Jordan Fisher — Skipping the Line with Autonomous Checkout
08/04/22 • 57 min
Jordan Fisher is the CEO and co-founder of Standard AI, an autonomous checkout company that’s pushing the boundaries of computer vision.
In this episode, Jordan discusses “the Wild West” of the MLOps stack and tells Lukas why Rust beats Python. He also explains why AutoML shouldn't be overlooked and uses a bag of chips to help explain the Manifold Hypothesis.
Show notes (transcript and links): http://wandb.me/gd-jordan-fisher
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⏳ Timestamps:
00:00 Intro
00:40 The origins of Standard AI
08:30 Getting Standard into stores
18:00 Supervised learning, the advent of synthetic data, and the manifold hypothesis
24:23 What's important in a MLOps stack
27:32 The merits of AutoML
30:00 Deep learning frameworks
33:02 Python versus Rust
39:32 Raw camera data versus video
42:47 The future of autonomous checkout
48:02 Sharing the StandardSim data set
52:30 Picking the right tools
54:30 Overcoming dynamic data set challenges
57:35 Outro
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Connect with Jordan and Standard AI
📍 Jordan on LinkedIn: https://www.linkedin.com/in/jordan-fisher-81145025/
📍 Standard AI on Twitter: https://twitter.com/StandardAi
📍 Careers at Standard AI: https://careers.standard.ai/
---
💬 Host: Lukas Biewald
📹 Producers: Riley Fields, Cayla Sharp, Angelica Pan, Lavanya Shukla
---
Subscribe and listen to our podcast today!
👉 Apple Podcasts: http://wandb.me/apple-podcasts
👉 Google Podcasts: http://wandb.me/google-podcasts
👉 Spotify: http://wandb.me/spotify
Jordan Fisher is the CEO and co-founder of Standard AI, an autonomous checkout company that’s pushing the boundaries of computer vision.
In this episode, Jordan discusses “the Wild West” of the MLOps stack and tells Lukas why Rust beats Python. He also explains why AutoML shouldn't be overlooked and uses a bag of chips to help explain the Manifold Hypothesis.
Show notes (transcript and links): http://wandb.me/gd-jordan-fisher
---
⏳ Timestamps:
00:00 Intro
00:40 The origins of Standard AI
08:30 Getting Standard into stores
18:00 Supervised learning, the advent of synthetic data, and the manifold hypothesis
24:23 What's important in a MLOps stack
27:32 The merits of AutoML
30:00 Deep learning frameworks
33:02 Python versus Rust
39:32 Raw camera data versus video
42:47 The future of autonomous checkout
48:02 Sharing the StandardSim data set
52:30 Picking the right tools
54:30 Overcoming dynamic data set challenges
57:35 Outro
---
Connect with Jordan and Standard AI
📍 Jordan on LinkedIn: https://www.linkedin.com/in/jordan-fisher-81145025/
📍 Standard AI on Twitter: https://twitter.com/StandardAi
📍 Careers at Standard AI: https://careers.standard.ai/
---
💬 Host: Lukas Biewald
📹 Producers: Riley Fields, Cayla Sharp, Angelica Pan, Lavanya Shukla
---
Subscribe and listen to our podcast today!
👉 Apple Podcasts: http://wandb.me/apple-podcasts
👉 Google Podcasts: http://wandb.me/google-podcasts
👉 Spotify: http://wandb.me/spotify
Previous Episode
Drago Anguelov — Robustness, Safety, and Scalability at Waymo
Drago Anguelov is a Distinguished Scientist and Head of Research at Waymo, an autonomous driving technology company and subsidiary of Alphabet Inc.
We begin by discussing Drago's work on the original Inception architecture, winner of the 2014 ImageNet challenge and introduction of the inception module. Then, we explore milestones and current trends in autonomous driving, from Waymo's release of the Open Dataset to the trade-offs between modular and end-to-end systems.
Drago also shares his thoughts on finding rare examples, and the challenges of creating scalable and robust systems.
Show notes (transcript and links): http://wandb.me/gd-drago-anguelov
---
⏳ Timestamps:
0:00 Intro
0:45 The story behind the Inception architecture
13:51 Trends and milestones in autonomous vehicles
23:52 The challenges of scalability and simulation
30:19 Why LiDar and mapping are useful
35:31 Waymo Via and autonomous trucking
37:31 Robustness and unsupervised domain adaptation
40:44 Why Waymo released the Waymo Open Dataset
49:02 The domain gap between simulation and the real world
56:40 Finding rare examples
1:04:34 The challenges of production requirements
1:08:36 Outro
---
Connect with Drago & Waymo
📍 Drago on LinkedIn: https://www.linkedin.com/in/dragomiranguelov/
📍 Waymo on Twitter: https://twitter.com/waymo/
📍 Careers at Waymo: https://waymo.com/careers/
---
Links:
📍 Inception v1: https://arxiv.org/abs/1409.4842
📍 "SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation", Qiangeng Xu et al. (2021), https://arxiv.org/abs/2108.06709
📍 "GradTail: Learning Long-Tailed Data Using Gradient-based Sample Weighting", Zhao Chen et al. (2022), https://arxiv.org/abs/2201.05938
---
💬 Host: Lukas Biewald
📹 Producers: Cayla Sharp, Angelica Pan, Lavanya Shukla
---
Subscribe and listen to our podcast today!
👉 Apple Podcasts: http://wandb.me/apple-podcasts
👉 Google Podcasts: http://wandb.me/google-podcasts
👉 Spotify: http://wandb.me/spotify
Next Episode
Aaron Colak — ML and NLP in Experience Management
Aaron Colak is the Leader of Core Machine Learning at Qualtrics, an experiment management company that takes large language models and applies them to real-world, B2B use cases.
In this episode, Aaron describes mixing classical linguistic analysis with deep learning models and how Qualtrics organized their machine learning organizations and model to leverage the best of these techniques. He also explains how advances in NLP have invited new opportunities in low-resource languages.
Show notes (transcript and links): http://wandb.me/gd-aaron-colak
---
⏳ Timestamps:
00:00 Intro
00:57 Evolving from surveys to experience management
04:56 Detecting sentiment with ML
10:57 Working with large language models and rule-based systems
14:50 Zero-shot learning, NLP, and low-resource languages
20:11 Letting customers control data
25:13 Deep learning and tabular data
28:40 Hyperscalers and performance monitoring
34:54 Combining deep learning with linguistics
40:03 A sense of accomplishment
42:52 Causality and observational data in healthcare
45:09 Challenges of interdisciplinary collaboration
49:27 Outro
---
Connect with Aaron and Qualtrics
📍 Aaron on LinkedIn: https://www.linkedin.com/in/aaron-r-colak-3522308/
📍 Qualtrics on Twitter: https://twitter.com/qualtrics/
📍 Careers at Qualtrics: https://www.qualtrics.com/careers/
---
💬 Host: Lukas Biewald
📹 Producers: Riley Fields, Cayla Sharp, Angelica Pan, Lavanya Shukla
---
Subscribe and listen to our podcast today!
👉 Apple Podcasts: http://wandb.me/apple-podcasts
👉 Google Podcasts: http://wandb.me/google-podcasts
👉 Spotify: http://wandb.me/spotify
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