The Microsoft Cloud Adoption Framework for Azure guides customers through their cloud journey, to use and adopt cloud services with confidence and in control.

In this video, Scott Bockheim shows Lara Rubbelke the tools, templates, assessments, and resources to implement the guidance from this framework in different stages and steps of the cloud journey.

Related links:

I started coding at age 11, when my parents caved in and got me a Commodore 64.  When I asked for money to buy a game to play on it, my mom said there was no money for that and that I should “write my own games.”

This was a good decade before Netscape went public and, while the internet did exist, it was only available for university researchers, the military, and government. We also didn’t have a modem, so no BBS systems to get advice on how to learn to program.

All I had was the reference guide that came with the computer and insatiable curiosity. I was not actively encouraged to learn to program, in fact, mostly the opposite.  Even my parents thought it was a waste of time. Programming was not seen as a viable career path or even a useful skill.

Nowadays, it’s very different. Coding is all the rage and the kids have access to more information and tutorials than ever before.

Here’s an interesting story about how kids are “leveling up.”

Siddhant Attavar, 14, of National Public School, Bengaluru, started with robotics lessons when he was in class four. Gradually, he began doing online courses on app development. “Now I’m trying to learn machine learning using TensorFlow (a free and open-source software library). There are a few sites online where […]

The Microsoft Cloud Adoption Framework for Azure guides customers through their cloud journey, to use and adopt cloud services with confidence and in control. In this episode, Scott Bockheim explores the guidance and documentation of the framework with Lara Rubbelke to provide an overview of all the components and elements included.

Lex Fridman inteviews Cristos Goodrow, VP of Engineering at Google and head of Search and Discovery at YouTube (aka YouTube Algorithm).

This conversation is part of the Artificial Intelligence podcast.

OUTLINE:
0:00 – Introduction
3:26 – Life-long trajectory through YouTube
7:30 – Discovering new ideas on YouTube
13:33 – Managing healthy conversation
23:02 – YouTube Algorithm
38:00 – Analyzing the content of video itself
44:38 – Clickbait thumbnails and titles
47:50 – Feeling like I’m helping the YouTube algorithm get smarter
50:14 – Personalization
51:44 – What does success look like for the algorithm?
54:32 – Effect of YouTube on society
57:24 – Creators
59:33 – Burnout
1:03:27 – YouTube algorithm: heuristics, machine learning, human behavior
1:08:36 – How to make a viral video?
1:10:27 – Veritasium: Why Are 96,000,000 Black Balls on This Reservoir?
1:13:20 – Making clips from long-form podcasts
1:18:07 – Moment-by-moment signal of viewer interest
1:20:04 – Why is video understanding such a difficult AI problem?
1:21:54 – Self-supervised learning on video
1:25:44 – What does YouTube look like 10, 20, 30 years from now?

Roadshow takes Comma.ai CEO. George Hotz. out with the latest version of his company’s assisted-driving hardware here at CES 2020, featuring a more user-friendly interface and a cleaner install.

The Comma Two is a piece of hardware about the size of a smartphone that can be mounted on your windshield. A forward-facing camera shows the road ahead with your lane highlighted, your speed and the speed limit. 

Lex Fridman shared this lecture by Vivienne Sze in January 2020 as part of the MIT Deep Learning Lecture Series.

Website: https://deeplearning.mit.edu
Slides: http://bit.ly/2Rm7Gi1
Playlist: http://bit.ly/deep-learning-playlist

LECTURE LINKS:
Twitter: https://twitter.com/eems_mit
YouTube: https://www.youtube.com/channel/UC8cviSAQrtD8IpzXdE6dyug
MIT professional course: http://bit.ly/36ncGam
NeurIPS 2019 tutorial: http://bit.ly/2RhVleO
Tutorial and survey paper: https://arxiv.org/abs/1703.09039
Book coming out in Spring 2020!

OUTLINE:
0:00 – Introduction
0:43 – Talk overview
1:18 – Compute for deep learning
5:48 – Power consumption for deep learning, robotics, and AI
9:23 – Deep learning in the context of resource use
12:29 – Deep learning basics
20:28 – Hardware acceleration for deep learning
57:54 – Looking beyond the DNN accelerator for acceleration
1:03:45 – Beyond deep neural networks

Walmart, JPMorgan Chase, and AB InBev are using the AI to digitally transform operations in the hopes it will free up workers to focus on the more critical aspects of their jobs and lead to significant cost-savings over the next several years.

They are not alone, many corporations are rushing to adopt artificial intelligence.

To support this push, many organizations are spending significantly to train their employees on AI and other new digital tools.

Business Insider has compiled a list of the seven books that can help start someone on the path toward becoming an AI expert.