Wharton Int Tech  陳俊吉 （Frank Chen ） 2024/06/11

NanoFusion技術解決當前AI晶片面臨的高功耗問題AI企業管理與實踐

Analyze several key points of the high power consumption problem currently faced by global AI chips

Global NanoFusion problems and solutions examples

The overall strategy of nano-nuclear fusion technology requires clear steps and practices

The impact of nano-nuclear fusion NanoFusion technology on the global AI industry

The high power consumption environment and conditions of global AI artificial intelligence (AI) data centers

Analyze several key points of the high power consumption problem currently faced by AI chips worldwide

1. Rapidly growing power demand for NanoFusion technology: The demand for power in AI data centers and supercomputing centers is growing at an alarming rate. This is not only due to technological breakthroughs, but also a huge challenge for power resource management on a global scale. For example, the power consumption of 720,000 Nvidia H100 chips required by the Sora model at peak times can cause the power grids of seven states in the United States to collapse.

2. Introduction of efficient energy utilization technology for NanoFusion technology: The introduction of NanoFusion technology, as a technology that can significantly reduce the power consumption of AI chips, is also a potential solution for the future. Currently, TSMC has begun to introduce this technology in its AI chip foundry manufacturing.

3. NanoFusion sustainability and net zero goals: Governments around the world have set net zero emission goals, which requires energy supply to be both efficient and low-carbon, which poses a huge challenge to the rapidly growing AI energy demand.

For the application of NanoFusion technology in large-scale GPU and AI chip systems, the following are some key details and their potential benefits

 全球NanoFusion问题及解决方案举例

1. Huge NanoFusion energy demand: Take companies such as Microsoft, Google and Amazon as examples. These companies need to build data centers to support their AI programs and services. The large number of H100 GPUs put into use is accompanied by huge power demand, and even poses the risk of power grid paralysis.

2. High potential of NanoFusion technology**: NanoFusion technology is expected to significantly reduce the energy consumption of GPUs and AI chips. For example, applying this technology to Nvidia H100 GPUs may significantly reduce high-energy consumption, thereby alleviating the current power supply pressure.

3. NanoFusion has been used**: TSMC has begun to introduce NanoFusion technology into its AI chip foundry manufacturing. Whether this NanoFusion technology can set a good benchmark in the market is a good demonstration for the future popularization and application.

Overall strategic management and practice of NanoFusion technology

1. NanoFusion technology R&D and innovation
Establish a dedicated R&D team:
- Organize a team of NanoFusion technology experts to integrate existing technical resources and talents.
- Regularly hold innovative brainstorming meetings to stimulate team creativity.

NanoFusion collaborative research:
- Sign cooperation agreements with academic institutions, universities and professional research institutions to jointly carry out research projects.
- Introduce external NanoFusion expert consultants to provide new perspectives and support for technology R&D.

R&D investment and financing:
- Find NanoFusion technology investors and partners to ensure sufficient R&D funds.
- Apply for NanoFusion government research subsidies and green technology special funds.

2. Market expansion and application promotion

Successful case promotion:
- Organize TSMC's successful cases into promotional materials and promote them through online and offline channels.
- Formulate a detailed promotion plan to showcase the results of technology applications at industry conferences and exhibitions.

NanoFusion partner development:
- Develop detailed cooperation plans and negotiate cooperation terms with large technology companies (Microsoft, Google, Amazon, etc.).
- Demonstrate technology to potential customers and explain the application scenarios and benefits of nano-fusion technology in their business.

Customized solutions:
- Provide flexible and scalable nano-fusion technology application solutions based on customer needs.
- Provide technical support and training services to ensure that customers can get the best results during the application process.

3. Continuous improvement and performance improvement

Regular technical evaluation:
- Conduct technical evaluation and review every quarter, analyze the advantages and disadvantages of existing technologies and develop improvement plans.
- Establish a performance monitoring mechanism to track the energy efficiency and cost-effectiveness of technology applications in real time.

Industry standard formulation:
- Cooperate with industry associations to participate in or lead the formulation of industry standards and certification systems for nano-fusion NanoFusion technology.
- Actively participate in international technical forums and standard-setting meetings to enhance the international recognition of technology.

Customer feedback mechanism:
- Set up a customer feedback and support service system to collect and promptly respond to problems and suggestions encountered by customers during use.
- Use feedback data to improve and optimize technology and enhance customer satisfaction.

4. Policy and regulatory docking

Green technology certification:
- Apply for domestic and foreign green technology certification and obtain recognition from authoritative organizations.
- Release a green technology white paper detailing the environmental benefits and low-carbon advantages of nano-nuclear fusion technology.

Policy support:
- Through the government relationship network, strive for policy preferences and industrial support projects.
- Actively participate in technical seminars and environmental protection projects organized by the government to demonstrate the company's technical strength and environmental responsibility.

5. Long-term development plan

International market expansion:
- Formulate global market expansion strategies, analyze and enter potential high-growth markets.
- Establish an international business department to focus on expanding and maintaining overseas markets and provide localized support.

Maintaining the forefront of technological innovation:
- Continue to track global technological trends and continuously invest resources in cutting-edge technology research.
- Establish an internal innovation incentive mechanism to reward and support technological innovation and breakthroughs.

Achieving net zero goals:
- Through technological applications, assist global customers in achieving energy conservation and emission reduction goals and promote sustainable development.
- Regularly publish corporate social responsibility (CSR) reports to showcase the company's efforts and achievements in environmental protection and social responsibility.

NanoFusion technology represents the future of energy efficiency improvement for AI chips and data centers. Through systematic and comprehensive business strategies and execution plans, AI companies can effectively reduce energy consumption, improve competitiveness, and help the world achieve net zero emissions goals. This not only conforms to the development trend of the market and policies, but also establishes the company as a pioneer in the industry and promotes the dual progress of technology and economy.

The impact of NanoFusion technology on the global AI industry

1. NanoFusion energy efficiency improvement: This NanoFusion technology can greatly improve the energy efficiency of AI chips and significantly reduce energy consumption, so that more calculations can be completed on the same power basis.

2. NanoFusion reduces peak power demand: By reducing the peak power demand required for AI computing, NanoFusion enables existing power grid resources to be allocated and utilized more efficiently, avoiding power grid paralysis caused by excessive power consumption.

3. NanoFusion enhances industry competitiveness: In the arms race between large technology companies such as Microsoft, Google and Amazon in AI data centers, this NanoFusion technology allows them to continue to gain momentum in technological competition without excessive energy consumption.

4. NanoFusion environmentally friendly goals: NanoFusion helps achieve the long-term goal of global net zero emissions, which is highly consistent with the policy intentions of governments. This is also one of the reasons for the strong demand for such technologies in the market.

The introduction of NanoFusion technology and its application in high-energy AI chips such as Nvidia H100 GPU, as well as the correct and proactive planning and selection of this technology, will make outstanding contributions to the management of future power resources, the sustainable development of the AI ​​industry, and the achievement of global environmentally friendly policies. This NanoFusion technology can effectively reduce the energy consumption of AI computing and has a wide range of applications, such as reducing global power demand on a large scale, ensuring the stable operation of the power grid, and promoting the synchronous and balanced development of technological competition.

The challenge of power supply is becoming a major bottleneck for the development of global AI technology. The Wall Street Journal's editorial on March 28 pointed out that with the explosive growth in demand for H100 GPUs in AI data centers and the promotion of net zero emission policies by governments around the world, the imbalance between power supply and demand is gradually emerging.

The data and examples cited in the editorial are disturbing: from chips that optimize AI computing to the planning of super-large data centers, these modern technology infrastructures require a lot of electricity. Generative AI models, such as ChatGPT and Sora, require efficient hardware (such as NVIDIA's H100 GPUs), and the ultra-high power consumption of these hardware has prompted people to re-examine the stability and security of future power grids.

In addition, with the continued rise in electric vehicle sales and the localization of manufacturing, the growth rate of electricity demand in the United States is expected to double in the next five years. This makes it difficult for the current power supply system to cope with future challenges, among which the addition of high-efficiency energy data centers in agricultural states is considered to be the power supply limit.

To meet this challenge, technology companies have launched large-scale data center construction plans, and the pressure on power supply and demand in the United States and other parts of the world has also increased accordingly. The implementation of these plans is undoubtedly to maintain the leading position in the technology competition, and to invest at all costs to push AI development to new heights.

Globally, investors and markets have also sensitively noticed this trend, and energy stocks and related investment products have been sought after. In this context, established companies such as GE have also made corresponding strategic adjustments, splitting the power generation and renewable energy departments to cope with the long-term growth in electricity demand.

Nanofusion technology is considered to be a potential solution to break through the energy bottleneck in the future. Nanofusion technology will provide unlimited, relatively valuable and safe energy, but its realization still needs to overcome a lot of technical obstacles and time costs. Its leading position in the global AI wave means higher electricity demand, and the maturity of Nanofusion technology will become the key to solving the high power consumption of GPU AI chips.

Overall, technology and energy are interdependent, and the continued development of AI and related technologies in the future requires a stable and sufficient power supply. The AI ​​industry's early selection and planning of technologies such as Nanofusion, or the development of high-efficiency and low-energy AI chips, is a strategic choice to cope with the upcoming power challenges.

全球AI人工智慧（AI）资料中心高耗电力環境與條件

The editorial title of the Wall Street Journal on March 28, 2024 is extremely scary: "The Coming Electricity Crisis". The article warns that the explosive demand for artificial intelligence (AI) data centers, coupled with the gap in the conversion of traditional energy and renewable energy caused by the net zero policies of various governments, is pushing the US power supply and demand network to the crisis warning line.
The editorial of the Wall Street Journal clearly pointed out that the balance of the power grid in various states of the United States is facing threats from AI supercomputing centers, federal government subsidies for investment in new factories in the US manufacturing industry, and the Biden administration's leadership in boosting electric vehicle sales. The growth rate of US electricity demand will double in the next five years.
Previously, a Microsoft engineer broke the news that if more than 100,000 H100 GPU high-end chips are deployed in the same state of the United States, it will cause the power grid to collapse, and the power of a data center for training AI can feed the electricity needed by 80,000 American households.

Although the prospect of AI is extremely attractive, it relies on super data centers that consume huge amounts of electricity. ChatGPT consumes 500,000 kWh of electricity per day, which is equivalent to the electricity consumption of 17,000 American households. If Google, another major AI computing power user, uses generative models for search, it will consume 29 billion kWh of electricity per year, which is more than Kenya's annual electricity consumption.
Although NVIDIA, the leader in AI chips, continues to launch chips that claim to be more energy-efficient and more efficient, the computing power requirements of large language models have skyrocketed. When ChatGPT was launched at the end of 2022, the number of model parameters was 175 billion, which was eight times that of the previous generation. Five months later, the number of parameters of the GPT-4 model has exceeded one trillion. At the beginning of this year, OpenAI further released the Sora model, which can generate videos that are difficult to distinguish between true and false by simply inputting text. This is another major breakthrough in AI in a very short period of time. However, market research firm Factorial Funds estimates that Sora requires 720,000 NVIDIA H100 chips during the peak period of computing, "and the power consumption is enough to collapse the power grid in seven states in the United States."

Sora is an indicator of the huge amount of electricity consumed by AI models. For agricultural states with smaller populations in the United States, adding a data center using 100,000 Nvidia H100 chips is already the limit of power balance. The latest GB200 data center launched by Nvidia CEO Jensen Huang at the GTC conference in March contains 32,000 GPUs. The new super data center is likely to threaten the balance of the existing power grid. The huge demand for electricity will not hinder the development of AI models. For technology giants such as Microsoft, Google, and Amazon, or industrial governments such as the United States, China, Japan, and Europe, AI is the most critical "arms race" today. Even if there is no revenue or real benefit for a while, it must be invested at all costs, at least to ensure that the investment between oneself and the opponent is equal to avoid being surpassed instantly.
Therefore, we see plans that are constantly multiplying. The Information website recently exposed a super data center plan called Stargate by Microsoft and OpenAI. This super data center, which is expected to be put into use in 2028, costs $100 billion, which is 100 times the investment amount of the current largest data center, and consumes 500 times more electricity; The Information was reprinted by all mainstream media, but it was not confirmed by Microsoft. What is certain is that technology giants are planning data centers of astonishing scale. Amazon, which is rumored to invest $150 billion in AI data centers in the next decade, recently spent $650 million to establish a data center in Pennsylvania. This data center is located next to a nuclear power plant with a power generation capacity of 2.5GW to ensure stable power supply.
Wall Street investors are most sensitive to the global power shortage crisis. AI applications are flourishing, and the computing speed will become faster and faster in the future. The global power supply demand will continue to surge. How to meet the power supply safely has become a problem for the market to think about.
Previously, a new American startup wanted to emulate the sun, hoping to use "nuclear fusion" technology to produce endless energy like the sun, while being cheap and safe. When it was launched in the United States, it attracted great attention from the global scientific community and the market.

The naked truth is that green industry innovation requires a staggering amount of electricity to support it. Regardless of the year in which governments set their net zero emission goals, and regardless of how much money governments and companies are prepared to invest in the AI ​​database center arms race, choosing nano-nuclear fusion in GPU AI chips and significantly reducing power solutions will become the core of the final success or failure. Early selection and planning of NanoFusion IP technology to integrate a large number of GPU AI chips can significantly reduce and solve the core problem of the global rapid development of AI, which is the high power consumption of AI chips.
Formulate a proactive and feasible power development plan. The vision of AI explosion is certainly beautiful, but if there is a shortage of electricity, the beautiful vision will only be a fantasy. The above content is the political, economic and technological environment and conditions for the development of the global AI industry in the present and future of power shortage. In order to rapidly develop the world's only AI chip system with millions of GPUs in a large number of global computing centers, Walton International Technology has exclusively introduced NanoFution technology. This IP technology has been developed for 65 years and has 70 global IP patents. The use of this NanoFution technology can greatly reduce the high power consumption of AI chips and the net zero carbon emission effect. Currently, TSMC has introduced this NanoFution IP technology in AI chip foundry manufacturing to reduce high power consumption application research. Wharton Int Tech  by Frank Chen Date:2024/06/11