming calls; detecting the user's movement status; listing the most likely applications after unlocking the phone; automatically displaying nearby hotels; schedule; interest news recommendation and many more. These seemingly simple functions are all put into the machine learning system. For this reason, Apple has adopted a number of machine learning companies that use interest recommendation and custom prediction as research directions to improve their data mining capabilities.
Turi Machine Learning Platform
In August 2016, Apple spent $200 million to acquire machine learning company Turi. At present, Turi has launched products such as GraphLabCreate, Turi Machine Learning Platform, TuriDistributed and TuriPredicTIve Services, which are mainly used to develop solutions such as recommendation engine, sentiment analysis and fraud detection.
Cue data mining
In October 2013, Apple acquired Cue, known as the “cloud data search engineâ€, for $40 million. Cue can be used from user mail, contacts, Facebook, Twitter, LinkedIn, Reddit, Dropbox, Evernote, Tumblr. Collect data, organize it by processing all the data and find the information the user needs through machine learning algorithms: such as providing calendar reminders, notifying appointments with someone, meeting restaurant recommendations, etc. It is reported that Cue will be integrated into Siri.
Matcha video recommendation
In August 2013, Apple acquired Matcha for about $10-15 million (the two parties did not announce a clear transaction price), and its products can be crawled from streaming media sites such as Netflix, iTunes, Hulu, and Amazon Prime. The right information is given to the user. Apple's acquisition of Matcha is mainly to obtain video recommendation algorithms. Before the offline, Matcha's iOS app ranked in the top 15 of the App Store entertainment category software, and the user growth rate is very fast.
Semetric music data mining
In January 2015, Apple acquired Semetric for $50 million. The company launched the Musicmetric service in 2008. Its main business is to provide data analysis services related to music download and streaming, and use machine learning to help customers analyze music in social media. Fans like songs and songs to give relevant music recommendations. After the acquisition, Apple integrated it into iTunes music. In addition to music, Semetric's data analysis services in games, TV, movies and books also have a certain accumulation, which will help enhance Apple's data mining of its various digital products.
Spotsetter map social personalized recommendation
Spotsetter is a social search engine based on Google Maps. It was acquired by Apple in June 2014. It analyzes the user's social circle data and provides users with personalized location (such as tourist locations and restaurants) recommendation service, which is dedicated to solving the so-called "where to go" question. Apple's acquisition purpose is nothing more than the prospect of its recommendation algorithm and Apple Maps integration.
WiFiSlam machine learning and pattern recognition
In March 2013, Apple acquired WiFiSlam, an indoor navigation service provider, for $20 million. The company's strength lies in machine learning and pattern recognition technology, which can correlate data collected by various sensors on the device, and with WiFi triangulation. The data is combined to map accurate indoor maps, and Apple applies its algorithm to the map.
Topsy Social Data Mining
In 2013, Apple acquired Topsy for $200 million. The company's products help users extract critical information from Twitter and other social media data, including keyword trackers and how users respond to a topic in social media.
Computer vision
Apple officially mentioned that their face recognition and video detection technology has begun to be applied to products such as cameras. At the same time, the source said that Apple has acquired a number of companies focused on computer vision for the development of VR/AR products.
PercepTIo image recognition
In October 2015, Apple acquired PercepTIo, an image recognition company that develops an artificial intelligence image classification system on the smartphone side. The biggest advantage of this system is that it does not require a large amount of external data for classification. This is in line with Apple's privacy protection strategy, minimizing the use of user data and putting as much technology as possible on the phone side, not the cloud.
Metaio Computer Vision
In May 2015, Apple acquired Metaio, a technology company specializing in computer vision and augmented reality. It has more than ten years of research and development experience in computer vision, especially face recognition.
Polar Rose face recognition
In December 2011, Apple acquired Swedish face recognition vendor Polar Rose for $29 million. Polar Rose has launched several products, including FaceCloud, a face recognition technology for web services, and FaceLib, a feature for mobile phones. Its face recognition software, through face recognition Polar Rose, can automatically circle the faces in the photos for the user.
Emollient face recognition
In January 2016, Emollient was collected by Apple, which can analyze human expression through face recognition technology to judge people's emotions. Doctors can also use their company's technology to understand whether a patient's expression is painful. You can also apply this technique to a monitor to see if someone with a "sudden expression" is squatting in front of the product.
Flyby Media Computer Vision
Earlier this year, Apple quietly bought Flyby Media, which has cutting-edge computer vision technology, and its inertial sensing, simultaneous positioning and navigation space sensing technology is also popular with Apple. Flyby media has worked with Google to help Google develop Project Tango using computer vision technology. Flyby Media helps the system see and map its surroundings, essential for driverless cars and augmented reality.
Artificial intelligence is so hot, how can Apple miss this opportunity, it is bound to occupy a place in the field of artificial intelligence!
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