In the first year of Zhenguan in the Tang Dynasty, Master Xuanzang began to travel westward for the knowledge of ultimate yoga. After many hardships, he arrived at the Nalanda Temple [Nālandā], the center of ancient Indian Buddhism. He searched for more advanced literature for further study, and later became proficient in the Tripitaka. He traveled widely across India to study and collect scriptures, and showed his outstanding talent in debates. It can be said that this "open source exchange" activity that has lasted for more than ten years has had a profound impact around the world. In the late Zhenguan period, Master Xuanzang returned to China and was warmly welcomed by Emperor Taizong of the Tang Dynasty. He devoted himself to translating Buddhist scriptures and made great contributions to the development of Chinese Buddhist culture.
Looking at the current development of artificial intelligence (AI), we also see similar results.
In recent years, AI has developed rapidly like a blowout and has successfully crossed over from the initial stage. However, when it is deeply integrated with corporate business, it has ushered in a new round of unprecedented challenges, just like Master Xuanzang encountered the problem of insufficient documentation when he studied Buddhism deeply. Dilemma. At present, the development of artificial intelligence computing systems still faces challenges such as low algorithm efficiency, insufficient computing resources, limited Internet bandwidth, and energy efficiency bottlenecks. Enterprise applications are driven by demand and require coordinated progress of algorithms, computing power and data. Therefore, global innovation with the system as the core has become a new industry paradigm that promotes the rapid development of artificial intelligence.
Empower industries and accelerate the implementation of AI
Recently, Inspur Information held the IPF2024 Inspur Information Ecological Partner Conference in Beijing with the theme of "Intelligent Yuanqi Chuangxian·Cooperation", which deeply discussed hot topics such as the combination of AI and enterprise applications, accelerating the implementation of innovation, and released at the meeting Blockbuster products such as the enterprise large model development platform "Yuannao Qizhi EPAI", AI universal servers that support the operation of large models with hundreds of billions of parameters, distributed all-flash storage and super AI Ethernet switches have once again revitalized the ever-growing popularity of the AI market. Added a fire.
Peng Zhen, Chairman of Inspur Information
Peng Zhen, chairman of Inspur Information, gave a professional interpretation of the development, application, breakthroughs, strategies and future development of artificial intelligence at this conference. In addition to providing more efficient computing power, Inspur Information also provides more platforms, Tools to empower partners and accelerate the implementation of AI technology.
It can be seen that the rapid development of artificial intelligence has had a profound impact on the industry. It not only changed the three elements of productivity - workers, production factors and labor tools, but also brought about disruptive changes. According to the latest report from ARK Invest, from 2023 to 2030, the contribution of artificial intelligence to global GDP will exceed 4.5 times the impact of transformative technological machines such as steam on the entire economy in the past 80 years. This data not only demonstrates its huge market potential, but also indicates that AI will become an important engine for future development.
“人工智能给产业应用带来了前所未有的效率提升。例如，在编程领域，AI辅助的编码工具能够显著提高开发效率，编码效率提升了2.2倍；在医疗健康领域，AI技术被用于体检和诊断，极大提升了医疗服务的效率和质量，新药研发提升了3倍。这些进步不仅优化了工作流程，还推动了相关行业的快速发展。”谈到人工智能的应用，彭震这样介绍道。
The rapid growth of the AI market is expected to continue in the next few years. As the technology matures and application fields expand, artificial intelligence will play a key role in more industries and promote social and economic development. In the future, artificial intelligence will also create a new market of up to 25 trillion US dollars.
谈到人工智能的突破，彭震表示：AI的突破性进展依赖于三个核心要素：算法、算力和数据。在算力方面，随着芯片技术的进步和计算架构的不断创新，AI的计算效率得到了显著提升。这些改进不仅加快了数据处理速度，还降低了AI应用的成本，使得更复杂的AI模型得以实现。
In terms of algorithms, the development of large AI models has greatly improved the intelligence level of AI. These large models are able to process larger amounts of information and demonstrate more advanced capabilities in understanding, predicting, and generating content. At the same time, data plays a crucial role in the development of AI. High-quality data can not only improve the accuracy and performance of AI models, but also help AI better understand and adapt to complex and changing environments. Therefore, large-scale, high-quality data sets have become a key resource for AI research and application. The interaction and common progress of these three elements have promoted the rapid development of artificial intelligence technology and achieved unprecedented breakthroughs in many fields.
As a pioneer in the field of large model technology, Inspur Information took the lead in releasing the "Source 1.0" large model in 2021, and has accumulated rich experience in R&D and application implementation. EPAI (Yuan Nao Qi Intelligence) has been successfully applied in multiple business links such as Inspur Information's R&D, operations and services, promoting the innovation and application of large models.
Inspur Information solves complex problems
If artificial intelligence is a delicious meal, then this wave of information has already prepared it for users from all walks of life: dining places, tools, basic ingredients, seasonings, tableware and chefs. Ordinary users can order directly on demand. Users with special needs can be customized specifically, which can be said to be comprehensive.
The interesting question is: As an infrastructure company, how can Inspur Information build such a complete ecosystem to meet the various complex needs of users?
In the peak dialogue of "Ecological Progress in the Intelligent Era", guests from China Science and Technology, Torsi, Ronglian, Luchen, Xianyuan Technology and Inspur Information conducted in-depth discussions on the implementation of artificial intelligence in the industrial ecology. discussed and shared their own thoughts and practices.
Shi Shuicai, chairman of Torsi Information Technology Co., Ltd., said: Both hardware and software are fully embracing AI, and Inspur Information provides users with an integrated terminal through a sound partner ecosystem, a completely open source model and the EPAI platform. An end-to-end development platform. At the same time, inference has very high server requirements, and users urgently need strong products to support this aspect. Inspur Information's carefully polished AI universal server solves these problems and has accurate product positioning. When considering the huge industrial opportunities brought by today's AI field, we noticed an obvious trend: the diversified development of multiple computing power, multiple models, and multiple scenarios. While this diversification opens up a wide range of opportunities, it also raises a key question – how to make the entire ecosystem more efficient.
Liu Jun, senior vice president of Inspur Information, said: If we expect every computing chip manufacturer, model developer, and thousands of ISV development partners to be able to effectively connect with a large number of enterprise customers and achieve results transformation, in order to cope with this To meet the challenge, Inspur Information builds the Yuan Nao ecosystem and connects left- and right-hand partners to help enterprises solve various challenges encountered in the implementation of AI applications, such as technical complexity and deployment difficulty. This enables it to quickly build and deploy AI applications, lower the development and implementation threshold of AI applications, and better accelerate the empowerment and innovation of AI technology.
Software companies: efficiently transform data into productivity
The implementation of large models is the most talked about topic in this summit forum, and the challenges faced by each company are also different. For example, how to transform data into productivity has become one of the most important focuses for everyone.
Zuo Chun, chairman of ZhongkeSoft Technology Co., Ltd., believes that software companies are in a critical stage of transformation. Currently, Zhongkesoft has three main tasks. The first is to choose a base with low energy consumption and open technology. Inspur Information has obvious advantages in this regard. Advantages; the second is model training, users will adjust the training direction according to needs, and software companies need to make connections; the last is the induction stage to meet the various needs of users for implementation. Generative artificial intelligence solutions should be based on practicality. They must first be configured and learned, then built, run, and integrated with the original system.
As you can see from the EPAI just released by Inspur Information, it has the automatic generation of high-quality data, the realization of millions of Tokens, hundreds of billions of parameters, efficient fine-tuning of large-scale models in the field, professional knowledge-driven, three types of (calling) usage methods, and diverse support Features such as multi-mode can perfectly meet the needs of software companies and solve implementation problems such as complex application development processes, high thresholds, difficulty in multi-mode adaptation, and high costs.
Ronglian Technology: Scientific research is a race against time
In this era of rapid development, Ronglian Technology, which is deeply involved in the medical field, has already introduced AI technology and achieved scenario-based construction and interdisciplinary research in aspects such as cell testing.
Wang Xiangdong, chief scientist of Ronglian Technology Co., Ltd. , said: Ronglian has summarized the characteristics of this field as "two highs and two mores" through years of practical experience. "Two highs" refers to iterative concurrency with high computing power and high IO (input/output). Since this field involves high-throughput data, that is, high-throughput massive data collection of organisms, and then analysis using high-speed computing and AI technology, the requirements for computing power and efficiency are very high. "Two more" refers to the intersection of multi-business scenarios and multi-field data, which means using advanced AI technology to realize value-added utilization of data and promote business development.
Ronglian has explored a method in practice, which is to use fine learning technology to analyze user business processes and data correlations, and use AI models and machine learning to reveal the concurrency and data dependencies of business processes. Its purpose is to optimize concurrent processing, shorten execution time, optimize critical paths, and improve system efficiency and performance.
The cooperation between Ronglian and Inspur Information is based on the concept that scientific research is a race against time, and budgetary interests are an accelerator. Ronglian provides algorithm scheduling and solutions, while Inspur Information provides high-quality product platforms to jointly form standardized solutions. This cooperation model has been recognized by users in the university's AI platform, medical laboratories, and projects that stably identify massive data.
Lowering the threshold for large video models through new technologies
Colossal-AI built by Luchen Technology has as many as 38,000 stars on Github. It ranks first in the world in terms of segmented tracks and has users all over the world. Through computing power optimization, Luchen Technology has successfully helped three Fortune 500 and four Fortune 2000 customers among the top ten customers to increase the training speed by 2 to 7 times, demonstrating extraordinary strength.
You Yang, founder and chairman of Luchen Technology, said that we focus on vertical models or vertical industries that require the highest computing power, currently mainly in the field of video generation. Due to the huge amount of video data, its computing power requirements are far greater than those of language processing. In order to solve this problem, Luchen Technology launched Open-Sora, which allows users to quickly fine-tune and generate their own large video models at a low cost, such as only $10,000. Luchen cooperates with partners such as Inspur Information in this regard to jointly lower the threshold for large video models in key areas.
Build an open and professional ecosystem
Wang Xiaobo, chief operating officer and founding partner of Xianyuan Technology, believes that for many application scenarios, large models have no boundaries and require an open ecosystem. Only when more professional partners join in and work together can the entire ecosystem prosper.
Regarding the ideas for AI development, there are two main directions. One is to follow OpenAI's footsteps and follow the path it has taken. This approach is relatively low-risk because there is already a successful precedent. However, this may also bring about "winner takes all" problems.
Another way of thinking is to maximize the value of large models by improving efficiency or changing models in the current industrial format. This is a process of "get it first and meet it later", which means that when using large models to reconstruct the production process, the models are continuously optimized through the implementation of services, forming a data flywheel effect. This approach is more complex and requires not only modeling skills but also an in-depth understanding of the industry.
Xianyuan Technology is currently adopting the second strategy. They have launched the "Pin Shang Big Model", which is a large language model that focuses on applications in vertical fields. The product merchant model is directly oriented to the B-end market, such as hot marketing products and marketing brains, helping companies optimize copywriting planning, material generation and delivery management, and directly solve customer effectiveness problems. This strategy emphasizes the ability to leverage AI models in specific industries to provide direct value to enterprises through in-depth industry knowledge and model technology.
When it comes to the cooperation between Xianyuan Technology and Yuannao Ecology, Wang Xiaobo has high hopes. He expressed his hope to work with Inspur Information to liberate AI productivity and help customers change the future.
Liu Jun said in the summit dialogue that we have built the only ecosystem in the industry that can realize AI server distribution, AI scheduling platform distribution and channels. The ecological partners of Inspur Information Yuan Nao have shown a strong desire to learn and grow. By copying and implementing joint solutions, the strength and potential of the ecological partners have been fully demonstrated. In the era of large AI models, practice is the only criterion for testing truth. "What you learn on paper is only shallow, but you must do it in practice." Through the practice of the technical support department on the EPAI platform, Inspur Information successfully created a large-scale model tool: Bidding Parameter Tendency Analysis, and in the actual application process, Demonstrated great ability.
The EPAI platform is an excellent set of tools for enterprises that can quickly help partners improve their capabilities and thereby promote the development of the entire AI ecosystem.
More than 1,300 years ago, Master Xuanzang's "Open Source Exchange" established a monument for the development of Buddhism. Today, IT companies that are in the accelerated development stage are also embracing AI with full enthusiasm, and the tools they have are Yuannao Ecosystem, EPAI, AI universal servers, distributed all-flash storage, and super AI Ethernet switches. An era of prosperity is beginning!
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