πŸ“–
Wiki
CNCFSkywardAIHuggingFaceLinkedInKaggleMedium
  • Home
    • πŸš€About
  • πŸ‘©β€πŸ’»πŸ‘©Freesoftware
    • πŸ‰The GNU Hurd
      • πŸ˜„The files extension
      • πŸ“½οΈTutorial for starting
      • 🚚Continue Working for the Hurd
      • πŸš΄β€β™‚οΈcgo
        • πŸ‘―β€β™€οΈStatically VS Dynamically binding
        • 🧌Different ways in binding
        • πŸ‘¨β€πŸ’»Segfault
      • πŸ›ƒRust FFI
    • πŸ§šπŸ»β€β™‚οΈProgramming
      • πŸ“–Introduction to programming
      • πŸ“–Mutable Value Semantics
      • πŸ“–Linked List
      • πŸ“–Rust
        • πŸ“–Keyword dyn
        • πŸ“–Tonic framework
        • πŸ“–Tokio
        • πŸ“–Rust read files
  • πŸ›€οΈAI techniques
    • πŸ—„οΈframework
      • 🧷pytorch
      • πŸ““Time components
      • πŸ““burn
    • 🍑Adaptation
      • 🎁LoRA
        • ℹ️Matrix Factorization
        • πŸ“€SVD
          • ✝️Distillation of SVD
          • 🦎Eigenvalues of a covariance matrix
            • 🧧Eigenvalues
            • πŸͺCovariance Matrix
        • πŸ›«Checkpoint
      • 🎨PEFT
    • πŸ™‹β€β™‚οΈTraining
      • πŸ›»Training with QLoRA
      • 🦌Deep Speed
    • 🧠Stable Diffusion
      • πŸ€‘Stable Diffusion model
      • πŸ“ΌStable Diffusion v1 vs v2
      • πŸ€Όβ€β™€οΈThe important parameters for stunning AI image
      • ⚾Diffusion in image
      • 🚬Classifier Free Guidance
      • ⚜️Denoising strength
      • πŸ‘·Stable Diffusion workflow
      • πŸ“™LoRA(Stable Diffusion)
      • πŸ—ΊοΈDepth maps
      • πŸ“‹CLIP
      • βš•οΈEmbeddings
      • πŸ• VAE
      • πŸ’₯Conditioning
      • 🍁Diffusion sampling/samplers
      • πŸ₯ Prompt
      • πŸ˜„ControlNet
        • πŸͺ‘Settings Explained
        • 🐳ControlNet with models
    • πŸ¦™Large Language Model
      • ☺️SMID
      • πŸ‘¨β€πŸŒΎARM NEON
      • 🍊Metal
      • 🏁BLAS
      • πŸ‰ggml
      • πŸ’»llama.cpp
      • 🎞️Measuring model quality
      • πŸ₯žType for NNC
      • πŸ₯žToken
      • πŸ€Όβ€β™‚οΈDoc Retrieval && QA with LLMs
      • Hallucination(AI)
    • 🐹diffusers
      • πŸ’ͺDeconstruct the Stable Diffusion pipeline
  • 🎹Implementing
    • πŸ‘¨β€πŸ’»diffusers
      • πŸ“–The Annotated Diffusion Model
  • 🧩Trending
    • πŸ“–Trending
      • πŸ“–Vector database
      • 🍎Programming Languages
        • πŸ“–Go & Rust manage their memories
        • πŸ“–Performance of Rust and Python
        • πŸ“–Rust ownership and borrowing
      • πŸ“–Neural Network
        • 🎹Sliding window/convolutional filter
      • Quantum Machine Learning
  • 🎾Courses Collection
    • πŸ“–Courses Collection
      • πŸ“šAcademic In IT
        • πŸ“Reflective Writing
      • πŸ“–UCB
        • πŸ“–CS 61A
          • πŸ“–Computer Science
          • πŸ“–Scheme
          • πŸ“–Python
          • πŸ“–Data Abstraction
          • πŸ“–Object-Oriented Programming
          • πŸ“–Interpreters
          • πŸ“–Streams
      • 🍎MIT Algorithm Courses
        • 0️MIT 18.01
          • 0️Limits and continuity
          • 1️Derivatives
          • 3️Integrals
        • 1️MIT 6.042J
          • πŸ”’Number Theory
          • πŸ“ŠGraph Theory
            • 🌴Graph and Trees
            • 🌲Shortest Paths and Minimum Spanning Trees
        • 2️MIT 6.006
          • Intro and asymptotic notation
          • Sorting and Trees
            • Sorting
            • Trees
          • Hashing
          • Graphs
          • Shortest Paths
          • Dynamic Programming
          • Advanced
        • 3️MIT 6.046J
          • Divide and conquer
          • Dynamic programming
          • Greedy algorithms
          • Graph algorithms
Powered by GitBook
On this page

Was this helpful?

Edit on GitHub
  1. Home

About

NextThe GNU Hurd

Last updated 3 months ago

Was this helpful?

I’m Bowen Li and my code name is Aisuko. It looks great.

I have been doing it well until now. I am an excellent human being, today I am and, in the future, even if I bring into submission. But I will never be frustrated.

I’d like to do something interesting, like explore the GNU Hurd project. It’s cool.

And I’d like to explore the structure of the entire world. So, I’m not interested in the server, but the infrastructure needs to be updated.

I join the in 2020, I am the community manager until now. People there are so well. Now it is in the CNCF sandbox. I am happy with this.

I join the in 2021, I’d like to research more about the because the HA or distribution servers work on a monolithic kernel and are not stable (It’s a joke). And there are that I need to learn and research.

In 2023, I jump into the which is focused on running the AI model in consumer level hardware. It is so super cool and the binding technique between two different languages is useful. And the project is super cool.

In the beginning of 2024, I was a casual researcher at . I founded an open source community with a group of passionate students from RMIT University, along with some former colleagues. Inspired by , our goal is to provide a free, truly open-source RAG framework and data analysis solutions, enabling anyone to democratize and run AI on consumer-grade hardware.

By the end of 2024, I graduated from RMIT with a . I joined the and continued working on this topic. Additionally, I am working on founding a company focused on AI services and an education platform for businesses.

I’m a Sky photographer on and all the photos are free to download.

Maintainer , GPG Key: C52F AB76 4ECD 339F F038 1836 1F47 7E40 A672 B460 | |

fsf member
πŸš€
Meshery organization
GNU Hurd
microkernel
lots of things
go-Skynet organization
LocalAI
RMIT
SkywardAI
LocalAI
Master of Information Technology with Distinction
RMIT Race Hub
Flickr
CNCF
Savannah
gnu.org
meshery.io
skywardai
Page cover image