Name: May 7th In-Person Meetup - Seattle Data, AI & Security
Start: 2024-05-07T17:00:00-07:00
End: 2024-05-07T20:00:00-07:00
Location: Microsoft Reactor Redmond

**Join In-person Data and AI Event**
Connect with over 25+ enterprise and startup communities!
**Date & Time: May 7\, 2024 \| 5 PM \- 8 PM**
**Venue: Microsoft Reactor Redmond, USA**
**Free Food, Drinks, & T-Shirts**
Increase Your Net Worth through Your Network

**Schedule:**
**5:00 PM - 5:30 PM:** 30 Mins - Food & Networking
**5:30 PM - 6:20 PM:** 50 Mins - Beyond the Prompt: Powering Up with Long Context LLMs by Eden Cohen - Gen AI Product Lead, Google
**6:20 PM - 7:10 PM:** 50 Mins - Harnessing Large Language Models in Enterprise Data Engineering: An On-Call Revolution by Mitesh Mangaonkar - Tech Lead Data Engineer, Airbnb
**7:10 PM - 8:00 PM:** 50 Mins - SSOT: Fuel your organization with the right data by Sundar Subramanyam - Lead Data Engineer, DocuSign

**Dive Into Data & AI**
**Don’t Miss Out – Join Us for an Unforgettable Experience!**
👉 **Secure Your Spot Now!**
You may meet your next Business Collaborator, Client, Employer, Employee or Friend!

Seattle Data, AI & Security

Seattle Data AI Security

DataTorrent

Technology

Open Source

New Technology

Cloud Computing

Hadoop

Big Data

Data Visualization

Predictive Analytics

Internet of Things (IOT)

Apache Spark

Artificial Intelligence

Computer Vision

Natural Language Processing

Amazon Web Services

Microsoft Azure

Neural Networks

Padma A

**Eden Cohen: Beyond the Prompt: Powering Up with Long Context LLM**

Ready to take Gen AI to the next level? In this session we'll unpack long-context LLMs and the multimodal experiences they now make possible. Learn what sets them apart, optimal use cases, the long-context vs. RAG debate, and how to get hands-on. Live examples will illustrate the power of these models, sparking your next innovative applications

**Mitesh Mangaonka: Harnessing Large Language Models in Enterprise Data Engineering: An On-Call Revolution**

Data engineering teams encounter challenges like data quality issues and pipeline failures, especially in enterprise environments. Addressing this, our approach combines the linguistic prowess of models like GPT-4 with data engineering tasks. We autonomously identify and rectify data quality issues, transform anomaly detection paradigms, and automate recovery tasks. Our methodology achieves reduced resolution times, fine-tuned anomaly detectors and minimized downtime. Empirical evidence showcases enhanced metrics such as reduced MTTR and fewer false positives, advocating a future where AI plays a pivotal role in on-call data engineering.

**Sundar Subramanyam: SSOT: Fuel your organization with the right data**

Be it a basic reporting or powering your ML/AI model, SSOT ensures that consumers have access to high-quality, consistent data, enabling them to deliver accurate, reliable, and scalable results in various applications and domains. Let’s see why it is important to have SSOT & how can we create one.

Eden Cohen | Mitesh Mangaonkar | Sundar Subramanyam 

May 7th In-Person  Meetup - Seattle Data, AI & Security

Microsoft Reactor Redmond

COVID-19 safety measures

The event host is instituting the above safety measures for this event. Meetup is not responsible for ensuring, and will not independently verify, that these precautions are followed.

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May 7th In-Person Meetup - Seattle Data, AI & Security

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