Devoxx Greece 2024 Unleashing the GenAI magic: How we built a chatbot for traders with Generative AI

Learn how to build a chatbot for traders using Generative AI, applying Azure OpenAI and Golang, with semantic search, NLP, and ML to generate human-like responses and provide personalized insights.

Key takeaways

GenAI is a type of generative AI that can produce new content and ideas.
To build a chatbot for traders, the speaker chose GenAI due to its ability to understand and generate human language.
The chatbot uses semantic search to retrieve relevant news and analysis from XM’s research portal.
The speaker used Azure OpenAI and Golang to build the chatbot.
The chatbot uses a combination of natural language processing (NLP) and machine learning (ML) to generate responses to user questions.
The speaker used RAG (Retrieval-Augmented Generation) to retrieve relevant information and generate responses.
The chatbot can be trained to produce specific answers based on the user’s question and context.
The speaker used a cron job to update the vector database every 24 hours to ensure freshness.
The chatbot uses a combination of LLM (Large Language Model) and GPT (Generative Pre-trained Transformer) to generate responses.
The speaker used Azure OpenAI’s GPT-4 model to generate responses.
The chatbot can be used to answer user questions in real-time, such as the current price of a specific instrument.
The speaker used a system message to provide context to the user’s question and to generate responses.
The chatbot uses a combination of natural language processing (NLP) and machine learning (ML) to understand and generate human language.
The speaker used Go concurrency to handle multiple requests simultaneously.
The chatbot can be used to provide personalized advice to traders based on their individual needs and preferences.
The speaker used a combination of NLP and ML to analyze user behavior and provide personalized advice.
The chatbot can be used to analyze user data and provide insights to traders.
The speaker used a combination of NLP and ML to analyze user data and provide insights to traders.
The chatbot can be used to generate reports and analysis for traders.
The speaker used a combination of NLP and ML to generate reports and analysis for traders.
The chatbot can be used to provide real-time data and analysis to traders.
The speaker used a combination of NLP and ML to provide real-time data and analysis to traders.

Devoxx Greece 2024 Unleashing the GenAI magic: How we built a chatbot for traders with Generative AI

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