hugo bowne-anderson
Hugo Bowne-Anderson is an independent data and AI consultant with extensive experience in the tech industry. He is the host of the industry Vanishing Gradients, where he explores cutting-edge developments in data science and artificial intelligence.
As a data scientist, educator, evangelist, content marketer, and strategist, Hugo has worked with leading companies in the field. His past roles include Head of Developer Relations at Outerbounds, a company committed to building infrastructure for machine learning applications, and positions at Coiled and DataCamp, where he focused on scaling data science and online education respectively.
Hugo's teaching experience spans from institutions like Yale University and Cold Spring Harbor Laboratory to conferences such as SciPy, PyCon, and ODSC. He has also worked with organizations like Data Carpentry to promote data literacy.
His impact on data science education is significant, having developed over 30 courses on the DataCamp platform that have reached more than 3 million learners worldwide. Hugo also created and hosted the popular weekly data industry podcast DataFramed for two years.
Committed to democratizing data skills and access to data science tools, Hugo advocates for open source software both for individuals and enterprises.
Sessions
LLMs offer powerful capabilities, but deploying them effectively in production remains a challenge for conversational AI and Chatbot applications, especially when it comes to minimizing hallucinations and ensuring accurate responses. In this 90-minute hands-on tutorial, we’ll explore building conversational AI systems using CALM and Rasa. CALM (Conversational AI Language Model) combines traditional conversational AI techniques with LLMs, separating conversational ability from business logic execution to deliver reliable, cost efficient, and scalable solutions. Unlike LLMs that handle both sides of the conversation, CALM focuses on user understanding with predefined business logic. This approach not only accelerates development but also enhances cost efficiency, scalability and reliability. By focusing on predefined business logic with CALM, you’ll gain the ability to build sophisticated, scalable systems faster. You’ll also learn how to use fine-tuned, open-weight models, such as llama 8b to power your AI assistant.
Participants will learn how to use CALM for business logic and Rasa for dialogue management, with practical insights, code examples, and best practices. Materials will be provided via a GitHub repository with a GitHub Codespace for easy access and execution.