Common sense: the Chomsky/Piaget debates come to AI

In 1975, Noam Chomsky and Jean Paiget held a historic debate about the nature of human cognition; Chomsky held that babies are born with a bunch of in-built rules and instincts that help them build up the knowledge that they need to navigate the world; Piaget argued that babies are effectively blank slates that acquire knowledge from experiencing the world (including the knowledge that there is a thing called "experience" and "the world"). Read the rest

A catalog of ingenious cheats developed by machine-learning systems

When you train a machine learning system, you give it a bunch of data -- a simulation, a dataset, etc -- and it uses statistical methods to find a way to solve some task: land a virtual airplane, recognize a face, match a block of text with a known author, etc. Read the rest

Researchers claim to have permanently neutralized ad-blocking's most promising weapons

Last year, Princeton researchers revealed a powerful new ad-blocking technique: perceptual ad-blocking uses a machine-learning model trained on images of pages with the ads identified to make predictions about which page elements are ads to block and which parts are not. Read the rest

Using machine learning to teach robots to get dressed

In the Siggraph 2018 paper Learning to Dress: Synthesizing Human Dressing Motion via Deep Reinforcement Learning, a Georgia Institute of Technology/Google Brain research team describe how they taught body-shame to an AI, leaving it with an unstoppable compulsion to clothe itself before the frowning mien of God. Read the rest

DeOldify: a free/open photo-retoucher based on machine learning

Jason Antic's DeOldify is a Self-Attention Generative Adversarial Network-based machine learning system that colorizes and restores old images. It's only in the early stages but it's already producing really impressive results, and the pipeline includes a "defade" model that is "just training the same model to reconstruct images that augmented with ridiculous contrast/brightness adjustments, as a simulation of fading photos and photos taken with old/bad equipment." Read the rest

Robin "Sourdough" Sloan is using a machine-learning autocomplete system to write his next novel

Robin Sloan is a programmer and novelist whose books like Sourdough and Mr Penumbra's 24-Hour Bookstore are rich and evocative blends of self-aware nerdy playfulness and magical speculation. Read the rest

Compression could be machine learning's "killer app"

Pete Warden (previously) writes persuasively that machine learning companies could make a ton of money by turning to data-compression: for example, ML systems could convert your speech to text, then back into speech using a high-fidelity facsimile of your voice at the other end, saving enormous amounts of bandwidth in between. Read the rest

What would a "counterculture of AI" look like?

Shitty math kills: shitty math "proved" that being selfish produced optimal outcomes and torched the planet; shitty math rains hellfire missiles down on innocents; in the 1960s, shitty math drove the "hamlet pacification program," producing 90,000 pages a month in data about the endless hail of bombs the US dropped on Vietnam. Read the rest

Hate-speech detection algorithms are trivial to fool

In All You Need is “Love”: Evading Hate Speech Detection, a Finnish-Italian computer science research team describe their research on evading hate-speech detection algorithms; their work will be presented next month in Toronto at the ACM Workshop on Artificial Intelligence and Security. Read the rest

There's a literal elephant in machine learning's room

Machine learning image classifiers use context clues to help understand the contents of a room, for example, if they manage to identify a dining-room table with a high degree of confidence, that can help resolve ambiguity about other objects nearby, identifying them as chairs. Read the rest

IBM developed NYPD surveillance tools that let cops pick targets based on skin color

The NYPD's secretive Lower Manhattan Security Coordination Center uses software from IBM in its video analytics system, which allows cops to automatically scan surveillance footage for machine-generated labels that identify clothing and other identifying classifiers. Read the rest

Here's the funniest, most scathing, most informative and most useful talk on AI and security

James Mickens (previously) has a well-deserved reputation for being the information security world's funniest speaker, and if that were all he did, he would still be worth listening to. Read the rest

A machine learning system trained on scholarly journals could correct Wikipedia's gendered under-representation problem

Quicksilver is a machine-learning tool from AI startup Primer: it used 30,000 Wikipedia entries to create a model that allowed it to identify the characteristics that make a scientist noteworthy enough for encyclopedic inclusion; then it mined the academic search-engine Semantic Scholar to identify the 200,000 scholars in a variety of fields; now it is systematically composing draft Wikipedia entries for scholars on its list who are missing from the encyclopedia. Read the rest

There's something eerie about bots that teach themselves to cheat

One of the holy grails of computer science is unsupervised machine learning, where you tell an algorithm what goal you want it to attain, and give it some data to practice on, and the algorithm uses statistics to invent surprising ways of solving your problem. 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

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

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