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

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:

  • Jeff Dean, Google
  • Megan Kacholia, Google
  • Frederick Reiss, IBM
  • Theodore Summe, Twitter
  • Craig Wiley, Google
  • Kemal El Moujahid, Google

In this nature video explains Google’s recent announcement on reaching a major quantum computing milestone.

Google says they have reached ‘quantum supremacy’ with their quantum computer ‘Sycamore’. Nature reporter Elizabeth Gibney explains what this means, why IBM disagree, and the significance for quantum computing.

Read the full news article here: https://www.nature.com/articles/d41586-019-03213-z

Read the research paper here: https://www.nature.com/articles/s41586-019-1666-5

Seeker examines a leaked paper from Google claimed that a quantum computer demonstrated “quantum supremacy.”

But what does that mean exactly?

Quantum computers’ potential and the advantages they promise over classical computers all remain largely theoretical, and hypothetically speaking, it is predicted that quantum computers will be able to solve problems that are beyond the reach of the classical computers we use today. Passing such a threshold will be considered proof of what we call “quantum supremacy.”

Siraj Raval just posted this video on defending AI against adversarial attacks

Machine Learning technology isn’t perfect, it’s vulnerable to many different types of attacks! In this episode, I’ll explain 2 common types of attacks and 2 common types of defenses using various code demos from across the Web. There’s some really dope mathematics involved with adversarial attacks, and it was a lot of fun reading about the ‘cat and mouse’ game between new attack techniques, followed by new defense techniques. I encourage anyone new to the field who finds this stuff interesting to learn more about it. I definitely plan to. Let’s look into some math, code, and examples. Enjoy!

Slideshow for this video:
https://colab.research.google.com/drive/19N9VWTukXTPUj9eukeie55XIu3HKR5TT

Demo project:
https://github.com/jaxball/advis.js

 

Lex Fridman interviews Peter Norvig.

Peter Norvig is a research director at Google and the co-author with Stuart Russell of the book Artificial Intelligence: A Modern Approach that educated and inspired a whole generation of researchers.

EPISODE LINKS:

OUTLINE:

  • 0:00 – Introduction
  • 0:37 – Artificial Intelligence: A Modern Approach
  • 9:11 – Covering the entire field of AI
  • 15:42 – Expert systems and knowledge representation
  • 18:31 – Explainable AI
  • 23:15 – Trust
  • 25:47 – Education – Intro to AI – MOOC
  • 32:43 – Learning to program in 10 years
  • 37:12 – Changing nature of mastery
  • 40:01 – Code review
  • 41:17 – How have you changed as a programmer
  • 43:05 – LISP
  • 47:41 – Python
  • 48:32 – Early days of Google Search
  • 53:24 – What does it take to build human-level intelligence
  • 55:14 – Her
  • 57:00 – Test of intelligence
  • 58:41 – Future threats from AI
  • 1:00:58 – Exciting open problems in AI