Tag Archives: RAG
The Helsinki Python meetup on Tuesday 27th May was hosted by MariaDB Foundation with nearly 100 participants of the 2600+ members of the Helsinki python meetup community.
In addition to being a successful opportunity to mingle and learn python together, we finally got to announce the winners of the MariaDB AI RAG Hackathon! (winners posing in the feature photo of the blog)
Presentations: AI and MariaDB
We welcomed participants of the meetup with a brief introduction to what MariaDB is as a software, and the sponsoring parties: MariaDB Foundation, Open Ocean Capital and verkkokauppa.com.
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Continue reading “Helsinki Python meetup with AI RAG and MariaDB Foundation”
On Monday we had our final submission day for the MariaDB AI RAG Hackathon. We got several high quality replies in both tracks: integration and innovation.
The quality was so high that we are keen to replicate this hackathon in other locations and are currently looking for cooperation partners. We are truly grateful to the Helsinki Python meetup group without which this would not have been possible. They have a great community, organise excellent events, and played a key role in making the hackathon happen.
We are now reviewing the submissions together with the Helsinki Python meetup group.
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Continue reading “Impressive Submissions at the MariaDB AI RAG Hackathon”
We had the pleasure on Friday to take individual calls with everybody who submitted to the ideation phase of the MariaDB AI RAG hackathon.
The ideation phase deadline passed last week, and we are happy to share that we received several promising submissions for both the innovation track and the integration track. Innovation involves applications using MariaDB Vector, like RAG, and integration being enabling MariaDB Vector in an existing framework.
Participants range from individual contributors to even a corporate team. Some already have some experience with AI, and some are newcomers to RAG.
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The ideation phase of the MariaDB AI RAG Hackathon is nearing its deadline on Monday (by end of March).
We have several cool submissions so far. One is about combining the Knowledge Graph and LLMs, using MariaDB Vector Nearest Neighbour Search. Another one is about an “advanced context diff”, identifying the differences between two text corpuses based not on their literal wording, but on their content.
All of the current submissions are in the Innovation track. We would particularly like submissions in the Integration track – to add MariaDB to frameworks such as these, or other apps.
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One week left to join the AI RAG Hackathon with MariaDB Vector and Python!
Winners get to demo at the Helsinki Python meetup in May, receive merit and publicity from MariaDB Foundation and Open Ocean Capital, and prizes from Finnish verkkokauppa.com.
To participate, gather a team (1-5 people) and submit an idea by the end of March for one of the two tracks. You then have until May 5th to develop the idea before the meetup 27th May.
- Integration track: Enable MariaDB Vector in an existing open source project or AI-framework.
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The day has come that you have been waiting for since the ChatGPT hype began: You can now build creative AI apps using your own data in MariaDB Server! By creating embeddings of your own data and storing them in your own MariaDB Server, you can develop RAG solutions where LLMs can efficiently execute prompts based on your own specific data as context.
Why RAG?
Retrieval-Augmented Generation (RAG) creates more accurate, fact-based GenAI answers based on data of your own choice, such as your own manuals, articles or other text corpses. RAG answers are more accurate and fact-based than general Large Language Models (LLM) without having to train or fine-tune a model.
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Continue reading “Try RAG with MariaDB Vector on your own MariaDB data!”