Currently, a technological revolution represented by a new generation of artificial intelligence industry is brewing. The construction of digital, networked, and intelligent information infrastructure is accelerating. Integrated innovation and cross-field innovation, characterized by the cross-fusion of information communications, life, and materials science, have gradually become mainstream. New industrial applications and new industries built around “intelligence” Business formats and new models are constantly emerging, and the “head goose” effect of artificial intelligence is fully exerted.
It is expected that in 2021, artificial intelligence will accelerate to become an important driving force in building a modern digital economic system and promoting high-quality economic and social development. As part of the “new infrastructure”, it will be closely integrated with new technologies such as 5G, cloud computing, big data, and industrial Internet. Integration forms the core capabilities of a new generation of information infrastructure and provides underlying support for the development of the digital economy.
Juicio básico sobre la situación en 2021
1.Emerging technologies continue to be nurtured, and integrated technological innovation with artificial intelligence as the core will accelerate
Since 2020, the application of my country’s single-point artificial intelligence technology has become more mature, but the collaborative large-scale and industrial application of artificial intelligence and related technologies is still in its early stages, and the efficiency of enabling high-quality economic development needs to be improved. We judge that in the future, individual artificial intelligence technologies will face a ceiling when they function independently.
It is expected that in 2021, new technologies and products such as virtual reality, ultra-high-definition video, and emerging automotive electronics will continue to emerge and accelerate cross-integration with artificial intelligence to promote the economic form of intelligent transformation of production, lifestyle, and social governance methods; with this At the same time, artificial intelligence and new generation information technologies such as 5G , cloud computing, big data, industrial Internet, Internet of Things, mixed reality (MR), quantum computing, blockchain, and edge computing support each other.
Through the industrialization of intelligent technology and the intelligentization of traditional industries, artificial intelligence will provide underlying support for the development of the intelligent economy and the digital transformation of industries, promote the deep integration of artificial intelligence and 5G with cloud computing, big data, the Internet of Things and other fields, and form a new generation of information Infrastructure core capabilities.
En términos de direcciones específicas, la innovación integrada caracterizada por la fusión cruzada se ha convertido gradualmente en la corriente principal, y el valor de la integración cruzada de múltiples tecnologías emergentes permitirá a la inteligencia artificial ejercer un mayor valor social y económico. Se espera que en 2021, la inteligencia artificial acelere la integración con la electrónica del automóvil y otros campos para realizar módulos funcionales especiales como la percepción, la toma de decisiones y el control, promover la formación de sistemas de aplicación de conducción autónoma, asistencia a la conducción, interacción hombre-vehículo, servicio y entretenimiento, e innovar aún más la cadena tradicional de la industria del automóvil. Hacer que los coches sean más inteligentes y estén más conectados; se espera que la inteligencia artificial se combine con la tecnología de realidad virtual para proporcionar herramientas para la fabricación, la decoración del hogar, etc., y proporcionar escenarios ricos para la fabricación virtual, la conducción inteligente, la atención médica simulada, la educación y la formación, el entretenimiento cinematográfico y televisivo, etc., un entorno de plataforma interactivo y oportuno.
2.The smart economy is beginning to take shape, and ubiquitous intelligence is developing rapidly
La epidemia de COVID-19 se ha convertido en la "nueva normalidad" para el desarrollo mundial en el próximo periodo. Tanto los países nacionales como los extranjeros se encuentran en un periodo de innovación, desarrollo, transformación y actualización económica y social. Existe una necesidad urgente de aplicar la inteligencia artificial. Consideramos que con la innovación de algoritmos, la mejora de la potencia de cálculo y la acumulación de recursos de datos, la construcción de infraestructuras inteligentes y las infraestructuras tradicionales lograrán actualizaciones inteligentes, y se espera que la tecnología de inteligencia artificial promueva la innovación inteligente en todos los elementos del desarrollo económico.
Looking forward to 2021, artificial intelligence will further promote the digital economy to enter a new stage of smart economy. The new economic form of smart economy has begun to take shape. Artificial intelligence will accelerate the integration with the real economy and become an important source of energy for industrial transformation and upgrading under the new normal. As one of the first, it not only promotes innovation in models and business formats such as smart manufacturing, smart logistics, smart agriculture, smart tourism, smart healthcare, and smart cities, but also drives the development of new products such as smart operations, smart software, smart hardware, and smart robots, ubiquitously the development of the intelligent economy will take shape. Artificial intelligence will give new connotations to cyber-physical systems (CPS), making them a more universal human-machine collaborative system.
In the future, the Internet of Everything will inevitably bring ubiquitous networks, ubiquitous data, and ubiquitous application needs. The application scenarios of artificial intelligence will expand to more industries, more fields, more links, and more levels. Anyone can, ubiquitous intelligence that can be used by any unit at any time and anywhere will be accelerated, which will further promote the deep integration of artificial intelligence technology with various fields of the real economy.
In terms of specific directions, it is expected that the manufacturing industry will be the field with the richest application scenarios and the greatest potential for artificial intelligence in 2021. Its application needs run through the entire life cycle of the manufacturing industry and will become a key area for the integrated application of artificial intelligence in the future. Artificial intelligence and manufacturing The deep integration will be promoted and deepened in more links and levels of the manufacturing industry. Demand orientation and pain point focus will become one of the keys to the integration of artificial intelligence and manufacturing. Artificial intelligence products and services will fall into specific industrial intelligent products. or system solutions in specific industry fields. In addition, since most industrial chain companies have not yet obtained value from artificial intelligence applications on a large scale, safety and input-output ratio will become an important decision-making basis for manufacturing companies to apply artificial intelligence. The key point of increasing its added value will be from equipment value mining to user value mining bottle by bottle.
3.Scenario empowerment becomes the main theme, and typical scenarios will become the focus of financing
As my country’s artificial intelligence technology gradually matures and application models and business models take shape, the artificial intelligence market and industry development will continue to improve. As of the end of June 2020, the scale of my country’s artificial intelligence core industry reached 77 billion yuan , and artificial intelligence companies intelligence exceeded With 2,600 companies, it has become one of the major concentrations of unicorn companies in the world. The artificial intelligence investment and financing logic of “scenarios determine applications, applications determine markets, and markets determine enterprise development prospects” has further gained recognition from all walks of life. It is expected that in 2021, the degree of segmentation and specialization in the field of artificial intelligence will be further enhanced, and the commercialization stage of widespread artificial intelligence applications will come. The government and the market will be more focused on applications that are closely integrated with specific application scenarios, especially with the application needs of the real economy.
Specifically, it is expected that local governments’ enthusiasm for the development of the artificial intelligence industry will continue in 2021, local support policies and measures will also become more pragmatic and operable, and application will become an important content that the government pays attention to and Domestic More cities (clusters) will focus on advantageous industries such as smart chips, smart drones, smart connected cars, and smart robots, and actively build solutions for key application fields such as healthcare, finance, supply chain transportation, manufacturing, home furnishing, and rail transportation. In-depth artificial intelligence application scenarios that are in line with local advantages and development characteristics.
It is expected that easy-to-implement artificial intelligence application scenarios such as new retail, driverless driving, medical care and education will attract more capital attention in the next year. At the same time, because China still lags behind the United States in the underlying technology of artificial intelligence, as artificial intelligence further develops in China, investment in underlying technology will continue to grow. Those underlying technology startups with top scientist teams and strong technological genes will With continued capital injection from the capital market, the transformation of the capital market will promote artificial intelligence to place more emphasis on rationality. Major companies will take root in the scene and dig deep into the application, making artificial intelligence products truly “useful”.
4.”New infrastructure” empowers all walks of life, and the underlying support for the artificial intelligence industry continues to improve
The Central Economic Work Conference proposed the concept of “new infrastructure” for the first time in 2018, pointing out that investment should play a key role, increase technological transformation and equipment updating in the manufacturing industry, accelerate the pace of 5G commercialization, and strengthen new technologies such as artificial intelligence, industrial Internet, and the Internet of Things. Regarding infrastructure construction, seven central-level meetings or documents have since made it clear that the strengthening of “new infrastructure” will be strengthened.
On March 4, 2020, the Standing Committee of the Political Bureau of the CPC Central Committee held a meeting and proposed to speed up the construction of new infrastructure such as 5G networks and data centers, which attracted greater attention. “New infrastructure” has rich connotations in the new era. It not only conforms to future economic and social development trends, but also adapts to China’s current social and economic development stage and transformation needs. While making up for shortcomings, it will become a new engine for social and economic development. Artificial intelligence “new ” Infrastructure” is of great significance to the development of the artificial intelligence industry. It is expected that in 2021, the construction of the artificial intelligence industry chain will continue to increase around the “troika” of new artificial intelligence infrastructure such as algorithms, data and computing power.
Specifically, in terms of computing power, my country’s 5G communication network deployment will accelerate in 2021, and the number of devices connected to the Internet of Things will increase to 50 billion. The growth rate of data will become faster and faster, and the amount of calculation required for artificial intelligence training will further increase. Showing exponential growth, the demand for computing power in related industries will be even greater.
The big data volume of leading Internet companies will reach thousands of petabytes, the data volume of leading enterprises in traditional industries will reach petabytes, and the data generated by individuals will reach terabytes. GPU, ASIC ､Computing units such as FPGA will become the underlying hardware capabilities that support the development of my country’s artificial intelligence technology, and the construction of the industrial chain around the Troika will continue to strengthen. In terms of algorithms, Cafe framework, CNTK framework, etc. collect and integrate different emerging artificial intelligence algorithm models, which can greatly improve the applicability of algorithm development scenarios. Artificial intelligence algorithms transition from RNN, LSTM to CNN to GAN, BERT and GPT. -3, etc., emerging learning algorithms will be more efficiently implemented in mainstream machine learning algorithm model libraries.
Several issues that need attention in the artificial intelligence industry
1.The basic computing power support capability of large-scale artificial intelligence is limited
Diversified artificial intelligence industry application data and more complex deep learning algorithms require powerful computing capabilities as support for implementation. It is expected that the amount of data will continue to grow explosively in 2021, and artificial intelligence algorithm models will become more complex and require higher levels of computing. capabilities, but domestic companies that can provide large-scale artificial intelligence computing power support are still very limited, and our country is generally underprepared in terms of artificial intelligence computing power infrastructure.
Professional organizations predict that the popularity of new generation information technologies such as artificial intelligence and 5G communications will cause the amount of newly created data in the world to rapidly increase from 33ZB in 2018 to 175ZB in 2025, which requires continuous upgrades in computer computing capabilities.
2010 Since the beginning of this year, with the popularization of GPU chips, FPGA and ASIC chips have accelerated their development and been applied in the field of artificial intelligence. In 2020, the computing power of supercomputers will reach the level of 10 billion times per second. However, with the continuous iteration and upgrading of the demand for computing power due to the development of artificial intelligence, a large number of domestic artificial intelligence chip companies still rely heavily on international giants such as Qualcomm, Nvidia, AMD, Xilinx, Marvell Electronics, EMC, Avago, and MediaTek to provide products that meet the requirements. Chip products, the development of leading enterprises in the domestic enterprise industry chain is still in the exploratory stage compared with giants.
In the field of commercial servers, international giants such as IBM, HPE, and Dell are firmly among the top three in the global server market, with Inspur, Lenovo, H3C, Domestic companies such as Huawei have limited market share.
2. Lack of open source and open artificial intelligence algorithm platforms and frameworks
This round of artificial intelligence industry development uses deep learning technology as the main engine. The open source and open deep learning underlying environment provides a basic guarantee for the evolution and innovation of technology. my country urgently needs to expand technological influence, promote technological innovation, and promote technological innovation through open source and open methods. Focus on the development of industrial ecology and provide new solutions for product traceability and system credibility assessment of artificial intelligence technology.
However, my country’s open source ecological construction started relatively late, and there is insufficient participation in the core artificial intelligence open source platforms and frameworks. The leaders of the global mainstream artificial intelligence industry algorithm frameworks and platforms are Google, Facebook, Amazon, Microsoft and other American companies, Baidu, 4Paradigm The algorithm frameworks and platforms of domestic companies such as Megvii Technology, SenseTime, and Yitu Technology have not yet been widely recognized and applied by the industry.
My country has insufficient support in the core technology field of deep learning frameworks, which is mainly reflected in: core technology and related technological innovations Limited capabilities, insufficient training performance and cross-platform support capabilities for neural network models; insufficient advanced design and development capabilities for deep learning frameworks, and lagging research on modular development and cross-platform support, which is not conducive to the formation of a complete artificial intelligence industry in my country Ecology, and has potential negative impacts on my country’s information infrastructure security, industrial security, and data security.
Chips have already put many Chinese companies and developers at risk, but deep learning frameworks have just attracted attention. The lack of core technologies will directly affect the development of chips, systems, software and hardware platforms related to the future artificial intelligence industry.
3. Industrial data standardization and interconnection levels are seriously insufficient
Data is the core element of iterative innovation of artificial intelligence. The development of new generation information technologies such as big data, cloud, Internet of Things, and 5G communications has produced unprecedented amounts of data, and the growth rate of data is getting faster and faster. Although my country’s artificial intelligence technology has implemented pilot applications in manufacturing, transportation, e-commerce, finance, medical and other fields, the application of industrial data by upstream and downstream enterprises in the industry is fragmented, repeated learning, sporadic scale, different standards, and scenarios With different characteristics, it is difficult to transfer the successful experience of a single industry or enterprise, which in fact delays the pace of the majority of small and medium-sized enterprises in using artificial intelligence technology to improve productivity and achieve high-quality development.
Data sources among different industries are more complex, data quality is uneven, annotation levels are different, and there is a lack of data standards and integration and sharing channels. As a result, data between various industries and within a single industry have not yet achieved effective interconnection and organic integration. Greatly reduces data availability and portability.
4. A customized artificial intelligence infrastructure construction evaluation framework embedded in industry scenarios has not yet been formed
Typical application scenarios serve as important “testing grounds” and “accelerators” for technology. Their evaluation, selection and creation will determine whether various industries can effectively use artificial intelligence infrastructure to improve their intelligence level and achieve intelligent transformation.
At present, our country has not yet effectively explored the development potential of rich data and diverse scenarios, and has not fully grasped the requirements and characteristics of the “new infrastructure” of artificial intelligence embedded in industry scenarios. Although it has a huge data scale and richer application scenarios, especially in the Financial, medical, education, manufacturing, retail, smart cities, government services and other fields have huge accumulation of basic data and demand for new generation infrastructure.
However, there is generally a lack of adequate assessment of the demand for artificial intelligence computing power and a lack of deep learning combined with their own industries. The ability to grasp, understand and apply algorithms, and the lack of awareness of gathering, coordinating, sorting, and cleaning industry data.
In fact, in the process of preventing and controlling the COVID-19 epidemic in 2020, the effectiveness of artificial intelligence industry as a “new infrastructure” has been fully demonstrated, playing an important role in relieving bottlenecks in the flow of people, logistics, information , and capital flows in various industries. It plays an indispensable role in preventing and managing major public safety risks, promoting the resumption of work and production of manufacturing enterprises, and maintaining teaching and education in universities and primary and secondary schools. It timely summarizes the successful experience in 2020 and sorts out the customized artificial intelligence infrastructure embedded in industry scenarios. The construction assessment framework is imperative in 2021.
5. There is a large gap in professional talents in subdivided application fields
My country’s further development of the artificial intelligence industry still faces the challenge of deep learning talent shortage. According to statistics from the Paulson Foundation think tank, China is the largest source of top AI researchers in the United States. As of the end of 2019, nearly 60 % of the world’s top AI talents have settled in the United States, of which 60% of the top AI talents who received undergraduate education in China The ratio is the highest at 29% (followed by 20% in the United States, 18% in Europe and 8% in India).
China is the largest source of top artificial intelligence talents in the United States and has played an important role in the innovation and development of artificial intelligence in the United States. According to LinkedIn big data, the overall supply of AI talents in the world is about 3.4 million, of which only 95,000 are deep learning talents, and their mobility is large, further widening the gap. Among them, China’s AI talents The total number is only 50,000. In 2020, the domestic artificial intelligence talent gap will reach more than 5 million, and the supply and demand ratio is seriously imbalanced; the penetration rate of children’s programming education in the United States has reached 44.8%, and it is only 0.96% in China; China’s top artificial intelligence talents only rank sixth, and the former The five are the United States, the United Kingdom, Germany, France, and Italy. In 2021, it is a top priority to continuously strengthen the training of artificial intelligence talents in our country and make up for the shortcomings in talent introduction and training.
Sugerencias
1. Promote the establishment of dedicated AI computing facilities to lay a solid foundation for computing power
Promover la creación de centros de supercomputación de IA para realizar cálculos de algoritmos de IA a gran escala, aprendizaje automático, procesamiento de imágenes, cálculos científicos y cálculos de ingeniería, acelerar la industrialización de la tecnología de inteligencia artificial en industrias verticales y promover el desarrollo de la industria local de inteligencia artificial. Promover la aplicación de la computación elástica, el almacenamiento masivo de datos y otras tecnologías para mejorar la eficiencia de la utilización de los recursos informáticos. Acelerar el desarrollo ecológico y eficiente de la infraestructura informática de IA y construir un centro informático ecológico y eficiente. Reforzar la planificación y el diseño tempranos del centro de computación, basándose en las necesidades de la aplicación, teniendo en cuenta factores y condiciones como la energía, el clima, las fuentes naturales de frío, las instalaciones de red, los indicadores de consumo de energía, etc., y diseñar y construir racionalmente la infraestructura de computación.
2. Build an intelligent ecosystem to create software and hardware synergy capabilities
Promover la realización de un alto grado de acoplamiento entre el software y los chips de IA personalizados para lograr un rendimiento óptimo. Crear capacidades de colaboración en la industria, promover una conexión eficaz entre las empresas de inteligencia artificial y las plataformas de la industria vertical y las plataformas generales, y garantizar el uso en tiempo real de las funciones de plataforma necesarias. Promover la conexión efectiva entre las instalaciones informáticas específicas de IA y los sistemas empresariales existentes en la industria, y crear un entorno ecológico de aplicaciones inteligentes basado en el soporte de la potencia informática. Apoyar a las empresas de la industria para que proporcionen infraestructuras informáticas inteligentes y servicios generales de software, reunir e incubar empresas de inteligencia artificial, promover el desarrollo de la industria de inteligencia artificial y crear un sistema de ecosistema inteligente de "investigación y desarrollo tecnológico, incubación industrial, capital riesgo, educación y formación, y entorno político de apoyo".
3. Continue to support the construction of artificial intelligence open source and public service platforms
Crear un soporte para la innovación tecnológica en inteligencia artificial, apoyar a las empresas líderes para que asuman el liderazgo, y unir a las empresas industriales ascendentes y descendentes, universidades, instituciones, instituciones profesionales, etc. para construir conjuntamente plataformas de innovación tecnológica en áreas clave de la inteligencia artificial, y apoyar a las universidades y empresas para que soliciten laboratorios nacionales y laboratorios nacionales clave, Centro Nacional de Innovación Tecnológica, Laboratorio de Ingeniería Clave y otras plataformas nacionales de investigación científica. Identificar varias plataformas de innovación tecnológica en inteligencia artificial a nivel de distrito y prestar apoyo en función de la eficacia de la innovación. Guiar y apoyar el establecimiento de una serie de plataformas abiertas de inteligencia artificial, proyectos de código abierto y bases de datos de sentido común a gran escala, establecer una serie de entidades de prueba de aplicaciones de inteligencia artificial basadas en plataformas, como plataformas de servicios públicos de tecnología de inteligencia artificial y laboratorios clave para la formación y verificación de pruebas en múltiples escenarios, y apoyar Proporciona marcos de desarrollo, bibliotecas de algoritmos, conjuntos de herramientas, etc. para la formación en la nube y la ejecución de terminales, y abre interfaces de tecnología subyacente e interfaces de llamada a bases de datos para que las universidades, instituciones y empresas innovadoras promuevan la innovación original e independiente en inteligencia artificial desde la fuente.
4. Build a supportive artificial intelligence policy toolbox
Improve the artificial intelligence industry data standards, evaluation, intellectual property and other service systems, strive to create standardized format data sets, establish metadata sets for artificial intelligence system training, verification and testing, focusing on industry terminology, reference frameworks, algorithm models, basic theories, key Technology, products and services, industry applications, safety and ethics, etc., provide application standards, deployment guides, and practical cases for the application of artificial intelligence technology in subdivided fields. Launch quantitative artificial intelligence technology measurement indicators, establish a standardized evaluation method system for artificial intelligence technology performance, and form an accountability system and audit tools for artificial intelligence intellectual property and ethical risks. Actively attract overseas scientific researchers, gather global talents, and launch a package of policies to introduce high-end overseas talents in a series of areas such as research funding, personal taxation, visas, household registration, children’s education, etc., to effectively solve the worries of scientific researchers and provide them with scientific research and entrepreneurship.
Palabras clave: What is the input and output module?
