好的，根据您提供的信息，我将为您构建一篇题为《算力筑基、AI‍ 启智，共迎数智化新纪元》的主旨发言稿，并融入李自学的观点。

尊敬的各位来宾，各位朋友：

大家上午好！

非常荣幸能在此与大家齐聚一堂，共同探讨数智化时代的未来发展。今天，我将以“算力筑基、AI 启智，共迎数智化新纪元”为主题，分享一些思考和展望。

当前，我们正处在一个激动人心的时代，网络、算力、终端、智能加速融合，推动着ICT产业向泛在智能发展。数智化浪潮席卷全球，深刻地改变着我们的生产方式、生活方式和社会治理方式。

站在这个数智化进程的新起点，我认为我们需要重点关注以下三个关键课题：

第一，算力不足的新挑战。

数智化转型离不开强大的算力支撑。无论是人工智能的训练和推理，还是大数据分析和云计算，都需要海量的算力资源。然而，随着AI应用的爆发式增长，算力需求呈现指数级上升趋势。如何突破算力瓶颈，构建高效、可靠、可持续的算力基础设施，是摆在我们面前的一项重要挑战。

第二，绿色节能的新进阶。

在追求算力提升的同时，我们必须高度重视绿色节能。传统的算力基础设施能耗巨大，对环境造成了不小的压力。因此，我们需要积极探索绿色算力技术，例如液冷散热、节能芯片、智能调度等，实现算力与环境的和谐发展。

第三，AI应用的新爆发。

人工智能正在加速渗透到各个领域，催生出无数创新应用。从智能制造到智慧医疗，从自动驾驶到金融科技，AI正在深刻地改变着我们的生活和工作。如何抓住AI应用爆发的机遇，推动AI技术与各行各业的深度融合，是我们需要重点关注的方向。

中兴通讯在AI算力领域的创新实践与深度思考

作为一家全球领先的ICT解决方案提供商，中兴通讯始终致力于在AI算力领域进行创新和探索。我们深知，算力是AI发展的基石，因此我们不断加大在芯片、服务器、数据中心等领域的研发投入，力求为客户提供更高效、更可靠、更绿色的算力解决方案。

在芯片方面，我们积极研发AI加速芯片，提升算力密度和能效比。
在服务器方面，我们推出了一系列高性能AI服务器，满足不同场景下的算力需求。
* 在数据中心方面，我们采用先进的液冷技术和智能调度算法，降低能耗，提升效率。

同时，我们也积极与各行各业的合作伙伴开展合作，共同探索AI在各个领域的应用场景，推动AI技术的普及和发展。

展望未来

数智化时代充满机遇，也充满挑战。让我们携手并进，以算力为基石，以AI为引擎，共同迎接数智化新纪元的到来！

谢谢大家！

Computing Power as foundation, AI as Engine: Welcoming the New Era of Digital Intelligence

As we stand at the cusp⁣ of a digital revolution, the convergence of networks, computing power, terminals, and intelligence is rapidly transforming the ⁤ICT industry towards widespread intelligent evolution.This Q&A article delves into the critical role of computing power and AI in shaping the era of digital intelligence.

What are the Key Challenges in the Age of Digitalization?

The digitalization⁢ boom ⁢brings exciting opportunities but also considerable challenges. Some critical issues that need focus are:

Computing Power Bottleneck: Addressing the exponentially growing⁢ demand for⁣ computing resources due to the surge in AI applications.

Green and Sustainable Energy: ⁤Balancing the increase of⁢ computing capabilities with environmental responsibilities.

AI Application Expansion: Exploring and promoting⁣ the integration of⁢ AI technology across various industries.

Why is Computing Power Considered the Cornerstone of AI ⁢Development?

Computing power provides the essential support for AI training, inference, big data analytics, and cloud computing. The vast amount of data processing and complex algorithms that AI relies on require robust⁢ and scalable computing resources. Without ⁣sufficient computing power, AI development ‍and deployment would be severely limited.

How Can the Computing Power Bottleneck Be Overcome?

Overcoming the computing power bottleneck requires a multifaceted approach:

Investing in ⁣R&D: Continuous investment in research and development ⁣to enhance chips, servers, and data centers.

High-Efficiency Infrastructure: Building efficient and ⁤reliable computing infrastructure.

Technological Innovation: innovative technologies, such as liquid cooling and intelligent ⁤scheduling algorithms.

What is Green ‍Computing⁢ and Why is it Crucial?

Green computing refers to the practice of using computing resources in an environmentally responsible manner. Traditional computing infrastructures consume significant energy, posing⁤ environmental challenges. Green computing is crucial ⁤for achieving‍ harmony between computing power⁣ and environmental sustainability.

How Can Green Computing Technologies Help?

green computing technologies offer several‍ benefits:

Liquid Cooling: Efficiently dissipates heat, reducing energy consumption.

Energy-Efficient Chips: Reduces power consumption while maintaining high performance.

Intelligent Scheduling:‍ Dynamically allocates resources to minimize energy waste.

What ⁣are the Emerging Applications of AI Across Various Industries?

AI is ‍rapidly permeating various sectors, ‍creating innovative⁢ applications such as:

Intelligent Manufacturing: Enhancing‍ production processes through automation and optimization.

Smart Healthcare: Improving diagnostics,treatment,and patient ⁢care.

Autonomous Driving: Revolutionizing transportation with self-driving vehicles.

FinTech: Transforming financial services with AI-driven‍ solutions.

How Can businesses Leverage ⁢the Explosive Growth‍ of AI Applications?

To harness the opportunities presented by the AI⁢ boom, businesses should:

Promote⁢ Deep Integration: Integrate‍ AI⁤ technologies into ‍their operations and services.

Foster⁤ Collaboration: ⁤Partner with ⁤industry⁤ experts to drive AI innovation.

Focus on Key Areas: Prioritize areas that offer the most significant potential for AI applications.

What is ZXCT’s⁢ approach to innovation in the AI computing power field?

ZXCT is dedicated to⁤ driving innovation and exploration in the AI computing power domain. Recognizing computing power as the cornerstone of AI development, ZXCT continuously increases R&D investment in chips, servers, and data centers to provide customers with more efficient, reliable, and greener computing solutions.

How is ZXCT contributing to the AI computing power field?

ZXCT is actively contributing in several key areas:

Chip Development: Developing AI‍ acceleration chips to boost computing density and energy efficiency.

Server Solutions: Launching high-performance AI servers to ⁤meet diverse computing needs.

* Data ⁤Center Advancements: Deploying liquid cooling technology and intelligent scheduling algorithms to minimize energy consumption and enhance efficiency.

How can collaboration drive AI⁣ technology advancement and proliferation?

Collaboration with partners across industries is crucial to explore AI application scenarios and promote ⁤AI technology advancement and proliferation. By‍ working together,stakeholders can leverage their expertise ⁢and resources ⁤to unlock new opportunities and drive widespread adoption of AI.

Computing and AI: A Synergistic Partnership

| Feature ⁢ | Computing Power ⁤ ⁤ ⁣ ‍ ⁢ | artificial ⁢Intelligence ⁢(AI) ⁤ |

| :————— | :————————————————– | :————————————————– |

| Description | Infrastructure ⁤for processing data and executing tasks | Algorithms and models that mimic human intelligence |

| Key Components | Chips, servers, data centers ⁣ ‍ ⁣ ‍ | Machine learning, deep learning, neural networks |

| Role‍ in Digitalization | Foundation⁢ for supporting AI and other technologies ⁢ | Engine for driving⁢ innovation‍ and intelligent solutions |

| Challenges | Meeting growing demand, energy consumption ⁢ | Ethical considerations, data privacy ⁤ ⁢ ⁢ ‍ |

| Future Trends ⁢| Green computing, edge computing ⁣ ‍ ⁤ ⁤ ⁤ ⁣ ⁤ | AI-driven automation, personalized applications ‍|

As‍ we embrace this new digital era, leveraging computing power as the foundation ‍and AI as the engine will ⁢propel us into a smarter, more connected future.