How to Set Up Your Very Own Private AI Yourself – Your Own R2D2 or CP30 Next?

This is POWERFUL Info from Network Chuck.  Sure It Will Take Some Figuring Out But if We All Work on it a Little by Little We Can Get There

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The video is about introducing a private AI model called “Private AI” and setting it up on a local computer. The host, Network Chuck, explains that Private AI is like Chat GPT, but it’s run locally on the computer and doesn’t share data with any external company.

The host then explains that AI models are pre-trained on data and can be fine-tuned for specific use cases. He shows how to download and install a pre-trained model called Llama 2, which is a large language model trained on over 2 trillion tokens of data.

The host then explains how to set up Windows Subsystem for Linux (WSL) on Windows, and how to install Ollama, a tool that allows users to run LLMs on their local computer. He also demonstrates how to run Llama 2 on his local computer and asks it questions.

The host then discusses the potential use cases for Private AI, such as fine-tuning the model with company-specific data or using it for customer support. He also mentions that VMware is enabling this technology by providing a package that includes all the necessary tools and resources for fine-tuning an LLM.

The host then explains that fine-tuning an LLM requires a lot of hardware and software resources, including GPUs, tools, and libraries. He praises VMware’s approach to making it easier for companies to fine-tune their own LLMs by providing a package that includes all the necessary tools and resources.

Finally, the host gives a peek behind the curtain at what a data scientist does when fine-tuning an LLM, and explains that the infrastructure for fine-tuning an LLM is set up using VMware’s vSphere platform

Based on the video, here are the action steps to set up a private AI:

Step 1: Download and Install WSL (Windows Subsystem for Linux)

Go to the Microsoft Store and download the Windows Subsystem for Linux
Install WSL on your Windows machine
Follow the installation instructions to set up WSL

Step 2: Install Ollama

Go to the Ollama website and download the Ollama installer
Run the installer and follow the installation instructions to install Ollama
Make sure to install Ollama on your WSL instance

Step 3: Download and Install LLM (Large Language Model)

Go to the Hugging Face website and download the LLM model (e.g. Llama 2)
Extract the downloaded model to a folder on your computer

Step 4: Set up VMware

Download and install VMware vSphere platform
Follow the installation instructions to set up vSphere
Create a new virtual machine and install a Linux distribution (e.g. Ubuntu)

Step 5: Install Required Tools and Libraries

Install required tools and libraries such as TensorFlow, PyTorch, or CUDA
Make sure to install the correct version of the tools and libraries for your LLM model

Step 6: Fine-tune the LLM Model

Use Ollama to fine-tune the LLM model with your company-specific data
Adjust hyperparameters and experiment with different fine-tuning techniques
Monitor the performance of the fine-tuned model and adjust as needed

Step 7: Run the Private AI Model

Use Ollama to run the fine-tuned LLM model on your local computer
Ask the model questions and test its performance
Integrate the private AI model with your company’s systems and applications

Note: These steps may vary depending on your specific setup and requirements. Additionally, fine-tuning an LLM requires significant computational resources and expertise, so it’s recommended to have a good understanding of AI and machine learning before attempting to set up a private AI.