Tag: manual

LMM Operation

Posted on by lechuck park

LLM Operations System Analysis

This diagram illustrates the architecture of an LLM Operations (LLMOps) system, demonstrating how Large Language Models are deployed and operated in industrial settings.

Key Components and Data Flow

1. Data Input Sources (3 Categories)

  • Facility: Digitized sensor data that gets detected and generates alert/event logs
  • Manual: Equipment manuals and technical documentation
  • Experience: Operational manuals including SOP/MOP/EOP (Standard/Maintenance/Emergency Operating Procedures)

2. Central Processing System

  • RAG (Retrieval-Augmented Generation): A central hub that integrates and processes all incoming data
  • Facility data is visualized through metrics and charts for monitoring purposes

3. LLM Operations

  • The central LLM synthesizes all information to provide intelligent operational support
  • Interactive interface enables user communication and queries

4. Final Output and Control

  • Dashboard for data visualization and monitoring
  • AI chatbot for real-time operational assistance
  • Operator Control: The bottom section shows checkmark (✓) and X-mark (✗) buttons along with an operator icon, indicating that final decision-making authority remains with human operators

System Characteristics

This system represents a smart factory solution that integrates AI into traditional industrial operations, providing comprehensive management from real-time data monitoring to operational manual utilization.

The key principle is that while AI provides comprehensive analysis and recommendations, the final operational decisions and approvals still rest with human operators. This is clearly represented through the operator icon and approval/rejection buttons at the bottom of the diagram.

This demonstrates a realistic and desirable AI operational model that emphasizes safety, accountability, and the importance of human judgment in unpredictable situations.

With Claude

Evolutions and THE NEXT?

Posted on by lechuck park

This illustration depicts the evolution of human-machine interaction in four stages:

  1. Manual Tools – A human uses basic tools, representing traditional manual labor.
  2. Machine Operation – A worker operates a mechanical machine, indicating the industrial age.
  3. Programmed Automation – A robotic system with a CPU chip functions automatically based on human-developed programs.
  4. AI Collaboration – An AI-powered robot with a GPU chip works interactively with a human, showcasing the era of intelligent collaboration.

This is from “https://eeumee.net/2025/05/28/machine-changes/“

Machine Changes

Posted on by lechuck park

This image titled “Machine Changes” visually illustrates the evolution of technology and machinery across different eras.

The diagram progresses from left to right with arrows showing the developmental stages:

Stage 1 (Left): Manual Labor Era

  • Tool icons (wrench, spanner)
  • Hand icon
  • Worker icon Representing basic manual work using simple tools.

Stage 2: Mechanization Era

  • Manufacturing equipment and machinery
  • Power-driven machines Depicting the industrial revolution period with mechanized production.

Stage 3 (Blue section): Automation and Computer Era

  • Power supply systems
  • CPU/processor chips
  • Computer systems
  • Programming code Representing automation through electronics and computer technology.

Stage 4 (Purple section): AI and Smart Technology Era

  • Robots
  • GPU processors
  • Artificial brain/AI
  • Interactive interfaces Representing modern smart technology integrated with artificial intelligence and robotics.

Additional Insight: The transition from the CPU era to the GPU era marks a fundamental shift in what drives technological capability. In the CPU era, program logic was the critical factor – the sophistication of algorithms and code determined system performance. However, in the GPU era, training data has become paramount – the quality, quantity, and diversity of data used to train AI models now determines the intelligence and effectiveness of these systems. This represents a shift from logic-driven computation to data-driven learning.

Overall, this infographic captures humanity’s technological evolution: Manual Labor → Mechanization → Automation → AI/Robotics, highlighting how the foundation of technological advancement has evolved from human skill to mechanical power to programmed logic to data-driven intelligence.

With Claude

Home LLM

Posted on by lechuck park

This image shows the architecture of a “Home LLM” system, illustrating an innovative change in how home appliances are used.

Key points:

  1. Evolution from Traditional Approach: While traditional electronics came as ‘product + paper manual’ packages, this new system replaces manuals with small LLM models.
  2. Home Foundation Model: Homes are equipped with a main LLM model (“Home Foundation LLM Model”) that learns from environmental data.
  3. Knowledge Exchange: Product-specific small LLM models and the home foundation model exchange data and learning outcomes with each other.
  4. User Interface: Users can easily interact through the LLM by asking questions and giving commands, making product usage much more intuitive and convenient.
  5. AI Agent Control: Additionally, AI agents automatically optimize the control of these products, increasing efficiency.

This system presents a smart home architecture that fundamentally improves the user experience of electronic products by integrating AI and LLM technologies in the home environment.

With Claude

Evolutions

Posted on by lechuck park

From Claude with some prompting
Summarize the key points from the image :

  1. Manually Control:
    • This stage involves direct human control of the system.
    • Human intervention and judgment are crucial at this stage.
  2. Data Driven:
    • This stage uses data analysis to control the system.
    • Data collection and analysis are the core elements.
  3. AI Control:
    • This stage leverages artificial intelligence technologies to control the system.
    • Technologies like machine learning and deep learning are utilized.
  4. Virtual:
    • This stage involves the implementation of systems in a virtual environment.
    • Simulation and digital twin technologies are employed.
  5. Massive Data:
    • This stage emphasizes the importance of collecting, processing, and utilizing vast amounts of data.
    • Technologies like big data and cloud computing are utilized.

Throughout this progression, there is a gradual shift towards automation and increased intelligence. The development of data and AI technologies plays a critical role, while the use of virtual environments and massive data further accelerates this technological evolution.

By Software System

Posted on by lechuck park

From Claude with some prompting
This image illustrates the improvement of work processes through a software system. It’s divided into two parts, with the left side showing manual work and the right side depicting work done through a software system.

Left side (Manual):

  1. Work: Represented by a wrench icon
  2. Process: Shown as a flowchart-like icon
  3. Stability and Efficiency are shown in a trade-off relationship with arrows

Right side (Software System):

  1. Automation: Depicted by a rotating gear icon
  2. Optimization: Represented by an ascending graph icon
  3. Long Jump: Shown with a clock and hourglass icon
    • Described as “Get great results over a long period of time”
  4. Both Stability and Efficiency are shown to increase with upward arrows

The image demonstrates that implementing a software system can simultaneously improve stability and efficiency, and through automation and optimization, achieve significant long-term results.

This diagram effectively contrasts the limitations of manual processes with the benefits of implementing a software system for work processes.