AI Revolution: Semiconductor Industry and Future Developments

The AI revolution is causing stock fluctuations stemming from policy uncertainty and liquidity reduction, impacting semiconductor companies.

### The Current and Future of the AI Revolution: Challenges and Opportunities
* 📉 Recent stock market fluctuations in the semiconductor industry were triggered by **policy uncertainty, excessive tech investments, and liquidity reduction**, affecting AI semiconductor companies like NVIDIA.
* 🎮 The AI revolution, which started suddenly with OpenAI's ChatGPT in 2022, created a **shortage of AI semiconductors**, benefiting NVIDIA due to its **strong software ecosystem**.
* 💻 NVIDIA's dominance in AI semiconductors may be challenged as big tech companies like Microsoft and Google start designing their own chips to **reduce costs for inference services**.
* 📈 NVIDIA's CEO expects the AI semiconductor market to **grow 15-20 times** in the next 10 years, aiming to maintain a **60% market share**.
* 🔋 The memory semiconductor market is shifting towards specialized, made-to-order solutions like **HBM**, with **SK Hynix leading** and **Samsung playing catch-up**.
* 🇰🇷 South Korea's semiconductor industry, traditionally strong in memory, is facing challenges in catching up with TSMC in foundry services due to **organizational culture and IP limitations**.
* 🧠 The AI value chain includes foundation AI models (L&M models), specialized models, and application AI models, with global big tech companies investing heavily to **catch up with OpenAI's ChatGPT**.
* 🌐 Sovereign AI, the concept of developing AI based on a country's own language, is seen as **crucial for national security and economic competitiveness**.

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손에잡히는경제

- The fluctuation in semiconductor stock prices is influenced by Trump's statements, excessive investment in big tech, and reduced liquidity from carry trade funds, causing policy uncertainty and fluctuating stock prices.

- The AI revolution's concentration in semiconductor manufacturing is due to the sudden and urgent need for AI semiconductors triggered by OpenAI, leading to supply shortages and significant price movements, with NVIDIA dominating the market due to its high-performance chips and software ecosystem.

- NVIDIA's dominance is attributed to its free CUDA software, accumulation of source code, open source utilization, and its crucial role in providing computing power for quickly creating AI models, ultimately shaping the AI ecosystem based on their hardware.

The Evolution of AI Technology and the Changing Landscape of AI Semiconductors

The speed of technological advancement stagnated for 40 years before the development of AI, which was driven by increased computing power and data accumulation, leading to the rise of machine learning and deep learning.

NVIDIA currently dominates the AI semiconductor market with its chips for data training, but there is a growing focus on cost reduction for inference, leading big tech companies to design their own custom chips.

Jensen Huang, the CEO of NVIDIA, acknowledges that the company's market share is expected to decrease, as other big tech companies like Microsoft and Google are shifting towards using their own custom-designed AI chips.

However, with the projected significant growth of the AI semiconductor market, there is still room for expansion and profitability.

The evolving landscape of AI technology and the increasing investment from big tech companies indicate that the AI market is still in its early stages, with the potential for future profitability similar to the establishment of monopolies in the internet and mobile

Big tech's heavy investment in AI is driven by the goal of achieving Artificial General Intelligence (AGI), which is seen as the next crucial infrastructure for modern civilization.

The ongoing supply shortage in AI technology is still a significant concern, impacting stock prices and global economic growth.

The memory semiconductor market is expected to undergo a transformation in the context of artificial intelligence, moving away from its traditional stronghold position.

The Evolution of Memory Semiconductors and the HBM Market

Memory semiconductors have shifted from being general-purpose to being customized, driven by increasing demand for specialized systems.

This has led to significant changes in the market, with HBM (High Bandwidth Memory) becoming a hot concept in the industry.

SK Hynix has taken the lead in HBM development, while Samsung Electronics initially struggled to catch up, experiencing delays in mass production.

However, with a recent reorganization and successful testing of HBM3, they are expected to start delivering supplies to NVIDIA soon, with SK Hynix also performing well in production.

The Role of NVIDIA and Samsung in the AI Semiconductor Industry

NVIDIA plays a crucial role in the AI semiconductor industry as a key player in the market with larger sales than Samsung.

Samsung's struggle to catch up with TSMC is due to a widening technology gap, organizational culture, and a lack of focus on the service mindset in the foundry business.

The global competition in the AI industry is focused on developing advanced AI models, with smaller companies contributing to the development of specialized models for various applications.

The Significance of L&M Models in Natural Language Processing

L&M models serve as the engine for AI to process natural language, eliminating the need for manual programming.

Big tech companies are striving to create their own L&M models, raising concerns about potential monopolies.

The development of an L&M model based on the Korean language is challenging, with big tech companies like Google and Naver leading the way.

These companies are making significant investments in computing power and big data to improve AI performance, highlighting the growing importance of L&M models in natural language processing.

The Global Impact of the AI Power Struggle

The AI power struggle will result in a significant gap between the adopters and non-adopters of the technology, creating disparities on a global scale.

As the competition resolves, only a few countries will have the capability to develop AI models and manufacture chips, leading to a concentration of power.

The rising costs of AI development, particularly in data gathering and computing power, are creating barriers for smaller companies to emerge, unlike previous technology revolutions.

AI's expansion into image and video generation is disrupting companies like Adobe and those in the VFX and advertising industries.

The AI boom is making it challenging for small companies to compete in the market.

The increasing demand for AI semiconductors, data centers, and telecommunications infrastructure is creating investment opportunities in these areas for the next few years.