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Work: Director, Research Development, Protocol Labs
Worked: Azure, Google, Chef, Amazon & Microsoft (Exchange, IE, Vista, Research)
Co-founder: Hark, MTS and Formatta
Open Source Projects: Kubernetes & Kubeflow

I am:

David Aronchick

I believe:

TECHNOLOGY IS NOT NEUTRAL.

So:
We must ACTIVELY use our skill, passion and energy for the good of humanity.

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About Me

About Me

I lead Research Development at Protocol Labs, helping, deploying and organizing our community building the next generation of the Internet.

Previously, I led Open Source Machine Learning Strategy at Azure, product management for Kubernetes on behalf of Google, launched Google Kubernetes Engine, and co-founded the Kubeflow project and the SAME project. I have also worked at Microsoft, Amazon and Chef and co-founded three startups.

When not spending too much time in service of electrons, I can be found on a mountain (on skis), traveling the world (via restaurants) or participating in kid activities, of which there are a lot more than I remember than when I was that age.

Mission

My Mission

We have seen technology do some amazing things. But, we've also seen technology misused, misapplied, or just plain broken.

These failures, more often than not, are because we take a hands off approach to what we build and how it will be used.

If we are going to leave the world a better place than it was when we found it, we must come together to ensure that it is easy to use tech for good, and hard for it to be used for bad.

I'm passionate about doing this in three areas:

Machine Learning

Machine Learning is hard!
​My job at Azure is to try to
make it less so.

Whether or not it is on the Azure Cloud, I'd love to hear about
what I can do to help.

Open Data

We collect an INSANE amount of information, only a tiny fraction of which is put to good use.

If you need data, have data you think should be publicly available or want someone
to collect data, let me know.

We all share a single planet and to survive as a species,
we've got to get it together.

I would love to bring more attention, help or funding to any effort that might help us get there.

The Environment

My Talks

Talks

Upcoming:

Past:

Title
Location
Date
Truly Universal Compute: Expanding the Boundaries of Execution
Tokyo, Japan
05/12/2023
Introducing Bacalhau - Compute Over Data On Filecoin
Toronto, Canada
21/07/2022
Feature Store Summit: The SAME Project: A Cloud Native Approach to Reproducible Machine Learning
Seattle, WA
22/10/2021
Owned By Statistics: How Kubeflow & MLOps Can Help Secure Your ML Workloads
Seattle, WA
01/09/2020
Weave Online User Group: Using MLOps to Bring ML to Production
Online
17/12/2019
Weave Online User Group: Using MLOps to Bring ML to Production
Online
17/12/2019
Azure Machine Learning and Open Source: Designed for Each Other
Orlando, FL
08/11/2019
Azure Machine Learning and Open Source: Designed for Each Other
Orlando, FL
08/11/2019
MLOps NYC19 Livestream: Best Practices for Multiplatform MLOps with Kubeflow and MLflow
New York, NY
24/09/2019
Using MLOps to Bring ML to Production
New York, NY
24/09/2019
O'Reilly Velocity: How to Adopt Cloud Native Machine Learning with Kubernetes and Kubeflow
San Jose, CA
13/06/2019
Kubecon Europe: Towards Kubeflow 1.0, Bringing a Cloud Native Platform For ML to Kubernetes
Barcelona, Spain
22/05/2019
Kubecon Europe: Managing Machine Learning in Production with Kubeflow and DevOps
Barcelona, Spain
22/05/2019
Microsoft //build: MLOps: How to Bring Your Data Science to Production
Seattle, WA
07/05/2019
Microsoft //build: Breaking the Wall between Data Scientists and App Developers with MLOps
Seattle, WA
07/05/2019
F8: Powered By PyTorch
San Jose, CA
01/05/2019
NVidia GTC: Cloud Native ML with Kubeflow and TensorRT
San Jose, CA
20/03/2019
Kubecon NA 2018: Kubeflow Deep Dive
Seattle, WA
12/12/2018
Kubecon NA 2018: Machine Learning as Code
Seattle, WA
11/12/2018
Kubecon China 2018: A Year of Democratizing ML with Kubernetes and Kubeflow
Shanghai, China
14/11/2018
PyTorch Developer Conference: PyTorch & Google Cloud Platform (@ 1:04)
San Francisco, CA
07/10/2018
PyTorch Developer Conference
San Francisco, GA
01/08/2018
GCP Next 2018: How to Build Flexible ML on Kubernetes
San Francisco, CA
26/07/2018
SciPy 2018: Kubeflow: Pythonic Machine Learning at Scale
Austin, TX
15/07/2018
Cloud Native ML with Kubeflow at Paris Container Day
Paris, France
04/07/2018
The New Stack: Managing AI Workflows on Kubeflow
Copenhagen, Denmark
14/06/2018
Conquering Kubeflow with ksonnet, Ark & Sonobuoy
Copenhagen, Denmark
09/05/2018
Google Cloud OnAir: Kubeflow: Machine Learning on Kubernetes
Seattle, WA
08/05/2018
OpenShift Commons Lightning Talk - Introduction to Kubeflow
Copenhagen, Denmark
03/05/2018
Google Cloud @ Kubecon 2018
Copenhagen, Denmark
02/05/2018
Kubecon EU 2018: Kubeflow Deep Dive
Copenhagen, Denmark
01/05/2018
Kubecon EU 2018: ML on Kubernetes with Kubeflow
Copenhagen, Denmark
01/05/2018
OpenShift Commons Briefing - Introduction to Kubeflow
San Francisco, CA
26/03/2018
Cloud Engineering Podcast - GKE 1.9 with Chen Goldberg & David Aronchick
Seattle, WA
07/03/2018
Kubecon NA 2017: Introducing Kubeflow - Hot Dog or Not at Scale
Austin, TX
15/12/2017
What's Next in Machine Learning Panel
Austin, Texas
07/12/2017
Docker Madrid @ Campus Madrid
Madrid, Spain
07/10/2017
Cloud Native Computing with Kubernetes and OpenStack
Boston, MA
08/05/2017
Kubernetes 1.6 on AWS
Berlin, Germany
03/04/2017
Kubecon EU 2017: How Google Cloud Hosts and Manages Kubernetes at Scale
Berlin, Germany
01/04/2017
Tectonic Summit 2016: Kubernetes 1.5 and Beyond
New York, NY
10/12/2016
Kubecon NA 2016: Kubernetes 1.4 Launch
Seattle, WA
01/11/2016
Kubernetes 1.2 Hands On
Amsterdam, Netherlands
01/04/2016
Kubecon EU 2016: Kubernetes State of the Union
London, England
25/03/2016
Kubernetes 1.2 Concepts and Roadmap
Amsterdam, Netherlands
12/03/2016
Tectonic Summit 2015: Scaling your Application with Kubernetes
New York, NY
05/12/2015
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