Avsnitt
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In this episode of A4N, I have a special announcement! While the A4N podcast will be going on indefinite hiatus, it is because I am now hosting the SuperDataScience Podcast. If you enjoyed A4N then you're sure to enjoy the SuperDataScience podcast, which publishes twice every week on Tuesdays and Fridays!
You can check it out here: https://www.superdatascience.com/podcast
In addition, a raw video feed of the podcast is available on YouTube. -
In this episode of A4N, Dr. Rasmus Rothe joins us to discuss Merantix, the world’s first AI Venture Studio, which he co-founded in 2016. We discuss how Merantix companies are shaping the future by applying machine learning to automating cancer detection, training self-driving cars, and more!
Dr. Rasmus Rothe is a German native, and co-founder of Merantix, the world’s first AI-focused venture studio. Merantix has already launched three successful AI-driven companies with three more operating in stealth, and raised an additional EUR 25 MM in 2020 to continue to apply world-class AI research to solving practical issues. Rasmus published 15+ papers on deep learning while attending Oxford, Princeton and ETH Zurich, where he received his Ph.D. in computer vision and deep learning. Before founding Merantix, Rasmus worked for BCG, Google, and built a deep learning service with 150m+ users. He is also a founding board member of the German AI Association.
Reference links:
1:53 Previous episode of A4N
2:05 racy doctoral research
2:28 Merantix
5:27 Deep Learning Illustrated
14:35 Merantix raised 25m euros
20:00 Vara Healthcare
20:10 Vara raised 6.5m euros ($7m) in Series A venture capital
31:41 Siasearch
38:50 Dr. Alex Flint's start-up, Zippy, was acquired by General Motors' self-driving car unit in 2018
41:30 German A.I. Association
46:20 Dr. Rasmus Rothe's LinkedIn
46:28 Rasmus on Twitter
47:15 Jon Krohn on LinkedIn
47:40 Jon Krohn's email newsletter signup on his homepage
48:00 Jon on Twitter
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Saknas det avsnitt?
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In this episode of our A4N podcast, our guest host Kirill Eremenko joins us to discuss SuperDataScience, his thriving data-science education business, and Vince introduces us to machine learning projects being applied to understand -- and preserve -- marine life in the oceans.
Our special guest today is Kirill Eremenko. Kirill is Russian-born Australian, and Founder and CEO of SuperDataScience , an online educational portal for Data Scientists. Their mission is to “Make The Complex Simple,” and become the biggest learning portal for Data Science enthusiasts. Ever. He is also the Co-Founder of BlueLifeAI, Founder of the DataScienceGo conference, and hosts his own podcast, the SuperDataScience Podcast!
Part I: Scaling a Global Data Business with Kirill Eremenko
4:25 OmniFocus
4:36 SuperDataScience
5:25 Udemy
8:00 The Productivity Project
8:05 Deep Work
8:20 The Great CEO Within
9:20 Peter Akkies: Get Stuff Done with OmniFocus 3
17:57 DataScienceGO Virtual
22:10 Fake Ad for “TPML”
Part 2: 23:00 Saving the Oceans with Machine Learning
24:30 A.I. Is Helping Scientists Understand an Ocean’s Worth of Data
30:18 Some like it hot - visual guidance for preference prediction
31:15 Merantix
32:10 Wirewax
33:05 Scale
36:00 VGGish
39:57 University of San Diego’s FRED
41:18 Jon Krohn’s LinkedIn
41:23 Kirill Eremenko’s LinkedIn
41:23 Vince Petaccio II’s LinkedIn
41:28 Twitter @JonKrohnLearns
41:49 [email protected]
41:52 email newsletter at jonkrohn.com
42:00 Machine Learning Foundations GitHub
42:38 Jon Krohn YouTube channel
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For our second episode of A4N — the Artificial Neural Network News Network podcast — we discuss how anyone can contribute to the cure for the coronavirus pandemic, mind-controlled prosthetic limbs, and what it takes to succeed as an AI start-up. (Reference Links for video are below)
Our special guest today is Ben Taylor. Ben is the Co-Founder and Chief AI Officer of zeff.ai, an AI product company, and former Chief Data Scientist at HireVue. He is a prolific thinker and innovator, and we’re thrilled to have him as a guest on A4N!
Segment 1 on Tackling Coronaviruses with Machine Learning
1:12 Ben Taylor, Hirevue
2:23 untapt, zeff.ai
4:41 Die Antwoord
5:39 Maryam Khakpour LinkedIn post, Yuval Noah Harari’s book Homo Deus
12:05 CORD-19
16:33 First episode of A4N podcast
17:00 Kaggle Covid-19-related tasks
20:44 Folding@home
Segment 2 on Mind Controlled Prosthetics 36:3937:45 Reference blog post from University of Michigan
47:41 Gabe Adams: Twitter account and YouTube video
54:27 Norman Doidge book The Brain That Changes Itself
Segment 3 on AI Startups 57:0057:20 Reference blog post from Andreesen Horowitz
Jon Krohn / A4N YouTube channel
Jon Krohn Twitter
Jon Krohn website for signing up to email newsletter
Jon Krohn LinkedIn
Grant Beyleveld Twitter
Ben Taylor Twitter
Ben Taylor LinkedIn
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For our inaugural episode of A4N — the "Artificial Neural Network News Network", a lighthearted podcast covering A.I. advances — we discuss real-time face recognition by London police, cheating in the famed Kaggle data-science competition, the landmark AlphaFold model for predicting protein structure from DNA, and how to become (or at least hire!) an A.I. researcher.
Below’s a detailed breakdown of the episode’s four segments, with time stamps for all of the references that we mentioned.
Segment 1 — Global headline news: Intrusive real-time face recognition
In this segment, we discuss a controversial new approach by the Met police force in London, which is to use a (low-performing) facial-recognition system to flag “known criminals” in real-time in train stations.
Segment host: Vince Petaccio II
Reference news article from The Guardian (1:10)
Citizen App (9:10)
Segment 2 — “Sports”: Kaggle Cheating
In this segment, we introduce what the Kaggle data-science competition platform is and how folks (now formerly!) working at the well-known firm H2O.ai cheated to perform well. How unsportspersonlike!
Segment host: Andrew Vlahutin
Reference news article from Towards Data Science (14:38)
Segment 3 — Health: AlphaFold
In this segment, we introduce how DNA encodes proteins that do all of the work in our bodies. We then describe the new AlphaFold algorithm that crushes all of the existing approaches at predicting protein structure from DNA-sequence data. In the benchmark “CASP” competition, AlphaFold correctly predicted the structure of 58.1% of the proteins while the second-best algorithm correctly predicted 7.0% of them.
Segment host: Grant Beyleveld
Reference blog post from DeepMind (26:31)
CASP (30:05)
AlphaGo documentary film (37:20)
Segment 4 — Classifieds: How to become (or hire!) an A.I. Researcher
In this segment, we list ways that you can find hidden-gem A.I. researchers to hire from within a high-demand field. We also list approaches for breaking into the field of A.I. if you come from a non-traditional background, e.g., you don’t already have a PhD in machine learning or statistics.
Segment host: Jon
How to Hire Smarter than the Market (38:33)
Getting Hired in AI as Self-Taught Researcher (40:39)
Deep Learning book by Goodfellow et al. (41:30)
