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Bitcoin micropayments: Coming to smartphones—and toasters?—everywhere

Micropayments might not top your list of most compelling inventions, but they’re a sought-after capability. Small payments of less than a dollar, or even less than a cent, have the potential to shake up old, established business models, and open up new doors for the Internet of Everything.

Small digital payments have been tried again and again—in fact, Web inventor Tim Berners-Lee tried to embed micropayment capability into the original World Wide Web, but without success. So far, inherent transaction costs have been an unsurpassable hurdle.

Some argue that digital payment methods like bitcoin are the way forward.

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Adversarial Machines

There’s been some interesting developments recently in adversarial training, but I thought it would probably be a good idea to first talk about what adversarial images are in the first place. This Medium article by @samim is an accessible explanation of what’s going on. It references this talk by Ian Goodfellow, asking if statistical models understand the world.

Machine learning can do amazing magical things, but the computer isn’t looking at things the same way that we do. One way to exploit that is by adding patterns that we can’t detect but that create enough of a difference in the data to completely fool the computer. Is it a dog or an ostrich?

There’s been quite a lot of research into finding ways round this problem as well as exploiting it to avoid facial recognition or other surveillance. And, like I said, there’s been some interesting recent developments that I hope to talk about here.

https://medium.com/@samim/adversarial-machines-998d8362e996#.n7j43766v

Illustration for the current issue of @wireduk, in which Jürgen Schmidhuber explains why human-level AI is within our reach.

Machine gun position on the German R-class Zeppelin ‘LZ 63’, 1916-17

via reddit

A Computer Vision System’s Walk Through Times Square

Video from deepython demonstrates an object recognition neural network framework applied to footage taken in New York:

This is a state of the art object detection framework called Faster R-CNN described here https://arxiv.org/abs/1506.01497 using tensorflow.

I took the following video and fed it through Tensorflow Faster R-CNN model, this isn’t running on an embedded device yet.

Link

Next-System

Japanese developers are creating mobile apps incorporating Augmented Reality for photographic tricks, from free floating object placements to optical camo effects:

[Google Translate:]

I tried to develop a demonstration using ARkit that makes it possible to take movies like MATOX like the cheat technique “The World” used by DIO in the third part of “Joji O’s Strange Adventure” It was. I hope to be able to respond to Google ARCore in the future. 

Optical camouflage like the Ghost in the Shell.前に開発した光学迷彩！#光学迷彩 #Opticalcamouflage #Invisible #ghostintheShell pic.twitter.com/wVlr7Q188t

— next-system (@next_kinesys)

September 7, 2017

Next-System website can be found here

Machine Learning with Python: Easy and robust method to fit nonlinear data ☞ https://towardsdatascience.com/machine-learning-with-python-easy-and-robust-method-to-fit-nonlinear-data-19e8a1ddbd49

SP. Gynoid (Fembot)

A.I. Artificial Intelligence (2001)

HV. Self-replicating artificial intelligence program named Dorothy.

Galerians: Ash (2002) PS2

Lol - Hello, would you like to hear a TCP joke?