The explosive development of artificial intelligence has brought a lot of business opportunities to all major fields. The cloud domain giants have already emerged, and the opportunities for those who want to be in the cloud field have become fewer and fewer. In the future, terminal-side artificial intelligence will usher in tremendous development opportunities, and manufacturers and capital will gather to the terminal.
After years of development, with the development of infrastructure such as ICT, cloud computing will be strengthened, and many Internet giants have entered this market. But for new-entrant entrepreneurs and investors – the “kings-to-eat†effect of the giants and the high valuations of mature companies have turned them out.
Opportunities in the cloud have become less and less, and with more and more advanced algorithms, more and more powerful terminal-side computing performance, and high-speed development of network connectivity, workloads can also be performed on the terminal side.
According to Gartner, the total shipments of smartphones will reach 8.5 billion units in the next five years. The reality that has occurred is that in 2016, the global smartphone market shipped a total of 1.47 billion units. According to Qualcomm's prediction, mobile terminals will become the most popular artificial intelligence platform in the world.
In the future, terminal-side artificial intelligence will usher in tremendous development opportunities.
When we talk about artificial intelligence, we have no less than keywords such as algorithms, calculations, speech, image recognition and vision. In fact, almost all well-known domestic and foreign Internet giants are concentrating on the application of these fields in the "cloud."
For example, Alibaba announced that the first quarter of the 2018 fiscal year (April to the end of June 2017) financial report shows that the number of Alibaba Cloud paying users increased from 874,000 in the previous quarter to 1.011 million, becoming the first in Asia to reach A cloud computing company with a million user scale.
Baidu CEO Li Yanhong also said that financial services and cloud computing business revenues have boosted (Baidu) revenue growth, such as the expansion of personal cloud business, the increase in the number of users.
Ma Huateng has repeatedly said that the future of the Internet is to use artificial intelligence to process big data in the cloud. Since the 2015 financial report first mentioned Tencent Cloud, the cloud business has been repeatedly emphasized in Tencent’s financial report. In Tencent's 2017 first quarter earnings report, Tencent's cloud services and payment-related services were included in “other business incomeâ€, up 224% year-on-year.
In addition to competing for the user market in China, Alibaba Cloud and Tencent Cloud have begun overseas deployments. Overseas, the cloud computing market is dominated by vendors such as Amazon, Google, Microsoft and IBM. The biggest player is Amazon. As the world's largest cloud computing company, Amazon, China's BAT three Internet giants have the same number of data center servers. And big players like Amazon have long been eyeing the Chinese market.
The "cloud" war has intensified. It can be observed that both the "GAFA" in the United States and the "BAT" in China are enterprises with many years of development and accumulation. The battle for this field will still show a strong Matthew effect - the "cloud" needs a lot of With the support of technology and data, the investment of small companies in technology is difficult to compete with the giants, and it is difficult to obtain the data mastered by the giants; on the other hand, the Internet giants naturally have the advantages of content, channels, users, and the ecosystem is complete.
In a nutshell, there are fewer and fewer opportunities for latecomers who want to be in the "cloud" field.
Why do manufacturers and capital gather to the terminal?Over the years, when people talk about artificial intelligence computing or storage, most focus on how to strengthen the computing power of the cloud. For the consideration of mobile terminals, it is basically how to collect data faster and more abundantly.
In most people's perceptions, the processing and calculations related to deep learning are in the cloud, and the mobile phone is just an interface. For example, if you want to identify an artifact, you are accustomed to transferring its image to the cloud, and then returning to the mobile terminal after comparison.
But as the example that has been mentioned numerous times: a driverless car needs to respond quickly during driving. Once there is no network or network is bad, human life will be threatened; even if the network is in good condition, if the system still needs Upload the collected road and vehicle information to the cloud and get the results before processing. This is more reliable than the direct processing on the car.
Reliable - this is one of the advantages of the terminal. Overall, the advantages of the terminal include: privacy, which is easy to understand, data privacy protection issues; low latency, and efficient use of network bandwidth.
In the past, most Internet giants spent more energy on the development of the cloud, on the one hand based on their original business form, on the other hand, this also has a great relationship with the development level of terminal-side technology.
The challenge of terminal-side artificial intelligence is that the artificial intelligence workload itself is very complex, it requires a lot of intensive computing, and it has always-on and real-time online needs; on the terminal side, like a smartphone, a drone , cars, etc., its computing environment is very limited, so they complete artificial intelligence workloads to overcome thermal efficiency, battery life, memory and storage space.
But with the development of mobile technology, these problems are being solved or optimized. At present, mobile processors have come to the process node of 10 nanometers in the process technology. The more advanced process technology means smaller cell size, higher processing performance and lower power consumption.
The scale effect of mobile technology is even more important. According to Gartner, smartphone shipments will reach 8.5 billion units in the next five years from 2017, and smartphones will undoubtedly become the most popular artificial intelligence platform in the world. Shen Jin, vice president of Qualcomm and vice president of Qualcomm Ventures, said earlier that online traffic portals are getting fewer and more expensive, and the future entrances are terminals of all sizes, including mobile phones, cameras, and sensations. Detectors, robots, etc. We need to master these portals, and if we don't master these portals, these values ​​will stay in the cloud. This is also the importance of artificial intelligence on the terminal side.
Meng Pu, chairman of Qualcomm China, also expressed similar views in his speech entitled "5G Achievement Intelligence Age". At the same time, he also believes that 5G will play an important role in the intelligent era of the Internet of Everything. 5G not only provides several gigabits per second transmission rate, lower latency and higher reliability, but more importantly, it can support cellular base stations to connect a large number of devices, which is impossible for 3G and 4G." Future machine learning will develop in harmony between the cloud and the terminal."
Lenovo CEO Yang Yuanqing also said that artificial intelligence contains two important aspects, perception and cognitive ability. He believes that smart terminals are human senses, clouds are the brain, and the perfect combination of smart terminals and cloud brains is the future direction of artificial intelligence.
For a time, terminal computing is becoming more and more optimistic, and vendors and capital are beginning to gather intensively toward the terminal.
In early September, Huawei released the Kirin 970, with a dedicated NPU (Neural Network Unit) dedicated hardware processing unit; Intel has acquired Altera, Yogitech and other companies, and acquired related technologies in the field of FPGA; Softbank to 23.4 billion The price of the pound bought ARM, which is intended to be embedded artificial intelligence; Tesla quietly made the unmanned car AI wafer in production without the introduction of Nvidia. The newly released iPhone is just equipped with the Apple A11 Bionic processor, which is also equipped with a neural engine that specializes in AI requirements.
In terms of capital, the valuation of companies related to the cloud has become more and more "unattainable", and the terminal wafer has recently become a hot track in the AI ​​field.
In August of this year, Cambrian Technology announced the completion of the $100 million Series A financing, becoming the first unicorn company in the global AI wafer field; at the end of October, the domestic AI wafer start-up company Shenjian Technology completed the A+ round of financing, its investment The party includes Ant Financial, Samsung Venture Capital, China Merchants Venture Capital and Huachuang Capital, raising about 40 million US dollars...
Qualcomm focuses on terminal side artificial intelligenceAlthough artificial intelligence is a concept that has been proposed in recent years, Qualcomm has been working in the field of artificial intelligence for more than a decade as a global leader in mobile communications.
In 2007, Qualcomm began exploring machine learning impulse neural methods for computer vision and motion control applications, and subsequently extended its research from bionic methods to artificial neural networks—primarily deep learning. In July 2017, Qualcomm began offering developers the Snapdragon Neural Processing Engine (SNPE) software development kit. SNPE is the first deep learning software framework designed for the Snapdragon mobile platform. It supports TensorFlow and Caffe/Caffe2. It has an automatic converter without modification, analyzes the performance through the SDK, and then integrates it. It provides developers with software tools to accelerate the operation of deep neural network workloads for mobile terminals and other types of network edge terminals equipped with the Opteron mobile platform.
Not long ago, Qualcomm just announced the acquisition of Scyfer BV, a subsidiary of the University of Amsterdam, which specializes in cutting-edge machine learning technology, to enrich its relevant talent team. Scyfer has created artificial intelligence solutions for companies in a variety of industries around the world, covering manufacturing, healthcare and finance.
On the morning of October 20, Shangtang Technology, the largest artificial intelligence startup in China, also announced with Qualcomm that the two companies will cooperate on artificial intelligence (AI) and machine learning (ML) around mobile terminals and the Internet of Things. Shang Tang Technology's algorithm will be targeted for Qualcomm's Snapdragon platform, and Qualcomm's Snapdragon will open up the "capability" to Shang Tang, which will fully leverage the fusion of algorithm + wafer.
From an investment perspective, Qualcomm Ventures, a venture capital arm of Qualcomm, has invested in nearly 40 companies since it entered China in 2003, including companies in the forefront of technology. To date, Qualcomm's companies and projects in the field of artificial intelligence include: the American brain group, which has used seven years to start from the brains of researchers, to provide software, to robots, to achieve mobility and navigation. There is also American face recognition company Clarifai; China Intelligent Voice Company Yun Zhisheng and so on.
Shen Jin has publicly stated that the scale effect of smart phones can bring about rapid iteration of technology, rapid cost reduction, reduction of mobile phone power consumption, and reduction of handset volume. At the same time, the scale effect of smartphones will also be radiated to other industries, including industries that need to use wafers and hardware, such as smart cities, automobiles, healthcare, networks, wearables, industrial Internet of Things, smart homes, and so on.
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