John's AI blog

This is a post on getting PrivateGPT to work. 1. Install git repo Firstly let's assume you have already downloaded and installed PrivateGPT in your local git repository. If that means nothing to you, open your terminal (Linux) and type: mkdir git cd git git clone https://github.com/imartinez/privateGPT 2. Make sure python and libraries are working Mostly if you install the components it just works, however Ubuntu 22 comes with a version of g++ and friends that it doesn't like. So you have to use Python 3.10 specifically and then run these commands: cd git/privateGPT sudo apt-get install python3.10 # please only use this version pip install 'pygpt4all==v1.0.1' --force-reinstall sudo apt install libxcb-cursor0 sudo apt-get install python3-dev python3.10 -m pip install --upgrade pip sudo apt install build-essential python3.10 -m pip install hnswlib python3.10 -m pip install chromadb then python3.10 -m pip install chroma-migrate chroma-migrate python3.10 -m pip install -r r

This post will discuss installing GPT4ALL from Nomic.io. It worked reasonably easily. I found it easier to install the app than the code. 1. Install Ubuntu linux version 22 (Jammy Jellyfish).  a. Go to  https://ubuntu.com/download   b. Get the iso file c. Copy it to a flash disk using Etcher ( https://etcher.io )  d. Insert flash disk, reboot, hit f2 on the keyboard; enter BIOS and tell your PC to boot off the flash disk. Take it from there.   Step 2. Install gpt4all from github: mkdir git mkdir gpt4all cd gpt4all git clone https://github.com/ParisNeo/Gpt4All-webui git clone https://github.com/nomic-ai/gpt4all Step 3. Do this step pip install 'pygpt4all==v1.0.1' --force-reinstall sudo apt install libxcb-cursor0 Step 4. Install dev tools and pip sudo apt-get install python3-dev python3.10 -m pip install --upgrade pip sudo apt install build-essential cd Gpt4All-webui python3.10 -m pip install -r requirements.txt Step 5. Install hnswlib and chromadb For some reason these do not se

In this post I will basically mention two LLMs that I am going to install and thereafter comment on them. Most AI apps seem to use python to run. So once you have installed  1. Install Ubuntu linux version 22 (Jammy Jellyfish).  a. Go to https://ubuntu.com/download   b. Get the iso file c. Copy it to a flash disk using Etcher ( https://etcher.io )  d. Insert flash disk, reboot, hit f2 on the keyboard; enter BIOS and tell your PC to boot off the flash disk. Take it from there.   e. Install PHP 3.10 sudo apt-get install python3.10  2. Install either or both of GPT4ALL or privateGPT. GPT4ALL :  https://github.com/nomic-ai/gpt4all PrivateGPT :  https://github.com/imartinez/privateGPT For example mkdir git cd git git clone https://github.com/imartinez/privateGPT git clone https://github.com/nomic-ai/gpt4all 3. Once those are downloaded ... cd git/privateGPT  or cd git/gpt4all then pip install 'pygpt4all==v1.0.1' --force-reinstall sudo apt install libxcb-cursor0 python3.10 -m pip ins

 So I decided to test ChatGPT to see if it lived up to the hype. Yes it does. However it seems limited to about 8000 chars input. So you can't give it wikipedia and ask for a summary. But it's really impressive. I asked it to summarise 4 pages of an article on conspiracy theories. Then I addressed it in Afrikaans and German. No problems. Even random "politeness" things we do in speaking to a human, it gives appropriate responses to, even though they do not contain significant propositional content. I am impressed. See screenshots below.

  This is the first of two posts on Generative AI. Late last year (November), OpenAI released ChatGPT to the public. However, it took a few months for the internet at large to catch on and realise the potential of this new tool. The trend started to take off in December, and by February everyone was talking about it. Well, what is ChatGPT? ChatGPT is an LLM, or Large Language Model, released by the company OpenAI, founded in 2015. A language model is a program that has been trained on a huge amount of text data, like books, articles, and websites. It learns patterns and relationships between words, so it can predict what words or phrases are likely to come next in a sentence. We see an example of this in predictive text in cellular telephone chat applications. The "large" part means that the model has been trained on a massive amount of data, which helps it become even better at understanding and generating human-like text. It's like having read millions of books and arti

  This is the second of two posts on Generative AI. Late last year (November), OpenAI released ChatGPT to the public. However, it took a few months for the internet at large to catch on and realise the potential of this new tool. The trend started to take off in December, and by February everyone was talking about it. ChatGPT is an example of a "Generative AI". To recapitulate, let's see what this means. For convenience, let's call AIs that are not generative, "regular" AIs. Regular or "Narrow" AI  (Artificial Intelligence): Regular AI, often referred to as "narrow" or "specific" AI, focuses on building systems that can perform specific tasks or solve specific problems. These AI systems are designed to operate within predefined boundaries and excel at specialised tasks. For example, a regular AI could be created to classify images, play chess, or process natural language. Another example is the AI that chooses your words in pred