생성형 AI에 의한 하드웨어 및 애플리케이션의 새로운 기회 : 1조 5,000억 달러 시장의 장악

AI research emerged in the 1940s and made breakthroughs in areas like expert systems, natural language processing, and machine learning from the 1960s to the 1980s. Essential milestones include the use of expert systems in business during the 1980s, IBM's Deep Blue defeating world chess champion Garry Kasparov in 1997, and AlphaGo defeating world Go champion Lee Sedol in 2016. With AI technology rapidly advancing, its applications in various fields are expected to become more profound and widespread and bring revolutionary changes in healthcare, education, transportation and manufacturing.

In November 2022, OpenAI launched ChatGPT, a large-scale language model that quickly garnered global attention. ChatGPT can produce human-like text and excels in dialogue, writing, translation, and more, marking a significant milestone in AI development. As a conversational system based on machine learning, ChatGPT comprehends and generates natural language, enabling meaningful interactions with users and advancing AI in language understanding and generation.

This article delves into the current state of generative AI, its potential applications, and its challenges, examining case studies across various domains to assess its capabilities and limitations. DIGITIMES Research predicts that led by Amazon, Google, Meta, Microsoft, NVIDIA, OpenAI and others, the global generative AI market will grow rapidly, reaching US$ 40 billion in 2024 and growing to US$ 1.5 trillion US in 2030. The recent growth mainly comes from the AI hardware market, from cloud servers and AI computing chips to various AI terminal devices. This report will analyze the development trends and key layouts of each hardware market; as for the long-term growth momentum, it will come from the implementation of generative AI in various application fields and will describe the future business opportunity value from the development and possibilities of application scenarios.

Table of Contents

Chapter 1: A Chronology of Generative AI

• 1.1. The rise of generative AI
• 1.2. Definition of Generative AI
• 1.3. Development history of generative AI algorithms
• 1.4. The Value and Challenges of Generative AI
• 1.5. New trends in generative AI

Chapter 2: The development of computing power of generative AI

• 2.1. Cloud Servers
• 2.2. Enterprise Servers
• 2.3. PCs, Notebooks and Handsets
• 2.4. Others: IoT devices
• 2.5. The future trend of cloud and edge computing in generative AI

Chapter 3: Examples of generative AI applications

• 3.1. Smart Transportation
• 3.2. Smart Retail
• 3.3. Smart Healthcare
• 3.4. Smart Manufacturing
• 3.5. Smart Home

Conclusion