BBC Click visits a children’s hospital using a new low-cost portable ultrasound scanner and see the latest gadgets from Japan’s CEATEC expo.
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.”
The Verge takes a look at the Skydio 2 – a drone that can fly itself, follow you around without crashing into trees.
This device is affordable at $999 for the aircraft itself. A pair of optional $150 controllers are a separate purchase if you need longer range and/or more control over filming.
Learn more: http://bit.ly/2olhnkx
Two Minute Papers explores the paper “Google Research Football: A Novel Reinforcement Learning Environment.”
Obviously, when they say “football”, they mean soccer.
Source code:: https://github.com/google-research/football
Related blog post: https://ai.googleblog.com/2019/06/introducing-google-research-football.html
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:
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.
- Peter web: http://norvig.com/
- 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.
- Demo 1 (Generating Music): https://colab.research.google.com/notebooks/magenta/piano_transformer/piano_transformer.ipynb
- Demo 2 (Generating Faces):
- Demo 3 (Generating 3D Objects):
- Autoencoders explained:
- Generative Adversarial Networks explained:
- Sequence Models explained:
- Generative Modeling explained:
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 […]