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

Siraj Raval explores generative modeling technology.

This innovation is changing the face of the Internet as you read this. It’s now possible to design automated systems that can write novels, act as talking heads in videos, and compose music.

In this episode, Siraj explains how generative modeling works by demoing 3 examples that you can try yourself in your web browser. 

This looks interesting.

Google today introduced Neural Structured Learning (NSL) , an open source framework that uses the Neural Graph Learning method for training neural networks with graphs and structured data. NSL works with with the TensorFlow machine learning platform and is made to work for both experienced and inexperienced machine learning […]

Lex Fridman interviews Chris Urmson, former CTO of the Google Self-Driving Car team, a key engineer and leader behind the Carnegie Mellon autonomous vehicle entries in the DARPA grand challenges and the winner of the DARPA urban challenge. Today he is the CEO of Aurora Innovation, an autonomous vehicle software company he started with Sterling Anderson, who was the former director of Tesla Autopilot, and Drew Bagnell, Uber’s former autonomy and perception lead.