Ep. 012, Rise of the machines

Underserved

Andrew Gelina

Society & Culture, Technology

5.0 • 1K Ratings

🗓️ 20 November 2019

⏱️ 39 minutes

🔗️ Recording | iTunes | RSS

🧾️ Download transcript

Summary

How many people started their data science career at 16 years old? Then took a sabbatical to play with famous jazz musicians? And subsequently bootstrapped the US presence for a Norwegian data science firm? I know one! His name is Russ Wilcox. On this week's Underserved Russel explains how a Tesla sees the world (and how it can be fooled), how to teach an old AI new tricks, and we discuss the ethical implications of artificial intelligence. If you ever wondered how machine learning worked, or if the rise of SKYNET is imminent, this is the podcast for you.

Russel's company, Sannsyn US Sannsyn.com/us
Gradient Descent: https://en.wikipedia.org/wiki/Gradient_descent
Convolutional neural networks: https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks
Anders Hanssen: https://www.mn.uio.no/math/personer/vit/anderch/
Tensorflow: https://www.tensorflow.org/
Keras: https://keras.io/
Pytorch: https://pytorch.org/
Comparison of TF, Keras, PT: https://dzone.com/articles/tensorflow-vs-pytorch-vs-keras-for-nlp
Anthony Fung: https://www.anthonyfungmusic.com/
George Garzone: http://www.georgegarzone.com/
The Russ Wilcox Jazz Group : https://www.facebook.com/rwilcoxjazz/

Transcript

Click on a timestamp to play from that location

0:00.0	Hello and welcome to this week's edition of Underserve, the podcast for the rest of the tech industry.
0:12.3	I'm your host Andrew Jelina. I am fortunate this week to be joined by Russ Wilcox, head of Sansin U.S.
0:20.0	Russ,
0:23.0	welcome.
0:24.0	A physicist turned data scientist over the years.
0:27.0	Yeah, it's been quite a journey.
0:29.0	I got my start in 2007, working with the US Geological Survey, doing data science or
0:36.7	alternative means of energy looking at a substance called methane gas hydrate.
0:40.6	And since then I've been attracted to computational solutions to
0:45.4	very challenging problems and I think that summarizes where we're at with
0:49.0	data science and AI today. So methane gas hydrate does that have to do with fracking at all or?
0:54.0	No not really so about 500 meters below the sea floor on continental shelves.
0:59.0	Methane is actually more stable being a solid than a gas and what we were interested is looking at
1:05.2	the physical properties of the sediment looking at whether we could classify
1:08.8	coarse-grain versus fine-grain and really kind of quantify how this stuff formed because there's far more potenti
1:15.0	far more of this than oil reserves in the world and more importantly
1:17.6	methane is a far more potent greenhouse gas than CO2.
1:21.5	So we were looking at it both from an alternative means of energy
1:24.1	standpoint but also a climate crisis standpoint. So you got into data science, you
1:28.6	know there's a lot of hype around it these days. I mean everyone's talking
1:31.9	about machine learning and AI and if
1:34.7	anyone has like an if-then statement in something they're like oh it's
	...

Please login to see the full transcript.

Previous episode | Next episode

Disclaimer: The podcast and artwork embedded on this page are from Andrew Gelina, and are the property of its owner and not affiliated with or endorsed by Tapesearch.

Generated transcripts are the property of Andrew Gelina and are distributed freely under the Fair Use doctrine. Transcripts generated by Tapesearch are not guaranteed to be accurate.