AI and ML for Software Engineers: Foundational Insights

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

Session Knowledge Graphs

Verifiable and Navigable LLMs with Knowledge Graphs

Monday Nov 18 / 10:35AM PST

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.

Speaker image - Leann Chen

Leann Chen

AI Developer Advocate @Diffbot, Creator of AI and Knowledge Graph Content on YouTube, Passionate About Knowledge Graphs & Generative AI

Session AI/ML

No More Spray and Pray— Let's Talk About LLM Evaluations

Monday Nov 18 / 11:45AM PST

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.

Speaker image - Apoorva Joshi

Apoorva Joshi

Senior AI Developer Advocate @MongoDB, 6 Years of Experience as a Data Scientist in Cybersecurity, Active Member of Girls Who Code, Women in Cybersecurity (WiCyS) and AnitaB.org

Session AI/ML

Recommender and Search Ranking Systems in Large Scale Real World Applications

Monday Nov 18 / 01:35PM PST

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.

Speaker image - Moumita Bhattacharya

Moumita Bhattacharya

Senior Research Scientist @Netflix, Previously @Etsy, Specialized in Machine Learning, Deep Learning, Big Data, Scala, Tensorflow, and Python

Session AI/ML

Why Most Machine Learning Projects Fail to Reach Production and How to Beat the Odds

Monday Nov 18 / 02:45PM PST

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.

Speaker image - Wenjie Zi

Wenjie Zi

Senior Machine Learning Engineer and Tech Lead @Grammarly, Specializing in Natural Language Processing, 10+ Years of Industrial Experience in Artificial Intelligence Applications

Session

Unconference: AI and ML for Software Engineers

Monday Nov 18 / 03:55PM PST

Session AI/ML

Reinforcement Learning for User Retention in Large-Scale Recommendation Systems

Monday Nov 18 / 05:05PM PST

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.

Speaker image - Saurabh Gupta

Saurabh Gupta

Senior Engineering Leader @Meta, Veteran in the Video Recommendations Domain, Helping Scale Video Consumption

Speaker image - Gaurav Chakravorty

Gaurav Chakravorty

Uber TL @Meta, Previously Worked on Facebook Video Recommendations and Instagram Friending and Growth

Track Host

Susan Shu Chang

Principal Data Scientist @Elastic, Author of "Machine Learning Interviews"

Susan Shu Chang is a principal data scientist at Elastic, which powers search around the world. Previously, she built machine learning at scale in the fintech, social, and telecom industries. She is the author of Machine Learning Interviews, published by O’Reilly.

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