Events

This is an event page for our Meetup community: 

What's the latest with Large Language Models (LLMs) and what does it take to start building applications with them?

Come talk to several builders, and find out how they're using LLMs in their new projects.

​In each of our stations, you can find a different engineer building an LLM-powered application.

​Come to look at their code, learn from their experience, ask questions, eat, drink and network!

Show up anytime! ​Can't wait to see you there!

Building with LLMs - Open House with AI Builders

Come meet us at Trinity Bar, by World Trade Center, at 8:30pm for the after-party!

We have two phenomenal talks to be followed by a new "office-hour" style conversation: just grab a chair at the Spotify tables and ask them anything about their work!

Talk 1: Spotify's Frictionless ML Platform

How can one build an ML platform for hundreds of users of diverse backgrounds and dozens of use cases while also delivering a frictionless developer experience?

This talk shares what Spotify's ML platform team has learned and solved over the past year particularly on the problem of enabling all ML practitioners to be able to code at the click of a button.

Learn about Spotify's new system for using SQL to generate features in near-real-time. Users provide a just SQL query, and our fully managed system applies the query to streaming data, and writes the resulting features to low-latency online storage. We'll discuss how the system works, and how this makes it easy for teams at Spotify to incorporate near-real-time features into their model.

Ryan Culbertson is a senior engineer on Spotify's ML platform team. He is currently working on Spotify's system for generating near-real-time features. Before that he worked on Spotify's feature management system, stream processing infrastructure, and backend deployment infrastructure.

David Xia is a senior engineer on Spotify's ML platform team. Over the past year he helped build and operate a centralized Ray platform that enables Spotify ML practitioners to easily start prototyping their ideas and scaling their workloads. Before that he worked on Spotify's core infrastructure for backend services, specifically on deployment tooling.

We'll hit up the local bar right after for an after-party.

NYC MLOps Community Meetup @ Spotify

Builder registration closed - but to attend the event, visit here: 

The MLOps Community in New York is partnering with AWS and Inspired Capital to highlight builders in the NYC community.

We are selecting 10 builders to showcase their work. You'll be given a monitor and a desk, and an audience of data-scientists and ML engineers will walk around your station, asking questions and discussing your project!

You’re either a data scientist building ML models or a software engineer building support for ML models, or building AI-applications.

You are also the kind of person who is open to going deep into the technical details and enjoy a technical conversation!

Call for ML Builders: Apply to present at August MLOPs Community meetup

Curious about how the NYC community is building and using AI?

Come see a dozen AI engineers and data scientists from the community showcase how they're using ML, how they're building ML, and how they're productionizing it!

Come walk around each of the stations, where you can find a different engineer building an intelligence-powered application or an internal ML platform.

Come to look at their code, learn from their experience, ask questions, eat, drink and network!

Jonathan Frankle, Chief Scientist -- Neural Networks at MosicaML / Databricks

6:30pm - Introductions and project overviews

Thank you to Inspired Capital and AWS startup for hosting and sponsoring!

For those who are interested in getting more guidance on how to build LLM powered applications from the ground up, we’ll be hosting a workshop on September 9. Spaces are limited. Register 

ML Show & Tell  [In-person]

Curious about how to build LLM-Powered apps?

Join us for a morning workshop led by engineers from Weights and Biases to learn how to build LLM-powered apps, evaluate their performance, and think through the new world of LLM-safety and deployment.

Register for this workshop to power-up your LLM skills in just 3 hours!

For this event, we are partnering with Women in Machine Learning and Data Science (WiMLDS), Weights and Biases, and South Park Commons!

Build and Deploy LLM-Based Apps [In-person]

🎉 The MLOps Community in San Francisco is coming together in person for our 5th meetup of the year, hosted at South Park Commons!

This month, we'll do a deep dive into some quirks and challenges in deploying LLMs to production - from training and fine-tuning to using popular APIs and even hosting your own inside your private cloud. 

🤔 𝗪𝗵𝗮𝘁 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗲𝘅𝗽𝗲𝗰𝘁:

🚨 𝗡𝗢𝗧𝗘: Limited seats. Please RSVP!

This event is brought to you in partnership with 

Adam Becker

Events