Track host
About the track
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.
The day in the host's words
Sessions in this track
Monday 18 November. 6 sessions per track, chosen and introduced by the Track Host.
10:35 Ballroom BC Session Knowledge Graphs Enhance LLMs’ Explainability and Trustworthiness With Knowledge Graphs Leann Chen AI Developer Advocate @Diffbot, Creator of AI and Knowledge Graph Content on YouTube, Passionate About Knowledge Graphs & Generative AI 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. 11:45 Ballroom BC Session Scale Out Batch Inference with Ray Cody Yu Staff Software Engineer and Tech Lead @Anyscale, Ex-Amazonian, vLLM Committer, Apache TVM PMC As AI technologies continue to evolve, the demand for processing both structured and unstructured data across diverse industries is rapidly growing. 13:35 Ballroom BC Session AI/ML Recommender and Search Ranking Systems in Large Scale Real World Applications Moumita Bhattacharya Senior Research Scientist @Netflix, Previously @Etsy, Specialized in Machine Learning, Deep Learning, Big Data, Scala, Tensorflow, and Python 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. 14:45 Ballroom BC Session AI/ML Why Most Machine Learning Projects Fail to Reach Production and How to Beat the Odds Wenjie Zi Senior Machine Learning Engineer and Tech Lead @Grammarly, Specializing in Natural Language Processing, 10+ Years of Industrial Experience in Artificial Intelligence Applications Despite the hype around AI, many ML projects fail, with only 15% of businesses' ML projects succeeding, according to McKinsey. Particularly with the significant investments in large language models and generative AI, only a small portion of companies have managed to realize their true value. 15:55 Seacliff D Unconference Unconference: AI and ML for Software Engineers 17:05 Ballroom BC Session AI/ML Reinforcement Learning for User Retention in Large-Scale Recommendation Systems Saurabh Gupta, Gaurav Chakravorty This talk explores the application of reinforcement learning (RL) in large-scale recommendation systems to optimize user retention at scale - the true north star of effective recommendation engines.
76%
senior dev or higher
1:11
speaker ratio
60+
practitioners
QCon San Francisco 2024 is a three day conference for senior software engineers, architects and team leads. An international program committee of working engineers selects every session. Patterns and practices, not products and pitches.