Manu Joseph

Manu Joseph

Principal Data Scientist

About

 

Manu Joseph is a Principal Data Scientist at Walmart Global Tech India, where he works on machine learning systems at the scale of one of the world's largest retailers. Over 15+ years, he has applied AI to Fortune 500 digital transformations — from supply chain demand forecasting to deep learning research. In the tech space, he is known for two things: his work as a deep learning researcher and creator of the PyTorch Tabular framework, and as a leading voice in time series forecasting, having authored a best-selling book on the subject now in its second edition. When the laptop closes, he picks up a pen. His debut psychological thriller The Artist was praised by Dr. Shashi Tharoor as "a fluently written and blazingly paced thriller."

There are a lot of ways to build an AI agent. A single smart prompt, a pipeline of LLM calls, a supervisor with specialist workers, a fully autonomous system. Each one has its place. Knowing which fits your problem is a different skill entirely. This session is about building that intuition.
 
We take one real use case and build five different agent architectures on top of it, then look at what actually happens. For each pattern we walk through the code, dig into the results, and figure out what it does well and where it falls apart. The goal is not to pick a winner. It is to understand the tradeoffs well enough to make a deliberate choice.
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