Machine Learning (ML) and AI play a key role in modern software, and powers much of what we see and interact with. Each talk in this track covers a foundational area of ML, along with real-life use cases. Attendees will learn how ML works behind-the-scenes with software systems, as well as about tools, platforms, and algorithms that make up the discipline.
From this track
Recommender and Search Ranking Systems in Large Scale Real World Applications
Recommendation and search systems are two of the key applications of machine learning models in industry. Current state of the art approaches have evolved from tree based ensembles models to large deep learning models within the last few years.
Moumita Bhattacharya
Senior Research Scientist @Netflix
Verifiable and Navigable LLMs with Knowledge Graphs
Graphs, especially knowledge graphs, are powerful tools for structuring data into interconnected networks. The structured format of knowledge graphs enhances the performance of LLM-based systems by improving information retrieval and ensuring the use of reliable sources.
Leann Chen
AI Developer Advocate @Diffbot
No More Spray and Pray— Let's Talk About LLM Evals
The pace of development in AI in the past year or so has been dizzying, to say the least, with new models and techniques emerging weekly. Yet, amidst the hype, a sobering reality emerges: much of these advancements lack robust empirical evidence.
Apoorva Joshi
AI Developer Advocate @MongoDB
