Chatbot Passed Turing Test

This nanochip reprograms cells to heal organs. The tissue nanotransfection device is a noninvasive nanochip that transports genes to cells through an electrical charge.

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Fractal Friday ॐ Not my photo ॐ

Struggle no more – Virtually choose your nail polish color

In an effort to solve the trial-by-purchase problem, the nail gurus at Sally Hansen are introducing a new app which lets you virtually paint on nail polish.

With ManiMatch, there’s no need to upload a photo or take a picture. Launch the app and put your hand in front of the camera and it starts scanning to determine your skin tone in order to provide color recommendations. Choose one, and the app paints the color right onto your nails then, Voila! Your nails on the screen.

How To Buy Bitcoins In India | A Step-By-Step Guide Find more Bitcoin mining rig reviews: http://bitcoinist.net

5 Mysterious Posts Found On Reddit That STILL Remain Unexplained…

FontCode

Research from Columbia Computer Graphics Group can create textual encryption by minute altering of font characteristics using neural networks:

We introduce FontCode, an information embedding technique for text documents. Provided a text document with specific fonts, our method embeds user-specified information in the text by perturbing the glyphs of text characters while preserving the text content. We devise an algorithm to choose unobtrusive yet machine-recognizable glyph perturbations, leveraging a recently developed generative model that alters the glyphs of each character continuously on a font manifold. We then introduce an algorithm that embeds a user-provided message in the text document and produces an encoded document whose appearance is minimally perturbed from the original document. We also present a glyph recognition method that recovers the embedded information from an encoded document stored as a vector graphic or pixel image, or even on a printed paper. In addition, we introduce a new error-correction coding scheme that rectifies a certain number of recognition errors. Lastly, we demonstrate that our technique enables a wide array of applications, using it as a text document metadata holder, an unobtrusive optical barcode, a cryptographic message embedding scheme, and a text document signature.

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Shape Representation by Zippables

Computational Fabrication research from the Interactive Geometry Lab can turn 3D model files into objects with textiles, connecting parts and forming shape using zip fasteners:

Fabrication from developable parts is the basis for arts such as papercraft and needlework, as well as modern architecture and CAD in general, and it has inspired much research. We observe that the assembly of complex 3D shapes created by existing methods often requires first fabricating many small parts and then carefully following instructions to assemble them together. Despite its significance, this error prone and tedious process is generally neglected in the discussion. We present the concept of zippables – single, two dimensional, branching, ribbon-like pieces of fabric that can be quickly zipped up without any instructions to form 3D objects. Our inspiration comes from the so-called zipit bags (just-zipit.com), which are made of a single, long ribbon with a zipper around its boundary. In order to assemble the bag, one simply needs to zip up the ribbon. Our method operates in the same fashion, but it can be used to approximate a wide variety of shapes. Given a 3D model, our algorithm produces plans for a single 2D shape that can be laser cut in few parts from fabric or paper. A zipper can then be attached along the boundary by sewing, or by gluing using a custom-built fastening rig. We show physical and virtual results that demonstrate the capabilities of our method and the ease with which shapes can be assembled. 

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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

Kavya Kopparapu, 16, invented an app and lens to diagnose the leading cause of preventable blindness

A teenager managed to develop an app that can help diagnose a diabetes-related condition affecting her grandfather.

Kavya Kopparapu’s grandfather lives in India, where there aren’t enough ophthalmologists to help diagnose all of those who could be affected by diabetic retinopathy.

DR is the world’s leading cause of vision loss in people age 20 to 65, according to the International Agency for the Prevention of Blindness, which estimated that 50% of people with diabetes are undiagnosed.

But in the absence of proper doctors, “computers could be used in their place,” Kopparapu, 16, said in a TEDx talk on artificial intelligence.

Alongside her brother and another classmate, she invented Eyeagnosis, a smartphone app that can photograph patients’ eyes and match them to a database of 34,000 retinal scans collected from the National Institute of Health. Read more (8/8/17)

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