MemoryCache is an experimental AI Firefox add-on that partners with privateGPT to turn a local desktop environment into an on-device AI agent. It saves your browser history and other local files to your machine for a local AI model to ingest, augmenting responses in a built-in chat interface. The goal is to create a deeply personalized AI experience that leverages your own data for insights and learning. It's designed to be completely private and on-device, using an older, but reliable, language model.
• personalized ai experience
• uses privategpt
• on-device ai agent
• augments responses to chat interface
• ingests local files
Right now (as of December 7, 2023), MemoryCache requires a few manual steps to set up the end to end workflow. There are three components: a) a Firefox extension, b) a local instance of privateGPT, and c) a symlinked folder between privateGPT and your local Downloads folder. There is also an optional configuration that can be done to a private build of Firefox to save files to your local machine as PDF files instead of HTML files. Check out the GitHub repository for more detailed instructions. We are looking into ways to streamline the deployment of MemoryCache to require less manual configuration, but if you’re here at this stage, you’re at the very earliest stages of our explorations.
No. One of the core principles of MemoryCache is that you have full control over the system, and that it all stays on your device. If you’re a developer or someone who just likes to tinker with your computer applications, and you want to cloud-ify this, feel free! But we’re looking to stay entirely local.
MemoryCache is using an old language model ([Nomic AI’s gpt4all-j v1.3 groovy.ggml](https://huggingface.co/nomic-ai/gpt4all-j)) and primordial privateGPT because right now, this combo is the one that passes our criteria for the type of responses that it generates. This tech is almost a year old, and there have been many advancements in local AI that we’ll be integrating in over time, but we’re a small team exploring a lot of different subsets of this problem space and the quality of the insight generated is a sweet spot that we want to preserve. This is a temporary tradeoff, but we want to be careful to keep a consistent benchmark for insight generation. GPT-J was trained on the ‘Pile’ dataset, and the versions between the 1.0 release and 1.3 release also added the ShareGPT and Dolly datasettes. The Databricks Dolly dataset is licensed under the Creative Commons license with human contributions and wikipedia entries. The ShareGPT dataset is human prompts and ChatGPT output responses that were submitted by human users.
MemoryCache is ultimately leaning into the weird and creative parts of human insight. The goal with MemoryCache is to “learn what you learn”, which is why you are in control of what you want files you want to augment the application with. This can be helpful for research, brainstorming, creative writing, and synthesis of new ideas to connect seemingly unrelated topics together to find new insights and learnings from the body of knowledge that matters most to you.
No. MemoryCache is a hackathon-style project by the Mozilla Innovation Ecosystem team, not a Firefox project.While the project uses a Firefox extension as a way of collecting information, this is a set of scripts and tools to augment privateGPT, a native AI application. It’s meant to streamline the process of saving information that you might read in the browser to store it in your own personal library of information.
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