This is what is sometimes missing from the debate around algorithms in our lives: A voice that speaks with clarity about how faulty algorithms are worsening inequality in our world. In addition to explaining the math, she makes an impassioned argument against the growing over-reliance on totally opaque models that are often biased and downright incorrect.
The fact that even in these progressive cities, the poor get poorer, equality is worsening, and the benefits are seen mainly by the well-off. “So which is it,” he asks early on in the book, as much to himself as to us, “Are cities the great engines of innovation, the models of economic and social progress, that the optimists celebrate, or are they the zones of gaping inequality and class divisions that the pessimists decry?”
Really, it’s about how we as a culture have totally misunderstood what play and fun really are. Bogost explains that fun comes from restrictions, rules, and tensions, not freedom.”Fun isn’t pleasure, it turns out,” he writes. “Fun is the feeling of finding something new in a familiar situation. Fun almost demands boredom: you need the sense that nothing good could possibly arise from an experience in order for the experience there to smolder with the hot pleasure of surprise.”
Google doesn't require a college degree, based on research showing no correlation between academic credentials and performance on the job. And Google has had its pick of top students from top programs at top universities.
One student told me that a friend of hers had left Yale because she found the school "stifling to the parts of yourself that you'd call a soul."
This system is exacerbating inequality, retarding social mobility, perpetuating privilege, and creating an elite that is isolated from the society that it's supposed to lead.
Peter Thiel's Fellowship offers students $100,000 over two years to drop out of school. The offer shocked me when I first heard of it. On meeting a few ThielFellows, all outstanding, and seeing how traditional universities can stifle many (not all!) students, I saw value in his approach and attack.
Inventor, entrepreneur, visionary, Ray Kurzweil's accomplishments read as a startling series of firsts -- a litany of technological breakthroughs we've come to take for granted. Kurzweil invented the first optical character recognition (OCR) software for transforming the written word into data, the first print-to-speech software for the blind, the first text-to-speech synthesizer, and the first music synthesizer capable of recreating the grand piano and other orchestral instruments, and the first commercially marketed large-vocabulary speech recognition.
In 2009, he unveiled Singularity University, an institution that aims to "assemble, educate and inspire leaders who strive to understand and facilitate the development of exponentially advancing technologies." He is a Director of Engineering at Google, where he heads up a team developing machine intelligence and natural language comprehension.
by Arsames Qajar
"Get ready for hybrid thinking" by Ray Kurzweil
why you should really stop using public wifi (hbr)
The most remarkable thing about neural nets is that no human being has programmed a computer to perform any of the stunts described above. In fact, no human could. Programmers have, rather, fed the computer a learning algorithm, exposed it to terabytes of data—hundreds of thousands of images or years’ worth of speech samples—to train it, and have then allowed the computer to figure out for itself how to recognize the desired objects, words, or sentences.
Venture capitalists, who didn’t even know what deep learning was five years ago, today are wary of startups that don’t have it. “We’re now living in an age,” Chen observes, “where it’s going to be mandatory for people building sophisticated software applications.” People will soon demand, he says, “ ‘Where’s your natural-language processing version?’ ‘How do I talk to your app? Because I don’t want to have to click through menus.’ ”