KBVE

Machine Learning

mL/AI - The movement to emulate natural intelligence.

#software #ml #ai

ML

  • Are you curious about the latest buzzword in the tech world?
  • Have you been wondering what machine learning is?
  • Let us take you on a journey to understand the basics of this revolutionary technology and its potential to revolutionize the future.

mL (machine learning) is a subset of artificial intelligence and follows the theory of computational training, to understand core principles through computer science and statistics. These training methods can be broken down to supervised, unsupervised and reinforcement learning.

If you’re interested in learning the basics of Machine Learning, then you’ll need to have a sound understanding of Computational Theory and the Basics of Computer Science. This involves learning the fundamentals of programming languages (python), algorithms, and data structures. Knowing these topics will give you a strong foundation to build upon as you dive deeper into Machine Learning; you will also need to understand the mathematics behind Machine Learning-algorithms, such as linear algebra, statistics, calculus, and probability. Additionally, you will need to be well-versed in the different Machine Learning / ML techniques and tools, such as neural networks, decision trees, support vector machines, and deep learning. Finally, you’ll need to understand the various Machine Learning frameworks available, such as Keras, PyTorch, TensorFlow, and Scikit-Learn.

Information

This documentation is a reference guide to the vast realm of machine learning and artificial general intelligence with examples, concepts and libraries to help you get started! We want to create this whole page as a one stop shop for all your mL needs xD! Note: This is an ever growing and evolving list of all mL / ai services, concepts and ideas that can be referenced for your experiences within the field.

AI

  • Artificial intelligence is an umbrella phrase that encapsulates various fields within computer science, mathematics, philosophy and information with the goal to emulate natural intelligence display by humans and animals.

Scope

  • The dream for many programmers, scientists, engineers and humans would be to create an entity that could scale past our natural intelligence.
  • This is a task that would define the 21st century and push the upper limits on humanity, naturism and metaphysics into the next industrial intelligence revolution.

Image Models

Stable Diffusion

Stable Diffusion is a python-based latent diffusion model that performs image generation through deep learning.

  • VOID-SD

    • VOID-SD has direct API access to various forks of Stable Diffusion, including waifu-diffusion, hosted on a hybrid-cloud.

  • Waifu Diffusion

  • Stable Diffusion WebUI

QQ

  • QQ has several interesting contributions within the AI/ML open source community, we will keep notes/references on these services for educational purposes only!

  • Different Dimension Me

    • Official QQ Link for Different Dimension Me
    • Just remember that you are visiting a Chinese site that comes across very sus , please take extra precautions when utilizing any qq services.

Text Models

Text WebUI

  • An easy gradio web user interface for running text transformers and large language models like LLaMA, llama.cpp, GPT-J, OPT, and GALACTICA.
  • Official Repo

GPT

  • GPT , currently known as GPT-3, stands for Generative Pre-trained Transformer with the number representing the generation via version control and is a neural network machine learning model

  • GPT-Neo

    • Official Github Repo
      • We should note that the team, EleutherAI, are no longer maintaining the gpt-neo and their repo is currently in archive mode. However below is the gpt-neox, which is still being actively maintained as for Oct 2022.
    • The GPT-Neo may have been an extension of GPT2 but changes to the layering.

  • GPT-NeoX

  • GPT4All

    • What I enjoy about this software is that it is really easy to install and use, plus it requires very bare metal resources.
    • WebUI for GPT4All written in Flask (Python) by Nomic AI, Repo Here

LLaMa

  • LLaMa, also known as, Large Language Model Meta AI, is actively being developed by Meta / Facebook and is a state-of-the-art foundational large language model that is designed to help researchers advance their work in natural language processing (NLP).

ChatGPT

  • TLDR; ChatGPT is an extension of GPT3 / GPT3.5 and focuses on holding a natural conversation with the client / User by keeping track of the previous question(s) / responses.

ChatGPT is an artificial intelligence (AI) system developed by OpenAI that uses a text generation language model to understand and produce natural language text. Furthermore, it has been trained on a massive amount of text data from the internet and can create text that resembles how humans write and speak, based on a given input. Finally the software can answer questions, converse on a variety of topics, and generate creative writing pieces but beaware that it might provide false information. OpenAI based the ChatGPT architecture from the sibling model, InstructGPT, which is trained to follow an instruction in a prompt and provide a detailed response. ChatGPT accomplishs this by its advance machine learning engine, built using a deep learning architecture called the Text Transformer, which enables it to learn patterns in language and generate text that is coherent and human-like. ChatGPT is one of the most advanced chatbots in the world and has the potential to revolutionize the way we interact with computers and digital systems. We will be providing examples of how to use prompt engineering to obtain positive feedback results from GPT software.

  • PyChatGPT

    • Official Repo. PyChatGPT is an on-going API written in Python to help scale and integrate ChatGPT to various applications / eco-systems via TLS.

Prompt Engineering

Prompt engineering theory covers a wide range of different GPT concepts, including examples and short cuts to generate the right style of questions and content.

  • Roles

    Common role examples for text transformers:

    • Act as a javascript console
    • Act as an excel sheet
    • Act as a HR interviewer
    • Act as an advertiser
    • Act as a publisher
    • Act as a music teacher
    • Act as a relationship coach
    • Act as a World of Warcraft player and limit the response to 50 characters

    Warning : Not all text transformers will let you assign roles, as it might create a security issue / risk.

  • Chaining

    • Common Terms include: Chain-of-Thought, Chained Prompt

Content Detection

While using various text transformers

  • Writer.com

    The AI Content Detector helps detect if the content was AI generated through an unique %-score rank.

  • CopyLeaks

    Another content dection style software is offered by CopyLeaks but we have not yet tested how accurate it is.

Journal

This is a collective journal with tasks, opinions and notes. They should not be taken as valid information and should be seen as mere unaudited thoughts of a wandering collection of souls.

  • Log

    • 4/5/2023

      • Merging the notes on prompt engineering with the mL notes because I believe they would fall into the same category.
      • I will try to update the notes more often as the field keeps progressing and changing rapidly.
      • Finally I believe we could add more videos as examples.

    • 10/24/2022

      • -> October 24th, 2022 -> “Computational Learning” as well as “mL/AI” -> two important concepts.
      • We should say that ai is an umbrella phrase that includes various tools, concepts and data. If we could imagine data as crude oil then we can say models are refined oils, thus the functional aspect of refinement should be a pillar of machine training.
      • It be like taking data from our natural world, filled with its random and chaos, is collected or drilled, then processed into abstract collections of meaningful and layered information, finally forming our computational models.
      • There definitely is more to this but that should be a solid building path for where we can go.
      • The speed at which this field is growing is also remarkable, its still insane to see how my laptop can generate art from just processing my vocals as I talk.