Eye tracking, Henry Kissinger on AI, Vim

06/08/2018 28 min Episodio 8
Eye tracking, Henry Kissinger on AI, Vim

Listen "Eye tracking, Henry Kissinger on AI, Vim"

Episode Synopsis


Chris and Daniel help us wade through the week’s AI news, including open ML challenges from Intel and National Geographic, Henry Kissinger’s views on AI, and a model that can detect personality based on eye movements. They also point out some useful resources to learn more about pandas, the vim editor, and AI algorithms.
Join the discussionChangelog++ members support our work, get closer to the metal, and make the ads disappear. Join today!Sponsors:Hired – Salary and benefits upfront? Yes please. Our listeners get a double hiring bonus of $600! Or, refer a friend and get a check for $1,337 when they accept a job. On Hired companies send you offers with salary, benefits, and even equity upfront. You are in full control of the process. Learn more at hired.com/practicalai.

Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com.

Linode – Our cloud server of choice. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code changelog2018. Start your server - head to linode.com/changelog

Rollbar – We catch our errors before our users do because of Rollbar. Resolve errors in minutes, and deploy your code with confidence. Learn more at rollbar.com/changelog.

Featuring:Chris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XShow Notes:News:

RFP for National Geographic AI earth innovation
Intel - AI Interplanetary challenge
App that lets Alexa read sign language
The mythos of model interpretability
Artificial Intelligence Can Predict Your Personality By Simply Tracking Your Eyes
Think You Know How Disruptive Artificial Intelligence Is? Think Again.
How the Enlightenment Ends

Learning resources:

Pandas tips and tricks
Mastering vim quickly
An introduction to Gradient Descent Algorithm
Introducing capsule networks

Something missing or broken? PRs welcome!