A 40cm-square patch that renders you invisible to person-detecting AIs

Researchers from KU Leuven have published a paper showing how they can create a 40cm x 40cm "patch" that fools a convoluted neural network classifier that is otherwise a good tool for identifying humans into thinking that a person is not a person -- something that could be used to defeat AI-based security camera systems. They theorize that the could just print the patch on a t-shirt and get the same result. Read the rest

A machine-learning wishlist for hardware designers

Pete Warden (previously) is one of my favorite commentators on machine learning and computer science; yesterday he gave a keynote at the IEEE Custom Integrated Circuits Conference, on the ways that hardware specialization could improve machine learning: his main point is that though there's a wealth of hardware specialized for creating models, we need more hardware optimized for running models. Read the rest

Mechanical calculators have the BEST divide-by-zero errors

In a delightful short video, Klara Sjöberg demonstrates the extreme and alarming freakout that you can trigger in a mechanical calculator by trying to divide a number by zero; in a followup, Lynn Grant tweets "That is why the old Friden calculators had a 'Divide Stop' key." Read the rest

What the rest of the world doesn't know about Chinese AI

ChinAI Jeff Ding's weekly newsletter reporting on the Chinese AI scene; on the occasion of the newsletter's first anniversary, Ding has posted a roundup of things about the Chinese AI scene that the rest of the world doesn't know about, or harbors incorrect beliefs about. Read the rest

Most paint-spatters are valid perl programs

If you run most paint-spatters through OCR software, it will generate valid perl programs. Read the rest

Front-line programmers default to insecure practices unless they are instructed to do otherwise

It's always sort of baffling when security breaches reveal that a company has stored millions of users' passwords in unencrypted form, or put their data on an insecure cloud drive, or transmitted it between the users' devices and the company's servers without encryption, or left an API wide open, or some other elementary error: how does anyone in this day and age deploy something so insecure? Read the rest

Creative Adversarial Networks: GANs that make art

Generative Adversarial Networks use a pair of machine-learning models to create things that seem very realistic: one of the models, the "generator," uses its training data to make new things; and the other, the "discerner," checks the generator's output to see if it conforms to the model. Read the rest

A machine-learning system that guesses whether text was produced by machine-learning systems

Gltr is an MIT-IBM Watson Lab/Harvard NLP joint project that analyzes texts and predicts whether that text was generated by a machine-learning model. Read the rest

Towards a general theory of "adversarial examples," the bizarre, hallucinatory motes in machine learning's all-seeing eye

For several years, I've been covering the bizarre phenomenon of "adversarial examples (AKA "adversarial preturbations"), these being often tiny changes to data than can cause machine-learning classifiers to totally misfire: imperceptible squeaks that make speech-to-text systems hallucinate phantom voices; or tiny shifts to a 3D image of a helicopter that makes image-classifiers hallucinate a rifle Read the rest

Even without explicit collusion, pricing algorithms converge on price-fixing strategies

Literally the only kind of monopolistic behavior that the US government is willing to prosecute is price fixing, and that's why it's so important to read Artificial intelligence, algorithmic pricing, and collusion, a paper by four Italian economists from the University of Bologna who document how price-fixing is an emergent property of pricing algorithms -- the systems online merchants use to price-match with their competitors. Read the rest

Teaching test-driven development and continuous integration with "Evil Fizz Buzz"

Fizz Buzz is the word-game in which players in a circle count from 1 up, substituting multiples of three with "fizz" and multiples of five with "buzz" ("1, 2, Fizz, 4, Buzz, Fizz, 7, 8, Fizz, Buzz, 11, Fizz, 13, 14, Fizz Buzz, 16, 17, Fizz, 19, Buzz, Fizz, 22, 23, Fizz, Buzz, 26, Fizz, 28, 29, Fizz Buzz, 31, 32, Fizz, 34, Buzz, Fizz, ..."). Read the rest

Building a high-performance cluster of Gameboy emulators to teach computers to play video games

Kamil Rocki was inspired by the 2016 paper from Google Deepmind researchers explaining how they used machine learning to develop a system that could play Breakout on the Atari 2600 with superhuman proficiency. Read the rest

Princeton's interdisciplinary Center for Information Technology Policy is seeking visiting scholars

Are you a PhD with interest in "the intersection of digital technology and public life, including experts in computer science, sociology, economics, law, political science, public policy, information studies, communication, and other related disciplines?" Princeton's CITP has three open job postings for 10-month residences starting Sept 1, 2019. Read the rest

Breed weird critters with machine learning and Ganbreeder

Ganbreeder uses a machine learning technique called Generative Adversarial Networks (GANs) to generate images that seem like photos, at least a first glance. Read the rest

What's missing from machine learning research: an East African perspective

CIT computer scientist Milan Cvitkovic conducted 46 in-depth interviews with "scientists, engineers, and CEOs" and collated their machine learning research needs into an aptly named paper entitled "Some Requests for Machine Learning Research from the East African Tech Scene," which presents an illuminating look into the gaps in the current practice of machine learning, itself an example of how rich-world priorities shape our ability to understand, compute and predict the world. Read the rest

How to use science fiction to teach tech ethics

Science fiction writer/lawyer Casey Fiesler is a maven in the field of tech ethics education (she maintains the amazing spreadsheet of tech-ethics syllabi); she uses science fiction stories as a jumping-off point for her own classroom discussions of ethics in technology. Read the rest

Generative adversarial network produces a "universal fingerprint" that will unlock many smartphones

Researchers at NYU and U Michigan have published a paper explaining how they used a pair of machine-learning systems to develop a "universal fingerprint" that can fool the lowest-security fingerprint sensors 76% of the time (it is less effective against higher-security sensors). Read the rest

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