Look Who it Was Random video

Operationalizing AI- Decoding the art of AI Alchemy - Part 1 at CYPHER 2018

331 views · Published 3 October 2018 · 26:25 · Indexed 28 September 2026

Channel: AIM Network · 2018 · Science & Technology

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By Madhusudan Shekar Principal Technical Evangelist at Amazon Internet Services , Vickye Jain Associate Principal at ZS Associates  , Abhishek Trigunait Principal and Executive Director of Software Products & Technology at ZS Associates

With the advent of citizen data-scientists, Artificial Intelligence (AI) algorithms are being applied to a very large number of problem statements to narrow down on those that really create value for organizations. Such applications begin with experimental study or proof-of-concept (POC) along the lines of what many of you may have seen on Kaggle.com and are then productionized as a part of scaling and embedding in business processes. While data scientists take the lead role in the model development phase, Machine Learning (ML) engineers take over during the productionizing / operationalization phase tackling a completely different set of problems such as ML model management, optimization and deployment, etc. In this session, we will walk you through the AI/ML process being followed within enterprises today and the differing needs of data scientists and AI/ML engineers that need to be catered for helping enterprises succeed in this space. We will also describe a reference model life cycle and discuss real life challenges, solutions and learnings from our joint implementations for clients.

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