Last November ChatGPT has held its first anniversary, after having reached a user base of 180 million active users, making this the fastest adopted technology with an internet user base ever. Now we are a year in, I’d like to explore how the open-source world has caught up with ChatGPT’s success. What is the current state of affairs when comparing open source LLMs to the closed source and proprietary models from OpenAI and others? Is open-source technology able to match or surpass the technology brought by OpenAI in 2022?
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Retrieval Augmented Generation (RAG) allows for adding knowledge from external sources into a Large Language Model (LLM) prompt. In this blog post I will be using this approach for using an LLM to retrieve data from an SAP S4/HANA system and visualizing the data using Streamlit. You will learn how to build a dashboard converting natural language questions into data visualizations using only a minimal amount of code!
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With the Tour de France 2023 having started last weekend there will be lots of media coverage of the world’s toughest cycle race in the next weeks. If you are a regular viewer of these races you will probably recognize a few situations where you found it difficult to exactly determine who you are watching on the screen. In this blog post I am presenting a way to do augment the race with rider and team recognition capabilities to make it easier to detect riders and follow what is happening during the race.
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GPT-based models have several inherent problems such as correctly aggregating figures in tabular structures and getting access to corporate data in database system. I will show an approach for connecting GPT to your custom database schema using the Langchain Python package. This allows text-based queries to be executed on the custom database schema, showing impressive results in GPTs ability to formulate complex SQL queries to the database and retrieving the correct information.
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One of the major drawbacks of GPT-based models is their lack of knowledge about custom documents living in knowledge bases in large organizations. In this blog post I will demonstate a way to set up adding custom documents into the body of knowledge of GPT-based models.
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