Google is trying harder than anyone else to make machine brains work

Backchannel has a fairly in-depth write up about Google’s scramble to hire or train programmers with experience in “machine learning” (aka artificial intelligence and neural networks). It’s betting hard on the technology’s ability to mine and interpret data in a way that’s not just novel, but also useful to it’s flagship Search app and more.

Deepmind, a British technology start-up that was bought by Google in 2014, and whose motto is “Solve intelligence,” was an early move for them. The company caught Google’s attention after they published an article detailing how one of their machine babies learned to play seven different Atari games well enough to pose a threat to human video game dominance. DeepMind also created AlphaGo, a machine learning program that whooped a “9 dan rank” human Go player in 2015. Additionally, the company is partly responsible for the DeepDream phenomenon of last summer. It was a neural network system that was able to take user-fed images and figure out terrifying ways to fuse them with puppies and slugs.

Google Brain / DeepMind HQ

Per the Backchannel article, Google has been “obsessed” with machine learning this year. Among their efforts so far: Pilfering any and all students of artificial intelligence guru Pedro Domingos of the University of Washington; allowing artificial intelligence engineers out of the mysterious Google X R&D basement and into daylight; posting flyers in the cafeteria bulletin boards of technical colleges across the country and the world: “Do you want to be a machine learning ninja????!” Google also made a powerful neural network building tool, TensorFlow, available to the public in November 2015, ostensibly to help build a generation of amateur programmers already familiar with machine learning, to be hired en-masse once they have degrees.

Machine learning is a new way of programming. From my limited understanding, it seems to be about creating semi-intelligent data golems to do your bidding, often to superhuman effect. Not only can a neural network learn and in a way understand what a shiba inu looks like (and find pictures of it for all your doge memes), it can use that understanding to then go through a pile of, say, a million pictures of dogs and doges of different breeds and then delineate between each different breed. “If it learns one breed,” reads the article, “it can use the same technique to identify the other 9999 using the same technique.”

Birth of a new God???

Machine learning can also, to a limited extent, understand language, which Google has put to use with its SmartReply feature. Per the article: “Traditional AI methods of language understanding depended on embedding rules of language into a system, but in [SmartReply], as with all modern machine learning, the system was fed enough data to learn on its own, just as a child would.”

Personally I like typing my replies and I think I always will, and, from what I read, SmartReply initially had the tendency to suggest “I love you” as a reponse whenever it sensed tension in the conversation. But other machine learning could be important, and, as this article will explain, Google is desperate to be at the forefront.

Artist Jennifer Linton reclaimed her life from the baby who stole it

Jennifer Linton created My Alphabet, (all of which is available to view on her website) as a way of reclaiming her life in the face of parenthood’s demands. She quotes the Guerrilla Girls, who in a 1989 poster quipped that women artists have “the opportunity to choose between career and motherhood.’” Linton defied the expectations of both so called “womanhood” and so called “adulthood,” by seizing “nap schedules and playdates as opportunities for creative output.” To many who feel the demands of real life are crushing to their true selves, she could be viewed as a sort of hero.

Your standard illustrated alphabet for children is depoliticized, and intentionally dumb. Usually involving animals and unremarkable objects -- O for Orange, T for Train -- they present the world in bits and idealized pieces that create a world of safe nonsense for our young ones, a fantasy zone where no one calls you fat, no one calls you a fag, and where the constant silent scream of the world at large can’t keep you from learning your ABCs.

Life is only a bit easier after learning the alphabet. Arguably, you’re one step closer to being able to read about the latest terrorist attack or Donald Trump tweet. But it’s disingenuous to say that Linton’s alphabet offers a more honest alternative to children’s literature. Linton's alphabet is for us, the sullied and profaned, we who have already had language imprinted on us and have suffered its ravages.

Typical childhood realness

What life is actually like

Illustrated alphabets for children are made for children by adults. They represent the world we want our kids living in, a world of smiling Apes eating Apples, a world where a Duck is fucking stoked to be beating a Drum, and where Frogs can wear Frilly dresses and Fans if they want to, Fuck the consequences. Illustrated alphabets by adults and for adults are invariably entirely about style, or entirely about sex, or entirely ironic. Ours is not a world of Bears eating Buns but of Bombs killing Babies, of Commercials asking for Cash.

In the end, Jennifer Linton seems to have succeeded where so many others have failed. She's integrated her family life with her artistic practice, in a way that doesn't compromise ideals, in a way that reminds us that the concepts that plague or control us in daily life are, in many respects, learned. 

You can buy Jennifer Linton’s alphabet in a “perfectly bound” edition (or as an ebook) at this Blurb.com page.