number nice but limit

Posted on by lechuck park

This concept emphasizes the balance between numerical analysis and human intuition. Numbers are efficient tools for decision-making but have limitations, as they cannot solve everything. It highlights the importance of adhering to principles and goals when using data. Areas beyond numerical solutions allow for creativity and human values to drive progress, advocating for an integrated approach to decision-making.

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.

RON ( Routed Optical Networking )

Posted on by lechuck park

From Claude with some prompting
This image provides an overview of Routed Optical Networking (RON), which is a networking technology that combines IP routing and MPLS with wavelength multiplexing to enable very long distance data transmission.

The key features highlighted in the image are:

  1. Network simplification: RON reduces the complex hierarchy of routers and transmission equipment traditionally used in optical networks.
  2. Cost-effectiveness: RON eliminates the need for separate transmission equipment, reducing hardware and maintenance costs.
  3. Reduced latency: Data is processed within a single device, rather than going through multiple devices, reducing latency.
  4. Operational efficiency: Routing and transport functions are consolidated, allowing the network to be managed from a single management platform.

The image also shows the main components of a RON system, including IP routing + MPLS, wavelength multiplexing, L3 layer, physical layer, router, and DWDM (Dense Wavelength Division Multiplexing). It also lists some specific technologies used, such as IP over Dense, Wavelength Division Multiplexing (Juniper) and Photonic Service Engine (Nokia).

Overall, this diagram illustrates how RON simplifies optical networking by combining multiple networking functions into a more efficient and cost-effective architecture.Copy

WUE

Posted on by lechuck park

From Claude with some prompting
The image provides information about Water Usage Effectiveness (WUE), which is a metric used to measure the water efficiency of data centers. Here’s a breakdown of the key points:

    1. WUE Components:
      • Water Usage: Includes partial, IT equipment cooling, data center building operations, and indirect water usage.
      • IT Power: Consists of UPS (Uninterruptible Power Supply) and PDU (Power Distribution Unit).
      • One of these two components – IT Power or Water Usage – is selected to be used in the WUE calculation.
    2. WUE Levels:
      • Inefficient Level: > 2.0 L/kWh
      • Industry Standard: 1-2 L/kWh
      • Optimal Target: ≤ 0.5 L/kWh
    3. Recommended Practices:
      • Water Reuse: Recycle wastewater from the data center for cooling purposes after treatment.
      • Adopting Air Cooling: Use external air instead of water for cooling systems.
      • Closed-Loop Systems: Implement systems that minimize water loss through evaporation.
      • Strategic Location: Build data centers in regions with abundant water resources or cooler climates to reduce cooling demand.

    The key update here is that the WUE calculation can use either the IT Power component or the Water Usage component, but not both simultaneously. Please let me know if I can clarify or expand on any part of this explanation.

    PUE 1 2 3

    Posted on by lechuck park

    From Claude with some prompting
    detailed explanation of the PUE levels :

    1. Level 1 (Basic Measurement):
    • Simple power meters are used to measure the total energy consumption of the entire data center.
    • Measurements are done periodically or manually, which is low-cost but has lower precision.
    • This level only provides visibility into the overall power usage of the data center.
    1. Level 2 (Intermediate Measurement):
    • Power consumption of individual IT equipment, cooling systems, and other subsystems is measured separately.
    • Automated software is used to collect more detailed data, providing moderate cost and mid-level precision.
    • This allows identifying the power usage breakdown across different subsystems.
    1. Level 3 (Advanced Measurement):
    • Real-time monitoring and in-depth data analysis provide deep insights, such as power usage patterns and predictive analytics.
    • Additional data points like power losses and environmental monitoring are collected.
    • The high-precision data enables advanced optimization of the data center’s energy efficiency.

    The key differences between the levels are in terms of cost, precision, and the scope of data collected. Organizations can choose the appropriate PUE measurement level based on their operational goals and budget.

    Getting digital “1” from real world

    Posted on by lechuck park

    Bringing a digital “1” from the real world is far from simple.

    1. The need for complete control over “1”
      If a specific analog value is converted into a digital “1,” it must be clearly defined and controlled, as analog values are always subject to change. Determining the exact boundary of what qualifies as “1” is critical.
    2. Influence of external factors
      The analog world is full of external factors, such as temperature and humidity, which can affect digital values. Maintaining “1” consistently as desired in such an environment is a challenging task.
    3. Clear definition of “1”
      The value represented as “1” in digital form must have a clear definition from a human perspective. It should be universally understandable and explainable as “1.”
    4. Risks in AI environments
      In the realm of AI, where vast amounts of data are processed into complex outputs, even a single incorrect “1” can have significant and potentially dangerous consequences.

    Ensuring and maintaining a digital “1” involves numerous challenges and complexities.


    with ChatGPT