Two Minute Papers highlights the paper “Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis”
An unofficial implementation of this paper is available here.
Note that this was not made by the authors of the original paper and may contain deviations from the described technique – please judge its results accordingly!
Lex Fridman interviews Elon Musk in this fascinating podcast.
Elon Musk is the CEO of Tesla, SpaceX, Neuralink, and a co-founder of several other companies. This is the second time Elon has been on the podcast. You can watch the first time here: https://www.youtube.com/watch?v=dEv99vxKjVI This conversation focuses on the incredible engineering and innovation done at Neuralink. This work promises to help treat neurobiological diseases, to help us further understand the connection between the individual neuron to the high-level function of the human brain, and finally to one day expand the capacity of the brain through two-way communication with computational devices, the Internet, and artificial intelligence systems. This conversation is part of the Artificial Intelligence podcast.
Transcript (PDF): http://bit.ly/32Lt7M5
Machine learning can be hard but moving your ML model to your embedded device can be even harder.
This article by John Fogart discusss a few pain points in this process, and some solutions.
How do you get from this set of tools, code and data using many different formats, sources, licenses and execution environments into something that you can execute entirely inside some little box—one that may (or may not) be connected to the internet ever again?
Data Scientist, Laura Edell shows us how she dominates her Fantasy Football league by using Azure Machine Learning.
Additional Resources:
BBC Click heads to Taiwan to find out what ‘Made in Taiwan’ really means in the 21st century; from healthcare artificial intelligence to solving the pollution crisis.
Two Minute Papers examines the paper “HoloGAN: Unsupervised learning of 3D representations from natural images.”
In my final article for MSDN, I explore the nuts and bolts of face detection.
Detecting Faces It’s important to point out two distinct terms that are often used interchangeably: face detection and face recognition. Face detection, as the name implies, is limited to detecting the presence of faces in an image. Face recognition involves discerning unique facial characteristics (such as location and shape […]
TensorFlow 2.0 is all about ease of use, and there has never been a better time to get started.
In this talk, learn about model-building styles for beginners and experts, including the Sequential, Functional, and Subclassing APIs.
We will share complete, end-to-end code examples in each style, covering topics from “Hello World” all the way up to advanced examples. At the end, we will point you to educational resources you can use to learn more.
Presented by: Josh Gordon
View the website → https://goo.gle/36smBfW
Lex Fridman interviews Sean Carroll in this thought provoking interview.
Sean Carroll is a theoretical physicist at Caltech and Santa Fe Institute specializing in quantum mechanics, arrow of time, cosmology, and gravitation. He is the author of several popular books including his latest on quantum mechanics (Something Deeply Hidden) and is a host of a great podcast called Mindscape. This conversation is part of the Artificial Intelligence podcast.
This is the second time Sean has been on the podcast. You can watch the first time here: https://www.youtube.com/watch?v=l-NJrvyRo0c
O’Reilly and TensorFlow teamed up to present the first TensorFlow World last week.
It brought together the growing TensorFlow community to learn from each other and explore new ideas, techniques, and approaches in deep and machine learning.
Presenters in the keynote:
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