Unconference: MLOps

What is an unconference?

An unconference is a participant-driven meeting. Attendees come together, bringing their challenges and relying on the experience and know-how of their peers for solutions. A professional facilitator is also there to help keep the discussion moving forward, but where it goes is up to the participants.

It's a facilitated peer group that avoids the hierarchical aspects of a conventional conference, such as a top-down organization. Only the broad themes are predetermined. Everything else is just space for attendees to sound off ideas together, relate to shared challenges and rewards, and identify new ideas and goals. 

Our unconference sessions have been based on the Open Space Technology and Lean Coffee format since 2006.

Why are we doing unconference sessions?

We have designed QCon for senior software practitioners. That role comes with demanding challenges and complex problems. 

Connecting with your peers in a structured environment allows you to:

  • Broaden your perspective with the benefit of the experience of others.
  • Challenge how you've been doing things by breaking out of your bubble.
  • Learn from peers who have already overcome the challenges you're facing now.
  • Benchmark your solutions against other teams and organizations.
  • Get real-world perspectives on challenges that might be too novel or specific to find solutions in books or presentations.
  • Validate your technical roadmap with real-world research.
  • Connect with others like you and build relationships that go beyond the event.

Date

Wednesday Jun 14 / 01:40PM EDT ( 50 minutes )

Location

Carroll Gardens

Video

Video is not available

Slides

Slides are not available

Share

From the same track

Session Machine Learning

Improve Feature Freshness in Large Scale ML Data Processing

Wednesday Jun 14 / 11:50AM EDT

In many ML use cases, model performance is highly dependent on the quality of the features they are trained and inference on. One of the important dimensions of feature quality is the freshness of the data.

Speaker image - Zhongliang Liang
Zhongliang Liang

Engineering Manager @Facebook AI Infra

Session MLOps

Platform and Features MLEs, a Scalable and Product-Centric Approach for High Performing Data Products

Wednesday Jun 14 / 04:10PM EDT

In this talk, we would go through the lessons learnt in the last couple of years around organising a Data Science Team and the Machine Learning Engineering efforts at Bumble Inc.

Speaker image - Massimo Belloni
Massimo Belloni

Data Science Manager @Bumble

Session AI/ML

A Bicycle for the (AI) Mind: GPT-4 + Tools

Wednesday Jun 14 / 02:55PM EDT

OpenAI recently introduced GPT-3.5 Turbo and GPT-4, the latest in its series of language models that also power ChatGPT.

Speaker image - Sherwin Wu
Sherwin Wu

Technical Staff @OpenAI

Speaker image - Atty Eleti
Atty Eleti

Software Engineer @OpenAI

Session ML Infrastructure

Introducing the Hendrix ML Platform: An Evolution of Spotify’s ML Infrastructure

Wednesday Jun 14 / 10:35AM EDT

The rapid advancement of artificial intelligence and machine learning technology has led to exponential growth in the open-source ML ecosystem.

Speaker image - Divita Vohra
Divita Vohra

Senior Product Manager @Spotify

Speaker image - Mike Seid
Mike Seid

Tech Lead for the ML Platform @Spotify

Session

Panel: Navigating the Future: LLM in Production

Wednesday Jun 14 / 05:25PM EDT

Our panel is a conversation that aim to explore the practical and operational challenges of implementing LLMs in production. Each of our panelists will share their experiences and insights within their respective organizations.

Speaker image - Sherwin Wu
Sherwin Wu

Technical Staff @OpenAI

Speaker image - Hien Luu
Hien Luu

Sr. Engineering Manager @DoorDash

Speaker image - Rishab Ramanathan
Rishab Ramanathan

Co-founder & CTO @Openlayer