The advent of the era of artificial intelligence has brought unprecedented opportunities and challenges to the entire technology industry. As the core hardware that supports the development of artificial intelligence, the innovation and breakthrough of AI chips will directly determine the development height of artificial intelligence technology. In this critical period, the mainland is making every effort to promote the independent innovation of AI chips, in order to occupy a favorable position in this scientific and technological revolution.
Artificial intelligence: the new engine of technological development
Artificial intelligence has been hailed as "a strategic technology for a new round of scientific and technological revolution and industrial transformation". Its rise has not only brought new development momentum to traditional industries, but also given birth to a large number of cutting-edge emerging industries. Whether it is intelligent manufacturing, intelligent transportation, or intelligent medical care, intelligent security, artificial intelligence is injecting new vitality into these fields.
With the continuous breakthrough of artificial intelligence technology, its application scenarios are also rapidly expanding. Large model AI, represented by ChatGPT, has demonstrated amazing capabilities and can efficiently complete a variety of complex tasks such as writing, programming, and Q&A. Artificial intelligence will be deeply integrated into all aspects of our lives, completely changing the production and lifestyle of human beings.
The development of artificial intelligence technology is inseparable from the support of computing power. High-performance AI chips are the key to providing computing power for artificial intelligence. Only by breaking through the bottleneck of chip technology can artificial intelligence achieve a real leap. The independent innovation of AI chips is crucial for the mainland to seize the commanding heights of artificial intelligence development.
Domestic AI chips: the only way for independent innovation
For a long time, the mainland chip industry has been in the dilemma of "lack of cores and fewer cores". Although domestic chip companies have made great progress in the field of traditional chips such as CPUs and GPUs in recent years, there is still a certain gap between us and the international advanced level in the new track of AI chips.
The design and manufacture of AI chips requires a large amount of capital investment, talent reserves, and technology accumulation. Due to its late start, the mainland once lagged behind developed countries such as the United States in this regard. However, in recent years, with the strong support of the national strategy, breakthroughs have been made in the development of domestic AI chips.
A large number of domestic chip companies have begun to deploy in the field of AI chips, including well-known companies such as Huawei, Horizon, and Cambrian, as well as many start-ups. They continue to innovate in AI chip architecture, process manufacturing, algorithm optimization, etc., and have launched a series of AI chip products with independent intellectual property rights, and their performance has approached or surpassed the international advanced level.
The state has also issued a number of major policies to vigorously support the development of the domestic AI chip industry. From finance and taxation, investment and financing to talent training, from market application to international cooperation, policies and measures have created a good development environment for AI chip companies in an all-round way.
Under the guidance of policies and the unremitting efforts of enterprises, the road of independent innovation of domestic AI chips will become broader and broader. Mainland will have more independent and controllable AI chip products, so as to truly grasp the initiative in the development of artificial intelligence.
Breaking through bottlenecks: multiple paths for AI chip innovation
The innovation of AI chips is by no means achieved overnight, and breakthroughs are needed at multiple levels. Innovation in chip architecture. At present, mainstream AI chip architectures include GPU, FPGA, ASIC, etc., each with its own advantages and disadvantages. In the future, more advanced and efficient architectures need to be explored to meet the rapid growth of AI computing power demand.
A breakthrough in the process. The advanced degree of the process technology directly determines the performance and power consumption of the chip. Although China has made significant progress in 14nm and 7nm processes, there is still a certain gap between it and the international advanced 5nm and 3nm processes. Conquering advanced manufacturing processes is a key part of achieving a leap in the performance of AI chips.
Algorithm optimization is also a key area of AI chip innovation. By optimizing algorithms such as deep learning and machine learning, the computing power potential of the chip can be maximized and the computing efficiency can be improved. The emergence of new algorithms will also promote the innovation of AI chip architecture and design.
The innovation of AI chips also requires the support of software and hardware collaboration, ecosystem construction, and other aspects. Only by forming a complete industrial chain can AI chips truly achieve a complete closed loop from R&D to mass production.
On the road of AI chip innovation, Continental is exploring a variety of possible technical routes. In addition to traditional digital chips, new concepts such as brain-like chips and quantum chips have also become hot spots in the industry. They are expected to break through the bottleneck of von Neumann's architecture and traditional processes, and bring a new round of computing power explosion to artificial intelligence.
The innovation of AI chips is a system project, which requires all-round breakthroughs and long-term persistence. Only when we continue to innovate at all levels such as chip architecture, process and algorithm optimization can we truly master the independent intellectual property rights of AI chips and inject lasting impetus into the development of artificial intelligence.
Talent training: the fundamental guarantee of AI chip innovation
Talent is the fundamental driving force of scientific and technological innovation. In the field of AI chips, high-quality compound talents are hard-core resources. Chip design requires a deep theoretical foundation in multiple disciplines such as computer, electronics, and mathematics, as well as hands-on practical ability. For AI chips, the understanding and application of AI algorithms are also essential skills.
AI chip talents must master both chip design and artificial intelligence expertise, which is very lacking in the current education system. Cultivating AI chip talents has become a key part of supporting the independent innovation of domestic chips.
To this end, domestic universities and scientific research institutions are actively exploring new models for the cultivation of AI chip talents. On the one hand, they have increased investment in related disciplines and improved the professional curriculum system such as chip design and artificial intelligence; On the other hand, they also cooperate deeply with enterprises to deliver accurate talent reserves for enterprises through project-based training, order classes and other forms.
A collaborative innovation mechanism combining production, education, research and application is also gradually established. Universities, research institutes and chip companies have carried out in-depth cooperation to jointly build an innovation platform and concentrate on overcoming major theoretical and technical problems in chip design. In this process, a large number of compound talents will be born.
The state also vigorously supports the cultivation of AI chip talents at the policy level. From improving the treatment of scientific researchers, to setting up special funds for talent training, to simplifying the procedures for talent introduction, a series of measures have created a good environment for the cultivation and introduction of AI chip talents.
Talent is the fundamental guarantee of scientific and technological innovation, and AI chip talent is the key to independent innovation of domestic chips. Only by intensifying talent training and building a talent highland can the mainland occupy a dominant position in this artificial intelligence chip revolution.
Industrial ecology: an important support for AI chip innovation
The chip industry chain is long, there are many links, and the investment is huge, and it is difficult to make a substantial breakthrough alone. Building a complete AI chip industry ecology and realizing the close collaboration of upstream and downstream enterprises is the top priority to promote the independent innovation of domestic chips.
In the upstream, the mainland needs to accelerate the localization process of advanced process technology and master the key core technologies of chip manufacturing. At present, there are not a few domestic companies that have mastered the 14nm and 7nm processes, but there is still a certain gap with the international advanced 5nm and 3nm processes. Breaking through the bottleneck of advanced manufacturing processes will directly improve the performance and energy efficiency of AI chips.
In the midstream, we need to cultivate a number of chip design companies with independent intellectual property rights. These companies will become the main force of AI chip innovation, and they need to master core technologies such as chip architecture and algorithm optimization, and work closely with upstream manufacturing companies to open up the channel of chip design and manufacturing.
In the downstream, it is necessary to develop and expand the application ecology of AI chips. Whether it is cloud computing, edge computing, or vertical applications such as intelligent driving and smart home, a large amount of AI computing power is required. Only by forming a complete application ecosystem can AI chips be implemented on a large scale, thus forming a virtuous circle of sustainable development.
We also need to pay attention to the seamless connection between the upstream and downstream of the AI chip industry chain. Upstream manufacturing companies should be deeply involved in chip design, midstream design companies should also feed back the optimization of manufacturing processes, and downstream application companies need to provide demand feedback for chip customization. Only by interlocking the industrial chain can we truly create a complete industrial chain of domestic AI chips.
The government, universities, scientific research institutions and other parties also need to actively intervene to provide all-round support for the construction of the AI chip industry ecology. The government needs to introduce favorable policies, universities and scientific research institutions need to provide talents and technologies for the industry, and enterprises need to be brave in innovation and practice. Only by working together can we finally create a domestic AI chip industry chain with active innovation and a complete ecosystem.