The Equation Group's sourcecode is totally fugly

With the leak of exploits developed by The Equation Group, the long-secret, NSA-adjacent super-elite hacking squad -- published by The Shadow Brokers, who have some extremely heterodox theories about auction design -- it's now possible to audit the source code of some of the NSA's crown-jewel cyberweapons. Read the rest

UK/EU security researchers: tax-free stipend to study privacy and authentication

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UC London's offering a tax-free stipend for UK/EU students to work on designing and evaluating new approaches for continuous authentication, based on a solid theoretical underpinning so as to give a high degree of confidence that the resulting decisions match expectations and requirements" as well as "ways to preserve user privacy by processing behavioural measurements on the user’s computer such that sensitive information is not sent to the online service." (Image: LordHarris, CC-BY-SA) (Thanks, William!) Read the rest

If the 2016 election is hacked, it's because no one listened to these people

Ever since the Supreme Court ordered the nation's voting authorities to get their act together in 2002 in the wake of Bush v Gore, tech companies have been flogging touchscreen voting machines to willing buyers across the country, while a cadre computer scientists trained in Ed Felten's labs at Princeton have shown again and again and again and again that these machines are absolutely unfit for purpose, are trivial to hack, and endanger the US election system. Read the rest

Forget Skynet: AI is already making things terrible for people who aren't rich white dudes

Kate Crawford (previously) takes to the New York Times's editorial page to ask why rich white guys act like the big risk of machine-learning systems is that they'll evolve into Skynet-like apex-predators that subjugate the human race, when there are already rampant problems with machine learning: algorithmic racist sentencing, algorithmic, racist and sexist discrimination, algorithmic harassment, algorithmic hiring bias, algorithmic terrorist watchlisting, algorithmic racist policing, and a host of other algorithmic cruelties and nonsense, each one imbued with unassailable objectivity thanks to its mathematical underpinnings. Read the rest

100 million VWs can be unlocked with a $40 cracker (and other cars aren't much better)

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In Lock It and Still Lose It—On the (In)Security of Automotive Remote Keyless Entry Systems, a paper given at the current Usenix Security conference in Austin, researchers with a proven track record of uncovering serious defects in automotive keyless entry and ignition systems revealed a technique for unlocking over 100,000 million Volkswagen cars, using $40 worth of hardware; they also revealed a technique for hijacking the locking systems of millions of other vehicles from other manufacturers. Read the rest

Trump is an object lesson in the problems of machine learning

Trump's algorithm is to say semi-random things until his crowd roars its approval, then he iteratively modifies those statements, seeking more and more approval, until he maxes out and tries a new tack. Read the rest

How facial recognition works (and how to hack your own in Python)

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You could not ask for a clearer, easier-to-read, more informative guide to facial recognition and machine learning thank Adam Geitgey's article, which is the latest in a series of equally clear explainers on machine learning, aimed at non-technical people -- and if you are a programmer, he's got links to Python sample source and projects you can use to develop your own versions. Read the rest

Man builds giant, discrete-component-based computer that can play Tetris

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James Newman's "Megaprocessor" is a giant "microprocessor" built on transistors and other discrete components that he soldered onto boards and wired together in frames that stand 2m high and run 10m long. Read the rest

White House contends with AI's big social challenges, July 7/NYC

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Meredith from Simply Secure writes, "Artificial Intelligence is already with us, and the White House and New York University’s Information Law Institute are hosting a major public symposium to face what the social and economic impacts might be. AI Now, happening July 7th in New York City, will address the real world impacts of AI systems in the next next 5-10 years." Read the rest

Analyzing all known Metal lyrics with natural language processing

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Iain ("an ex-physicist currently working as a data scientist") scraped Dark Lyrics and built a dataset of lyrics to 222,623 songs by 7,364 metal bands, then used traditional natural language processing techniques to analyze them. Read the rest

Even if Moore's Law is "running out," there's still plenty of room at the bottom

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A very good piece by Tom Simonite in the MIT Technology Review looks at the implications of Intel's announcement that it will slow the rate at which it increases the density of transistors in microprocessors. Read the rest

Google is restructuring to put machine learning at the core of all it does

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Steven Levy is in characteristic excellent form in a long piece on Medium about the internal vogue for machine learning at Google; drawing on the contacts he made with In the Plex, his must-read 2012 biography of the company, Levy paints a picture of a company that's being utterly remade around newly ascendant machine learning techniques. Read the rest

Cataloging the problems facing AI researchers is a cross between a parenting manual and a management book

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Concrete Problems in AI Safety, an excellent, eminently readable paper from a group of Google AI researchers and some colleagues, sets out five hard problems facing the field: robots might damage their environments to attain their goals; robots might figure out how to cheat to attain their goals; supervising robots all the time is inefficient; robots that are allowed to try novel strategies might cause disasters; and robots that are good at one task might inappropriately try to apply that expertise to another unrelated task. Read the rest

Algorithms to Live By: what computer science teaches us about everyday decisions

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Brian Christian and Tom Griffiths' Algorithms to Live By: The Computer Science of Human Decisions is pitched as a combination of personal advice and business book grounded in the lessons of computer science, but it's better than that: while much of the computer science they explain is useful in personal and management contexts, the book is also a beautifully accessible primer on algorithms and computer science themselves, and a kind of philosophical treatise on what the authors call "computational kindness" and "computational stoicism."

Let's teach programming as a tool for analyzing data to transform the world

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Data-scientist Kevin H Wilson argues that computers are tools for manipulating data -- from companies' sales data to the input from games controllers -- but we teach computer programming as either a way to make cool stuff (like games) or as a gateway to "rigorous implementation details of complicated language," while we should be focusing on fusing computer and math curriciula to produce a new generation of people who understand how to use computers to plumb numbers to find deep, nuanced truths we can act upon. Read the rest

Intel x86s hide another CPU that can take over your machine (you can't audit it)

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Recent Intel x86 processors implement a secret, powerful control mechanism that runs on a separate chip that no one is allowed to audit or examine. When these are eventually compromised, they'll expose all affected systems to nearly unkillable, undetectable rootkit attacks. I've made it my mission to open up this system and make free, open replacements, before it's too late.

Emojibot uses deep learning to synthesize expressive new nonverbal communications

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Dango is a personal assistant that feeds its users' messages into a deep-learning neural net to discover new expressive possibilities for emojis, GIFs and stickers, and then suggests never-seen combinations of graphic elements to your text messages that add striking nuances to them. Read the rest

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