Stylistic analysis can de-anonymize code, even compiled code

A presentation today at Defcon from Drexel computer science prof Rachel Greenstadt and GWU computer sicence prof Aylin Caliskan builds on the pair's earlier work in identifying the authors of software and shows that they can, with a high degree of accuracy, identify the anonymous author of software, whether in source-code or binary form. Read the rest

Voice assistants suck, but they suck worse if you have an "accent"

Research into the shittiness of voice assistants zeroed in on a problem that many people were all-too-aware of: the inability of these devices to recognize "accented" speech ("accented" in quotes because there is no one formally correct English, and the most widely spoken English variants, such as Indian English, fall into this "accented" category). Read the rest

Wildbook: facial recognition for critters in the wild

The Wildbook project conducts wild animal population censuses by combining photos of animals taken by tourists, scientists, and volunteers and then using their distinctive features (zebra stripes, whale fluke shapes, leopard spots, etc) to identify individuals and produces unprecedented data that uses creepy facial recognition tools for non-creepy purposes. Read the rest

Dank Learning: teaching a machine learning algorithm to generate memes

A physics student and an engineering student from Stanford fed 400,000 memes to a Long Short-Term Memory Recurrent Neural Network and asked it to generate more memes of its own. Read the rest

Ranking the most influential computer security papers ever published

Konrad Rieck has data-mined the nine top security conferences, compiling a decade-by-decade list of the papers most often cited in the presentations delivered at these events: top of the pile is Random Oracles are Practical: A Paradigm for Designing Efficient Protocols (Sci-Hub mirror), from the 1993 ACM Conference on Computer and Communications Security. Rieck has also produced a "normalised" ranking that tries to offset the seniority effect, whereby older papers collect more citations. (via Four Short Links) Read the rest

The first "portable" computer fit in two trailer vans and weighed 20 tons

The first electromechanical computers occupied whole buildings, making them rather unwieldy; in the 1950s, an effort to create a "portable" computer called the DYSEAC bore fruit in the form of a computer on wheels that could be relocated, provided you had the trucking logistics to move two trailers with a combined weight of 20 tons. Read the rest

The new Deep Fakes are in and they're spookily good

SIGGRAPH is coming, when all the amazeballs graphics research drops, and the previews are terrifying and astonishing by turns (sometimes both!). Read the rest

Machine learning may be most useful in tiny, embedded, offline processors

The tiny embedded processors in smart gadgets -- including much of the Internet of Shit -- are able to do a lot of sensing without exhausting their batteries, because sensing is cheap in terms of power consumption. Read the rest

Using saccade-tracking to trick VR users into walking in circles, giving the illusion of "infinite walking"

"Saccades" are the phenomenon where your eyes flick momentarily from one place to another; during saccades, you don't consciously register visual input, creating tiny moments of blindness (AKA "saccadic suppression"). Read the rest

The most interesting thing about the "Thanksgiving Effect" study is what it tells us about the limits of data anonymization

Late last year, a pair of economists released an interesting paper that used mobile location data to estimate the likelihood that political polarization had shortened family Thanksgiving dinners in 2016. Read the rest

Count your bees with a Raspberry Pi and machine learning

Sure, you worry about your bees, what with colony collapse disorder, but they're hard to count! Read the rest

Garbage In, Garbage Out: machine learning has not repealed the iron law of computer science

Pete Warden writes convincingly about computer scientists' focus on improving machine learning algorithms, to the exclusion of improving the training data that the algorithms interpret, and how that focus has slowed the progress of machine learning. Read the rest

The paleocomputing miracle of the 76477 Space Invaders sound effects chip

In 1978, the 76477 Complex Sound Generation chip was foundational to creating the sound effects in many popular games, notably Space Invaders; it was also popular with hobbyists who could buy the chip at Radio Shack -- it could do minor miracles, tweaking a white noise generator to produce everything from drums to explosions, using an integrated digital mixer to layer and sequence these sounds. Read the rest

Debugging AI is a "hard problem"

Writing code is a lot easier than fixing code! For a lot of well-understood reasons, code requires a lot of debugging to run safely and property, and different code structures and practices make debugging harder or easier. S. Zayd Enam, an AI researcher at Stanford, writes about the specific problems of debugging AI code, which is extremely difficult. Read the rest

A hard look at the wastefulness of "proof of work," the idea at the core of the blockchain

David Gerard is a technically minded, sharp-witted, scathing critic of Bitcoin and other cryptocurrencies; his criticism is long, comprehensive and multipartite, but of particular interest is is critique of "proof of work" (an idea that is central to the blockchain, but which many cryptographers are skeptical of). Read the rest

A dozen googlers quit over Google's military drone contract

Google's "Project Maven" is supplying machine-learning tools to the Pentagon to support drone strikes; the project has been hugely divisive within Google, with employees pointing out that the company is wildly profitable and doesn't need to compromise on its ethics to keep its doors open; that the drone program is a system of extrajudicial killing far from the battlefield; and that the firm's long-term health depends on its ability to win and retain the trust of users around the world, which will be harder if Google becomes a de facto wing of the US military. Read the rest

Enhance enhance: Using machine learning to recover lost detail from upscaled photos

A team of researchers from Twitter have published a paper detailing a machine learning technique that uses a generative adversarial network to make shrewd guesses about how to up-res small images by up to 400%, into crisp, large images, with eye-popping results. Read the rest

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