Beyond data

Posted on by lechuck park

From DALL-E with some prompting
This image depicts the process of overcoming the constraints of traditional programming based on expected data through big data and deep learning. Starting on the left, binary digits labeled as “Data” are processed through a “Filtered” stage to become the necessary “Expected Data.” The box labeled “Constraints” in the center represents the limitations that can occur in programming. These constraints suggest barriers that can be overcome with big data processing and deep learning technologies. On the right, there’s a section transitioning from “Codes” to “Errors,” which signifies possible errors during the coding process. However, the text “Fixed Code for fixed data type” reflects that program code is pre-established for expected data types and does not transcend the boundaries of this data, thereby limiting its potential. The phrase “beyond the limits of data!!” at the bottom expresses the ambition of future programming to surpass the limitations of data processing by utilizing big data and deep learning.

NTP

Posted on by lechuck park

From DALL-E with some prompting
The image appears to be a visual explanation of the Network Time Protocol (NTP). At the top, there’s a title, “Network Time Protocol,” and below it, there are icons arranged along a line that seems to represent servers, energy symbols, a thermometer, a surveillance camera, and storage devices. These icons are connected by arrows, indicating the flow of synchronization signals for time.

Below these icons, there are two messages. The first message says, “Sync Time of data from all connected Machine,” suggesting the synchronization of time across data from all connected devices. The second message reads, “sequence of events and causal relationship,” referring to the order of events and their causality. Underneath this message, icons representing the universe, Earth, a forest, and a group of people are displayed, which likely denote the concept of “Universal Time.”

Overall, the image emphasizes the importance of using Network Time Protocol to synchronize time across various devices and systems, accurately recording the sequence and causality of events, and maintaining consistent universal time globally. There’s an email address displayed in the top right corner of the image, but personal identity information cannot be shared.

Non-Uniform Memory Access

Posted on by lechuck park

From DALL-E with some prompting
The image depicts the NUMA (Non-Uniform Memory Access) architecture in computer systems. Key elements include:

  1. Operating System: Manages and controls processes running on the CPU.
  2. CPU: Central Processing Units where computing tasks are executed.
  3. NUMA Nodes: Guide CPUs to use the nearest memory, with each NUMA node having memory areas closer to specific CPUs.
  4. Memory Access Paths: “Short Path” indicates a fast and low-energy memory access that is closer, while “Long Path” represents a slower and more energy-consuming memory access that is farther away.

The structure illustrates that memory access times in a NUMA system are not uniform across all memory, suggesting that memory access optimization can enhance overall system performance.


Requires for DL

Posted on by lechuck park

From DALL-E with some prompting
The image outlines the importance of data in the era of deep learning (DL). It starts with “Data,” representing various sources and types, which feeds into “Deep Learning,” depicted by a neural network diagram. The process leads to “Result,” symbolized by charts and graphs indicating the output or findings. The central message, “Data determines the results,” stresses that the quality of data significantly impacts the outcome of deep learning processes. Below, “Data Verification” suggests the need for ensuring data accuracy, which ties into the cycle of “UPDATE” and “Analysis,” highlighting an iterative process to refine and improve deep learning applications. The phrase “What to deal with DL” hints at the challenges and considerations in managing and utilizing deep learning effectively.

Overall IP Network

Posted on by lechuck park

From DALL-E with some prompting
The image is a diagram explaining the overall structure and data flow of an IP network.

Overall IP network: The entire structure of an IP network
Ethernet In the LAN: Ethernet used within the Local Area Network (LAN)
Identification in the internet: Identifying devices on the internet
OSPF short path with IP addresses: Open Shortest Path First (OSPF) routing protocol finds the shortest path using IP addresses
Addressing/Routing to the peer: Assigning addresses and routing to peer devices
BGP to get/share IP (other & me): Border Gateway Protocol (BGP) is used for obtaining and sharing IP addresses between others and oneself
Service Connection: Establishing a service connection
IP address ↔ Domain address: The relationship between IP addresses and domain addresses
DNS Easy to keep an internet address by Domain name: Domain Name System (DNS) makes it easy to maintain an internet address by using domain names
On TCP/UDP: Operating on TCP (Transmission Control Protocol) and UDP (User Datagram Protocol)
The diagram illustrates how data moves within a network. For instance, when a user accesses web services using the HTTP protocol, the DNS translates domain names into IP addresses, and then a service connection is established using the IP address over TCP/UDP protocols. Routing protocols such as OSPF and BGP are used to find the optimal path for data transmission through internal networks and the wider internet, respectively.


Unexplainable

Posted on by lechuck park

From DALL-E with some prompting
The image intends to explain two critical perspectives of AI/ML. First, it illustrates that while traditionally digitalized data was defined by rules, AI/ML enables us to judge human ‘feelings’ as data based on a more extensive dataset. Second, AI/ML allows for the prediction of the future using data; however, some parts of these significant advancements remain unexplainable and difficult for humans to comprehend fully. This interpretation suggests that while AI aims to quantify and use non-visible elements like emotions for predictions through data standardization and optimized processing, there are aspects that cannot be fully articulated or understood.

Data Standardization

Posted on by lechuck park

From DALL-E with some prompting
The image emphasizes the importance of data quality in the digital transformation of large-scale operations. By securing “Data Quality” through data standardization, optimized operations based on verified data enable reliable decision-making, monitoring, and optimization. AI-enhanced analysis and optimization accelerate business transformation, drive data-led innovation, and achieve sustainable operation and customer satisfaction.

  1. Data Standardization: Emphasizes the importance of “Data Quality,” indicating that high-quality, standardized data is foundational.
  2. Operation based on verified data/system: Shows the use of verified data to ensure reliable decision-making, monitoring, and optimization, leading to sustainable operations, business intelligence, and customer satisfaction.
  3. Accelerating (AI) digital business transformation: Describes how optimized and customized processing, along with an AI data analysis platform, can accelerate digital transformation. This leads to work automation, user customization, resource optimization, data-driven innovation, AI predictions and analytics, and expanding standardization.

The overall message suggests that standardizing data quality is crucial for building AI systems that can drive digital transformation and improve business operations and customer satisfaction.