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The Current MLOps Landscape // Nathan Benaich & Timothy Chen // MLOps Meetup #43

The Current MLOps Landscape // Nathan Benaich & Timothy Chen // MLOps Meetup #43

FromMLOps.community


The Current MLOps Landscape // Nathan Benaich & Timothy Chen // MLOps Meetup #43

FromMLOps.community

ratings:
Length:
59 minutes
Released:
Nov 23, 2020
Format:
Podcast episode

Description

MLOps community meetup #43! Last Wednesday, we talked to Nathan Benaich, General Partner at Air Street Capital and Timothy Chen, Managing Partner at Essence VC about The MLOps Landscape.

// Abstract:
In this session, we explored the MLOps landscape through the eyes of two accomplished investors. Tim And Nathan shared with us their experience in looking at hundreds of ML and MLOps companies each year to highlight major insights they have gained. What do the ML infrastructure and tooling landscape look like at the moment? Where have they been seeing patterns emerge? What do they expect to see happen within the market in the next couple of years? What current tools out there are the most interesting to them? And last but not least how do they go about selecting which companies to invest in.

// Bio:
Nathan Benaich is the Founder and General Partner of Air Street Capital, a venture capital firm investing in early-stage AI-first technology and life science companies. The team’s investments include Mapillary (Acq. Facebook), Graphcore, Thought Machine, Tractable, and LabGenius. Nathan is Managing Trustee of The RAAIS Foundation, a non-profit with a mission to advance education and open-source research in common good AI. This includes running the annual RAAIS summit and funding fellowships at OpenMined. Nathan is also co-author of the annual State of AI Report. He holds a PhD in cancer biology from the University of Cambridge and a BA from Williams College.

Timothy Chen is the Managing Partner at Essence VC, with a decade of experience leading engineering in enterprise infra and open source communities/companies.
Prior to Essence, Tim was the SVP of Engineering at Cosmos, a popular open-source blockchain SDK. Prior to Cosmos, Tim cofounded Hyperpilot with Stanford Professor Christos Kozyrakis which later exited to Cloudera. Prior to Hyperpilot, Tim was an early employee at Mesosphere and CloudFoundry.
Tim is also active in the open-source space as an Apache member.

----------- Connect With Us ✌️-------------   
Join our Slack community:  https://go.mlops.community/slack
Follow us on Twitter:  @mlopscommunity
Sign up for the next meetup:  https://go.mlops.community/register  

Connect with Demetrios on LinkedIn:  https://www.linkedin.com/in/dpbrinkm/
Connect with Nathan on LinkedIn:  https://www.linkedin.com/in/nathanbenaich/
Connect with Tim on LinkedIn:  https://www.linkedin.com/in/timchen

Timestamps:
0:00 - Nathan Benaich & Timothy Chen
1:36 - Tim's background
4:07 - Nathan's background
8:08 - To Nathan: What's your take on the lay of the land in the MLOps fear or space?
10:20 - To Tim: Can you give us your rundown on what you've been seeing? The greater landscape that you look at.
14:35 - To Tim: What companies right now really excite you? What are some that are doing something that has a future?
19:36 - To Nathan: What kind of companies you're looking at right now that you're doing interesting things?  
22:37 - The MLOps tools mature as the companies mature.
23:45 - There's no tool that looks exactly the same from MLOps prospective
25:44 - Sometimes MLOps tools is not a choice by data scientists at all.
28:10 - What MLOps needs that are not being addressed by the market right now?
35:00 - What is the annotation stack?
37:28 - How do you think about in the context of federated learning?
41.24 - Will MLOps tools eventually become idiomatic? Would that be desirable?
47:55 - How do you switch from this open-source model to the money-making model?
52:30 - Should we focus only on the open-source only at first and think about monetization later? If so, are investors prepared to invest in no revenue companies?
Released:
Nov 23, 2020
Format:
Podcast episode

Titles in the series (100)

Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.