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Csaba Toth - senior software engineer, remote team lead, public speaker, tech meetup enthusiast
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Generative AI and other Hackathon projects and wins
Eco Trivia Quiz Application (with chat agent on the side): Eco Trivia is a web / mobile game about climate change. Apathy and information overload prevent people getting involved with climate action. I gathered Google Developer Student Club (GDSC) Fresno members Zheng Wei Ng and Ran Hao Wong to create a quiz game about sustainability. We were exploring how far we can go with low-code / no-code tools:
Eco Oracle Chat Agent: A no-code / low-code agent specialized in Sustainable Development Goals via RAG (Retrieval Augmented Generation). It uses the Google Cloud Platforms Agent Builder offerings which are Generative AI successor to DialogFlow CX conversational agents, and it offers no code "playbooks" (or behavior scripts), managed RAG, function calls and powered by Google Gemini under the hood.
LLM Knowledge agent with RAG Fusion: Using Cohere chat, document guided and web connector guided agents, Weaviate services and LangChain, I implemented a RAG Fusion solution with a Streamlit UI. I also experimented with Cohere's Command R large language model.
QBRAG (QnA Boosted RAG) Knowledge LLM agent on Vectara platform: A company's knowledge bases often times don't answer the wide variety of questions a user could come up with. A Customer Support system ideally could answer specific (but wide variety) questions about the company's systems and knowledge (example: "How can I enter Cash Flow in ThruThink?"). But sometimes the user asks generic questions, such as "What is Cash Flow?" which could be sourced from the mind of a giant LLM model and / or the internet. My submission is essentially synthetic data enrichment of the knowledge base by reusing generated questions and answers. To help and boost the performance by leveraging Question and Answer generation techniques - normally used for fine tuning but in this case - for knowledge base augmentation / indexing enrichment. The generated questions could support specific user queries potentially better matching than a "non focused" indexed generic knowledge base.
Myself: back-end, GCP functions, team organization
Winner of the Multi Modal hackathon by Weaviate at AIx Innovation Summit and ODSC West 2023 data science conference
Knowledge LLM agent with RAG utilizing low-code / no-code cnvrg LLMaaS platform: At the time of the project (Intel Innovation Bridge hackathon @ Intel Innovation 2023) cnvrg's LLMaaS (LLM as a service) by Intel was in alpha stage. The LLMaaS service provided a no code environment to fine tune and customize agent solutions with ease. Due to the development stage of this novel product I could use two toy datasets to fine tune an LLM, and I applied RAG (Retrieval Augmented Generation) with the help of a PineCone vector database, using ChatGPT's embeddings API. I also got familiar with GRadio and similar front-ends. Due to confidentiality the materials I can share are limited.
Winner of the Intel Innovation Bridge hackathon's LLM category @ Intel Innovation 2023
Gen AI Rock Star Challenge: Song "Xeon Fury" of the band "Nerdcore Annihilation". Participants were tasked with generating a poster or album cover for an imaginary rock band, along with generating the lyrics of an imaginary song for said band. We were provided with a Gaudi2 accelerated deep learning AWS EC2 instance equipped with a Runway 1.5 text-to-image stable diffusion model, and also a Vicuna 7-based LLM model. We increased the steps of the stable diffusion model from 10 to 50 to conclude with much better images. The EC2 box was inaccessible for a while, and in the meantime, we experimented with some other LLM models for lyrics, such as ChatGPT and PaLM, as well as the officially accessible Runway Gen 1. We used the LLM to get the band name (Nerdcore Annihilation) and the song name (Xeon Fury) as well. The stable diffusion model couldn't feature text on the image precisely, so we used Runway's web-accessible edit feature to add an old school Intel Inside logo and modify the center image of the front cover. The back cover was purely generated by the Gaudi2 instance (notice how the wafer is a pastry wafer and not a chip wafer). We adjusted the prompt many times. I used my geek knowledge to provide desired keywords for the lyrics: MMX, AVX, AVX2, AVX512, AMX, Xeon Phi, Gaudi 2, Optimum Habana, 288-core Xeon (freshly announced). We mixed the best parts of the various tries together to create a hilarious final set of lyrics.
Winner of Intel GenAI Rock Star Challenge @ Intel Innovation 2023
Multi Modal Generative AI Travel blog helper app: An app indexes pictures taken during travel trips or everyday experiences. With the power of multi modal embedding models and vector databases it is able to categorize them, describe them and help document the experiences. The back-end uses Chooch for image to text tasks and Google Cloud Platform for everything else such as asset management, search, summarization and RAG. The front-end is written in Kotlin and uses Compose UI by Kevin Moore GDE. The project management, iteration on ideation, user interviews, feasibility, presentation of our work was done by Yiru and Coco He.