1. Before the Samsung executives were in town, Rokid's first AI chip reduced costs by 30%?
Set micro-message (Text / Xiaobei) According to foreign media technode report, China's AI startup company Rokid will be held on June 26 in Hangzhou, held in Hangzhou for the first time since the establishment of the first conference Rokid Jungle released a self-developed intelligent voice chip.
According to the official introduction, after two years of research and development, the chip has high performance and low cost. Its price may be 30% lower than similar products, and the chip can provide better design for third-party suppliers, OEMs and small device manufacturers.
It is reported that Zhou Jun, the former head of Samsung Semiconductor’s China area, jumped to Rokid as vice president in April of this year. He once said that due to the technical requirements of smart speakers, there is no universal chip equipped with a neural network processing unit and a digital signal processor. It is difficult to be competent, even if it meets the demand for computing power, it will consume too much in power consumption and cost, which is not conducive to the promotion of intelligent voice products such as smart speakers.
Dr. Zhou Jun first taught at the Department of Electronic Science and Engineering of Nanjing University after graduating from school. After that, he successively worked at Nanjing Microelectronics, Double Power Technology, Samsung Semiconductor (China), and is a senior semiconductor person.
According to Lei Feng reports, Zhou Jun has said that Rokid AI chip focuses on the field of voice interaction. Its development path is: In the limited capacity, maximize performance, while reducing the price from the perspective of reducing the cost of the supply chain, so as to create competitiveness.
Founded in July 2014, Rokid is headquartered in Hangzhou and has R&D centers in Beijing and San Francisco. It is positioned as an intelligent hardware company focusing on AI human-computer interaction.
Smart Voice is one of the main directions of Rokid. In October 2017, Rokid and Alibaba Cloud jointly launched a full-stack voice open platform to provide a one-stop voice solution for the industry. Today, Sonos San Francisco held a new product launch and announced that Rokid is the only one in the world. Chinese voice partner. It is reported that Rokid and Amazon at the same time began to do intelligent voice interactive hardware. Rokid's hardware product line is a smart speaker Pebble (Moonshiki).
In addition to the smart speaker Pebble, Rokid also owns the intelligent robot Alien (alien) and AR glasses.
Rokid has won multiple rounds of financing. In August 2014, Rokid received IDG, Linear Capital, Mfund, and Angels Capital’s $8.3 million angel round investment; in October 2015, he won the Walden International Leading Angel Investor’s investment. Tens of millions of dollars in Series A financing; on November 1, 2016, they were awarded by Shangshang Capital, IDG, Mfund, Lansing Capital, Walden International and other institutions with the investment in Series B financing, the amount was not announced, but Rokid officials said that B After the round of financing, the company's valuation reached 450 million U.S. dollars. In January 2018, a new round of financing was completed. The lead investors were Temasek, Credit Suisse, CDIB, and IDG. It was reported that the financing amount was close to 100 million U.S. dollars.
2. From the long tail market, Jinyun Technology can make an AI core;
Xing Yang Capital Founding Partner Yang Ge and Xing Hao Department CEO Jin Yun Technology CEO Niu Yuyu received an interview with Yibang Power. In the field of artificial intelligence, this future technological development will focus on the development prospects of the start-up AI companies. The application direction and how to grasp market opportunities and other topics were shared.
AI chip's rivers and lakes in the 'China Core' call and the trend of artificial intelligence sweeping across all industries, the fire do not want.
The traditional chip giants Nvidia, Intel, Qualcomm, Internet giants Google, Alibaba, Baidu, and entrepreneurial leaders such as the Cambrian, Shenzhen Science and Technology, Horizon, etc., have all raised a lot of high-profile investment from the capital level. The amount of financing starts at 10 million US dollars.
In addition, there are also the dark horses such as Bit Continent and Kennan Soochi that have emerged directly from the application market. From a single bitcoin mining, they ran out of mining machine chips and began to extend to other application areas.
In a market where big gamers compete, is there a chance for start-ups? Where are the opportunities? How to seize the opportunity? Yibang Power talks with the rather low-key Jinyun Technology. A member of the team, the background of the team is not expected to be gorgeous. The team's soul character Lu Yongqing is the British Royal Academy of Engineering, the Institute of Electrical and Electronics Engineers (IEEE), the British Academy of Sciences academician, Imperial College professor, in 1992 began to study custom computing chips, Participated in the development of the world’s first high-level compilation software for custom chips, Handel-C.
Many of its CEO NIU Yu-yu and the team’s core R&D staff are students of Academician Lu Yongqing. Niu Yu-Yu said that Jinyun Technology has almost evacuated the talents of the major AI laboratories of the Imperial College of Technology.
At present, Jinyun Technology has a laboratory research team in the UK, and has algorithms, hardware, products, operations and other teams in Shenzhen and Shanghai.
Different from other high-flying artificial intelligence chips, Jiyun Technology's initial technological capabilities are aimed at providing a customized end-to-end AI application solution for IoT terminals and vertical domains.
'Our chip architecture is divided into two layers, the upper layer is customized data, the bottom is a unified chip architecture. Customization can ensure that the chip performance is strong enough, generalization can ensure that the cost is low enough. The technology accumulated in our laboratory is through the compiler Deploying the requirements of different algorithms to the chip, automating the personalization with a compiler, both solving the customization and guaranteeing high performance while solving the common problem. ' This technology simulates the human design process through a compiler Automatic generation of customized chips, which greatly reduces the threshold and cost of chip design.
Yang Ge, a founding partner of Xingyi Capital, who invested in Jinyun Technologies in Pre-A, also mentioned that chips are a highly-invested industry, which can cost millions to tens of millions, and require continuous iterative upgrades. The entire artificial intelligence application market is still very elementary, and applications in many fields are at an experimental stage. The market is extremely fragmented, and traditional chips are too expensive for the market. It is too expensive to develop chip costs for market segments. Cloud technology can achieve a great deal of customization and versatility, and can provide a better market price.
The opportunities of LoT market start-ups are more to grow with the market. The current market is characterized by a very wide spread, very decentralized, and large scale, which gives us opportunities for growth. In some areas such as smart phones, the market is very large. , The demand is relatively single, it is suitable for giants to fight in the inside. Some areas have requirements for AI chips, need low power consumption, high enough performance, can be embedded in the front, while the market has not been normalized like a mobile phone, giants Input and output in these areas are not directly proportional.
This leads to the creation of a market for GAP.
Many start-up companies come out of the lab, have technical strength, and the team is small enough and fast enough to quickly respond to such market demands. Compared with the giants, there is a speed and cost advantage, and they are technologically premised , there is a prerequisite for the growth of such companies. '
Niu Haoyu and Yang Ge also saw this opportunity.
It is understood that Jinyun Technology's game is aimed at a vertical segmentation field, customizing a complete set of end-to-end software and hardware solutions, by customizing the artificial intelligence algorithm model into modules, and configuring them into unified bottom-layer chips to solve the actual industry. Problems, contributed to the chip's tape.
'The chip itself has no value, only the solution runs on the chip, to solve the customer's actual problems can provide value. The AI market is not mature enough to provide only the chip can solve the problem, is still in its infancy. Take out a chip, It's not hard, but startups need to think about how to land quickly and industrialize. The development of the chip industry is following the industrialization. The chip is the result of industrial development, not the reason. ' Niu Yu-Yu said.
In addition to COMAC, a major customer of China Aerospace, Jinyun Technology has focused on smart cities, industrial monitoring, smart manufacturing, and smart finance. Niu Haoyu told Yibang Power Network that Jinyun Technology selected the industry. There are three criteria:
The first is that the market is large enough to reach 100 billion yuan; the second is deep enough in the market; the third is close enough to commercialization.
It seems that smart cities, finance, etc. are almost all industries targeted by AI companies, a single market, but in fact, Jinyun chooses to be a long-tailed, deeply-spread market in this large market. 'The deeper the market, the more we can accumulate. The more customization programs, the more slowly we have accumulated one by one scenario. Iterate over our own chip architecture according to the application scenario. This is the value we can accumulate.
Different from the AI company that sells face recognition in the security field, Jinyun Technology emphasizes providing other capabilities than face recognition. It uses a whole set of more customized solutions to move customers and solve needs. This is at the current stage of AI development. , It is very easy to get the customer's approval.
It is not the ultimate goal of Jinyun Technology to tackle the market and solve the problem in one area. As a chip company, Niu Yuyu's expectation is to personally accumulate a number of industry scenarios, develop algorithms, and deeply understand the needs of each subdivided industry. , Form a set of practical and feasible solutions, so as to continuously optimize the AI open platform of Jiyun Technology, so that users on the platform can develop and design solutions for subdivided industries at a low cost, and finally the solution will be landed on the bottom chip, and the scale will be maximized. Reduce the cost of the chip.
Jinyun AI development platform mainly focuses on the field of artificial intelligence chips, and can provide full automation support from data labeling, hardware compilation to board testing. It can be automated only by providing user data labels, and provides customized AI for specific areas. Front-end products and solutions, without the need for the underlying hardware expertise, greatly reduce the user's use threshold.
'Our development is bound to be more and more open cooperation. At this stage we as a start-up company to call everyone to use our development platform, this is difficult. On the contrary we can attract everyone to do it together.
What value can we provide to the market? Stable chip, low enough price, mature application case, let developer can make money. If an AI chip company can't do these points, it won't be quite big. The opportunity for growth. ' Niu Yu-yu said.
For the upcoming LoT big market, all chip entrepreneurs are expected to be lucky. However, many fields are still using the AI function such as data calculations in the cloud, just because of the price of AI chips. Too high, it is not realistic to popularize in terminals. Individual wealthy buyers only place AI capabilities on the terminal in partial test scenarios. In the future, let end devices have an AI chip. Is this a certain trend?
Niu Yu-yu thinks that the trend of terminal + cloud is basically a pattern of the future. Some algorithm training, a large number of confidential data can only be entered into the cloud, and many need not to store data, private data, data that need fast feedback is more suitable Put on the terminal processing.
Take the mall flow management as an example. If all camera data is transmitted to the cloud for processing, one camera generates half a T of data a day. Many of these data are not related to commercial applications and are transmitted to the cloud. The cost is high, and the cost of back-end server storage is also high. Especially for chain stores, cloud-based deployment cannot support it.
On the contrary, if each camera can handle basic face extraction, tracking and other calculations, and only transmit the extracted data to the cloud aggregate analysis, it can greatly reduce costs and increase efficiency. Here, it needs a sufficiently low cost. The chip is embedded in the camera. This is also the development direction of Jinyun Technology.
The characteristic of the chip is that the higher the cost is, the lower the cost will be. Firstly, it is used in the military industry, and the big companies finally go to personal consumption. Retailing is actually pulling the chip directly to the level equivalent to the C-side consumption. If a camera program is done in hundreds of pieces, Personal consumption is more competitive.
But when this time can come, Niu Yu-yu can not give accurate answers, more driven by market demand.
At present, the AI chip buyer is mainly based on government agencies and large-scale enterprises. The real LoT era is still in the darkness before dawn.
'The entire AI chip ecosystem has just started. Great companies such as Nvidia and Google are also in the exploration stage. However, the ecology that will ultimately win will form an industry monopoly, such as intel in the PC era and ARM in the mobile Internet era.
Who can successfully land before the monopoly? All AI chip entrepreneurs want to be their own.
3. More than 50% of AI technology is still not mature by 2022;
According to Gartner, an international research and consultancy, according to the artificial intelligence technology maturity curve, 86% of artificial intelligence technologies have not yet entered the "trough of Disturation" (mature period starting point), including predictive analysis, cognitive experts Advisors and virtual customer assistants, etc., move toward more practical and stable applications.
At the same time, Gartner also predicts that in the short-term - 2022, 54% of artificial intelligence technology applications have not yet reached the stage of technological maturity, can not enter the mainstream market, but in the long-term 85% of artificial intelligence technology will bring about tremendous changes in the industry Transformation, and provide high returns and business value.
Tracy Tsai, Gartner's vice president of research, said: 'The rapid growth of computing power and data, coupled with deep neural network (DNN) technology has won unprecedented research results, making artificial intelligence known as the most breakthrough in the next decade. In the next five years, we can see that many related technologies have retreated from the peak of the overheated market, returning to rationality and essence, and laying the foundation for entering the mainstream market applications; enterprises can also use this to precipitate restructuring. Opportunity, to clarify the application and commercial value of artificial intelligence in the enterprise, and then to grasp related technologies to solve unprecedented problems, while pursuing innovative mentality, to promote their own business transformation and create commercial value.
AI technology will continue to create huge business opportunities and job opportunities in the next 2 to 5 years
Gartner predicts that by 2020, at least 40% of people will interact with human-centered design technology. In the future, the human-centered design of the interface, the machine can understand human natural language judgment intentions, and therefore invest in how humans learn to use technology. The resources for operations will also be significantly reduced; in addition, 95% of the video or video content will no longer be manually reviewed, but will be passed by the machine to provide different levels of automated analysis; also in 2020, in the new artificial intelligence project Companies that adopt cognitive cognitive ergonomics or system design will achieve four times longer long-term success than other companies; artificial intelligence will also become a major source of new job opportunities in 2020 compared to alternatives. With 1.8 million jobs, the introduction of artificial intelligence by enterprises will create 2.3 million jobs.
In addition, Gartner also predicts that in 2021 artificial intelligence will achieve a business value of 2.9 trillion US dollars, and the equivalent of 6.2 billion hours of productivity; The commercial value created by artificial intelligence can be divided into three categories, including: Improve operational efficiency and quality, Improve customer experience, create new business models and revenues.
Improve operational efficiency and quality; Companies can use this to increase their competitive advantage, or risk losing their businesses in the next five years. Take the manufacturing industry as an example. Importing artificial intelligence technology can be used for predictive maintenance, quality control, inventory management, and industrial Robot automation, demand forecasting and improving logistics and warehousing operations, etc., increase product efficiency while also improving product quality and value; other application examples include chat robots built in customer service centers, virtual personal assistants (VPAs) or no one Banks use virtual agents etc.
Improve customer experience, enhance customer relationships, and distance from competitors. Take Xiao Bing, an artificial intelligence robot launched by Microsoft in China. For example, Xiao Bing can learn customer information from conversations, understand customer needs and emotions, and accelerate Service flow and improve the quality of interactive experience. At present, it has accumulated more than 30 billion conversations, and it can be used for 23 conversations each time.
Open up new business models and revenues to drive business transformation to bring new business opportunities. Take intelligent refrigerators as an example. In addition to food items and storage dates in intelligent function controllable refrigerators, they can integrate other e-commerce. The information of the platform will display relevant information on the screen outside the refrigerator, even on mobile phones and smart speakers, and transform into a new digital sales channel. The suppliers of smart refrigerators will also expand from original manufacturing and sales to new ones. Digital business opportunities, gaining new revenue growth through the transformation of customer experience and habits.
Cai Huifen pointed out: 'In the years following the rapid development of artificial intelligence, the commercial value created by the rapid decline in artificial intelligence still lies in improving customer experience and reducing business costs, including deepening customer understanding through artificial intelligence, improving interactive quality and experience, and increasing the number of visitors. And stickiness, or use artificial intelligence to improve business efficiency and decision making quality, which in turn reduces business costs; but from 2021 onwards, the introduction of new revenue generated by the introduction of artificial intelligence by enterprises will become a major business value, gradually in the artificial intelligence technology. As it matures, companies can better grasp the application of related technologies in market practice, thereby developing an unprecedented business model and expanding new value chains.
Enterprise AI Application Challenges: Lack of understanding and high complexity
According to Gartner's survey, nearly 90% (89%) of the companies surveyed believe that the lack of knowledge and understanding of artificial intelligence technology and the complexity involved in integrating the old and new technologies are the biggest challenges faced by companies when adopting artificial intelligence technology; Including existing products, services and even IT architecture, business process chaining, defining their own company's artificial intelligence strategy, identification of commercial value applications, and even the introduction of artificial intelligence after the benefit assessment.
Cai Huifen suggested that: 'For enterprises wishing to deploy artificial intelligence technology, in addition to strengthening their understanding of data science and IT technology, they should continue to deepen the mining of process pain points and problems in the professional areas of their industries. Artificial intelligence solves problems to get the most benefit. It even recruits or nurtures the cross-domain talents needed for the development of artificial intelligence technology, and is responsible for cross-disciplinary work such as data and analysis supervision, or data analysis and interpretation, etc., while examining the essence of artificial intelligence technology. When applying, enterprises should also raise the level and consider the impact of intelligent functions on customers, objects, ecosystems, and IT systems in all aspects. For IT leaders, establishing action plans with collocations is the key to deployment of artificial intelligence technology. First assess which existing problems artificial intelligence can use to solve, and work with other companies to identify suitable artificial intelligence applications, etc.; Long-term can increase the amount of manpower to maintain a competitive advantage, or re-examine with the changes in technology, Evaluate existing practices, Promote enterprises Agility of operations. ' Gartner
4. Hanwang's face recognition business cooperates with ZTE, Dahua and other companies;
In response to the micro-network news, Hanwang Technology responded to investor questions on the interactive platform on the 7th, saying that the company’s face and biometrics business units are working with companies such as ZTE and Dahua in some projects. In the future, the company will seek out more. Industry giants are likely to cooperate in more business.
5. Spring and Autumn Electronics: Subsidiaries and Foxconn have cooperation in the mold field;
According to the micro-message news, Spring and Autumn Electronics responded to investor questions on the interactive platform on the 7th. Foxconn is one of the subsidiaries' customers and has cooperation in the mold field. The company and Xiaomi, Apple have no direct business relationship.
6. BYD changes fund-raising use 1 billion yuan to build Qinghai lithium battery project
According to the micro-network news, BYD announced on the evening of June 7 that the company plans to increase the total amount of fundraising for the “Iron-Power lithium-ion battery expansion project” originally fundraising project from 6 billion yuan to 5 billion yuan, and change the fund-raising amount of 1 billion yuan. In the '12-kilowatt per year power lithium battery construction project' invested and built in Qinghai, the main entity for the new fund-raising project is BYD Lithium Battery Company of Qinghai Province.