In-person Meetup: Scaling Insights with GPU Acceleration & LLMs [NVIDIA, H2O.ai]

We are thrilled to announce our first in-person Meetup event in years! Mark your calendars for the QuantumBlack Southeast Asia Meetup, happening on Friday, June 9th, 2023, from 6:00 PM to 7:30 PM SGT / GMT+8, at McKinsey & Company Singapore Office.

Kindly ensure that you arrive prior to 6:00 PM and have a valid photo ID with you for building entry. When you arrive, please approach the concierge and kindly provide them with your full name (as used in registration), company affiliation, and mention that you are attending a McKinsey & Company event. This will assist in granting you access to the lift lobby.

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AGENDA (SGT, GMT+8)
5:30 PM - 6:00 PM: Arrival and Networking
6:05 PM - 6:10 PM: Welcome & Introductions
6:10 PM – 6:30 PM: "Scaling Modern Data Science on GPUs" by Dr. Deb Goswami, Big Data & Structured AI Technologist, ASEAN & ANZ, Developer Programs, NVIDIA
6:30 PM – 6:40 PM: Q&A
6:40 PM – 7:00 PM: "Unlocking Your Organization's Data with Large Language Models (LLMs)" by **Chun Ming Lee, Senior Principal Data Scientist & Kaggle Grandmaster, H2O.ai**
7:00 PM – 7:10 PM: Q&A
7:10 PM – 7:15 PM: Closing address
7:15 PM onwards: Networking with refreshment

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TOPICS:

Scaling Modern Data Science on GPUs by Dr. Deb Goswami

In any company, whether software, financial services, or retail, extracting insights from large data volumes efficiently is crucial. In this talk, we will explore how you can turbocharge your Big Data and Analytics workflows with NVIDIA RAPIDS - a suite of GPU-accelerated Machine Learning Libraries. We will see how easy it is to build and execute end-to-end GPU accelerated data science workflows using the RAPIDS accelerated data science libraries that are drop-in replacements for widely used existing Pythonic libraries (sk-learn, pandas, NetworkX etc.) Finally we will cover some best practices in rolling this out for real-world production workloads.

Unlocking Your Organization's Data with Large Language Models (LLMs) by Chun Ming Lee

The Large Language Models (LLM) space is transitioning from standalone chatbots to ecosystems of applications and plug-ins that leverage external knowledge bases. How can you leverage your organizational unstructured data with LLMs? Chun Ming will walk you through the approach of pairing LLMs with retrieval models to enable you to query your dynamic unstructured data.

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SPEAKERS:

Dr. Deb Goswami, Big Data & Structured AI Technologist, ASEAN & ANZ, Developer Programs, NVIDIA

Dr. Deb Goswami is currently responsible for growing NVIDIA’s Accelerated Data Science and Structured AI developer practice in the Asia Pacific South and ANZ Regions. With over a decade of expertise in scaling and enabling enterprise AI in the region, Dr. Deb is passionate about supporting the developer ecosystem in their AI journey.

Prior to joining NVIDIA, Dr. Deb worked on challenging AI problems across a variety of verticals in the APAC region, including Media (SPH, Head of Data), eCommerce (Traveloka, Head of AI), AdTech and Telco/Oil & Gas.

Dr. Goswami read his PhD in Face Recognition from the University of Surrey, where he also studied for his BEng (Hons) in Electronic Engineering.

**Chun Ming Lee, Kaggle Grandmaster & Senior Principal Data Scientist at H2O.ai**

Chun Ming Lee is a Senior Principal Data Scientist at H2O.ai. Chun Ming’s focus is on NLP and anything and everything to do with language and semantics. He’s worked in the investment space, with a focus on trading and has experiences both in sell and buy-side firms.

Chun Ming studied Computer Science at Carnegie Mellon University and holds an MBA from London Business School.

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Sponsors:
This event is sponsored by QuantumBlack, AI by McKinsey.

QuantumBlack is an advanced analytics firm operating at the intersection of strategy, technology and design to improve performance outcomes for organizations.

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Notice:
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