This illustration contrasts an old approach of endlessly adding more GPU servers, burning money for little gain, with a new era where AI-driven optimization of software, network, cooling and power delivers smarter GPUs and a much better ROI.
Next AI
Tag: infra
3 Key on the AI era
This diagram illustrates the 3 Core Technological Components of AI World and their surrounding challenges.
AI World’s 3 Core Technological Components
Central AI World Components:
- AI infra (AI Infrastructure) – The foundational technology that powers AI systems
- AI Model – Core algorithms and model technologies represented by neural networks
- AI Agent – Intelligent systems that perform actual tasks and operations
Surrounding 3 Key Challenges
1. Data – Left Area
Data management as the raw material for AI technology:
- Data: Raw data collection
- Verified: Validated and quality-controlled data
- Easy to AI: Data preprocessed and optimized for AI processing
2. Optimization – Bottom Area
Performance enhancement of AI technology:
- Optimization: System optimization
- Fit to data: Data fitting and adaptation
- Energy cost: Efficiency and resource management
3. Verification – Right Area
Ensuring reliability and trustworthiness of AI technology:
- Verification: Technology validation process
- Right?: Accuracy assessment
- Humanism: Alignment with human-centered values
This diagram demonstrates how the three core technological elements – AI Infrastructure, AI Model, and AI Agent – form the center of AI World, while interacting with the three fundamental challenges of Data, Optimization, and Verification to create a comprehensive AI ecosystem.
With Claude
New Infra Age
From Claude with some prompting
This diagram illustrates the cyclical evolution of computing infrastructure, emphasizing the re-entry into a new computing infrastructure era driven by AI technology:
- Development cycle:
- Traditional infrastructure era (Infra age) → Software era (SW Age) → New infrastructure era (New Infra age)
- Core elements of the new infrastructure era:
- AI/ML (highlighted with red circles): Processing humanity’s accumulated experiences and data
- GPU: Key computing infrastructure for AI
- Driving forces of development:
- More Users
- More Data
- These are visualized by the icons at the bottom
- Key connection points (highlighted with red circles):
- PC: Increased user base due to personal computer proliferation
- Internet: Enhanced global connectivity
- Web: Improved information accessibility
- Mobile: Anytime, anywhere access environment
- AI/ML: Processing and utilization of accumulated data
- Cyclical development:
- User increase → Data increase → Infrastructure development to process this data → Attraction of more users, creating a cyclical structure
This diagram emphasizes that as AI technology begins to comprehensively process and utilize humanity’s accumulated experiences and data, it necessitates the expansion of new GPU-centric computing infrastructure to support this. It demonstrates a cyclical structure where processing more users and data leads to further infrastructure development, which in turn enables handling even more users and data.
Simple & Complex
This image illustrates the evolution of problem-solving approaches, contrasting traditional methods with modern AI-based solutions:
‘Before’ stage:
- Starts with Simple data
- Proceeds through Research
- Find out Rules with formula
- Resolves Complex problems
This process represents the traditional approach where humans collect simple data, conduct research, and discover rules to solve complex problems.
‘Now with AI Infra’ stage:
- Begins with Simple data
- Accumulates too much Simple data
- Utilizes Computing for big data and Computing AI
- Solves Complex problems by too much simple
This new process showcases a modern approach based on AI infrastructure. It involves analyzing vast amounts of simple data using computational power to address more evolved forms of complexity.
The ‘Complex Evolution’ arrow indicates that the level of complexity we can handle is evolving due to this shift in approach.
In essence, the image conveys that while the past relied on limited data to discover simple rules for solving complexity, the present leverages AI and big data to analyze enormous amounts of simple data, enabling us to tackle more sophisticated and complex problems. This shift represents a significant evolution in our problem-solving capabilities, allowing us to address complexities that were previously beyond our reach.
New infra age
From Claude with some prompting
This image illustrates the surge in data and the advancement of AI technologies, particularly parallel processing techniques that efficiently handle massive amounts of data. As a result, there is a growing need for infrastructure technologies that can support such data processing capabilities. Technologies like big data processing, parallel processing, direct memory access, and GPU computing have evolved to meet this demand. The overall flow depicts the data explosion, the advancement of AI and parallel processing techniques, and the evolution of supporting infrastructure technologies.
Lechuck Park 