GPU works for

From ChatGPT with some prompting
The image is a schematic representation of GPU applications across three domains, emphasizing the GPU’s strength in parallel processing:

Image Processing: GPUs are employed to perform parallel updates on image data, which is often in matrix form, according to graphical instructions, enabling rapid rendering and display of images.

Blockchain Processing: For blockchain, GPUs accelerate the calculation of new transaction hashes and the summing of existing block hashes. This is crucial in the race of mining, where the goal is to compute new block hashes as efficiently as possible.

Deep Learning Processing: In deep learning, GPUs are used for their ability to process multidimensional data, like tensors, in parallel. This speeds up the complex computations required for neural network training and inference.

A common thread across these applications is the GPU’s ability to handle multidimensional data structures—matrices and tensors—in parallel, significantly speeding up computations compared to sequential processing. This parallelism is what makes GPUs highly effective for a wide range of computationally intensive tasks.

My own AI agent

From DALL-E with some prompting
This image appears to be a conceptual diagram of an individual’s AI agent, divided into several parts:

  1. Personal Area: There’s a user icon with arrows labeled ‘Control’ and ‘Sensing All’. This suggests the user can direct the AI agent and the AI is capable of gathering comprehensive information from its environment.
  2. Micro & Macro Infinite World: This part features illustrations that seem to represent microorganisms, plants, butterflies, etc., indicating that the AI collects data from both microscopic and macroscopic environments.
  3. Personalized Resource: The icon resembling a human brain could represent personalized services or data tailored to the user.
  4. Cloud Infra: The cloud infrastructure is presumably responsible for data processing and storage.
  5. Cloud Service: Depicted as a server providing various services, connected to the cloud infrastructure.
  6. Internet Connected: A globe icon with various network points suggests that the AI agent is connected to global information and knowledge via the internet.

Overall, the diagram illustrates a personalized AI agent that collects information under the user’s control, processes it through cloud infrastructure and services, and ultimately contributes to collective intelligence through an internet connection.

Digitization

From DALL-E with some prompting
The image illustrates the concept of digitization. It shows an analog signal being converted into a digital format, represented by a sequence of binary numbers. The process emphasizes the importance of accuracy and precision in digitization, noting that even small errors in digitizing the signal can lead to significant computing errors. Therefore, maintaining high accuracy and precision is marked as important to ensure the integrity of the huge computing tasks that rely on the digitized data. 

AI with humans

From DALL-E with some prompting
This image illustrates the process of how AI and humans interact with data. Initially, data undergoes computation, followed by human-led analysis. Rules are then discovered, which inform the creation or improvement of models. These processes lead to the sharing and generation of new ideas, feeding into an acceleration of AI capabilities.

The analysis and AI-discovered rules are used to construct or enhance models, which are then verified by AI to confirm the outcomes. Ultimately, the new ideas, products, or services developed through this process are shared and disseminated across society. This entire cycle fosters rapid advancements in AI, enabling improvements in human efficiency and task execution.