People respond to incentives, and so if we want to take on much bigger challenges, we need to collaborate across thousands and in some cases hundreds of thousands of people. How do you get 100,000 people to work together? It’s not that easy. In the old days, it was religion and before that it was simple fiat rules, tyranny. The Egyptians built some beautiful pyramids, but they did that with hundreds of thousands of slaves over decades. If we rule out slavery as a possible means of societal advances, there really isn’t any other choice. If we need 100,000 people to cure cancer, to deal with Alzheimer’s, to figure out fusion energy and climate change…I don’t know of any other way to do that other than financial markets: equity, debt, proper financing and proper payout of returns. I think that in many cases [finance] probably is the gating factor. That, to me, is the short answer to the question about why finance is so important.
Every time I get back into the editing room, I feel the wonder of it. One image is joined with another image, and a third phantom event happens in the mind’s eye – perhaps an image, perhaps a thought, perhaps a sensation. Something occurs, something absolutely unique to this particular combination or collision of moving images. And if you take a frame away from one or add a couple of frames to the other, the image in the mind’s eye changes. […] This “principle”, if that’s what you could call it, is just as applicable to the juxtaposition of words in poetry or forms and colours in painting. It is, I think, fundamental to the art of cinema. This is where the act of creation meets the act of viewing and engaging, where the common life of the filmmaker and the viewer exists, in those intervals of time between the filmed images that last a fraction of a fraction of a second but that can be vast and endless. This is where a good film comes alive as something more than a succession of beautifully composed renderings of a script. This is film-making.
As the technology advances, we might soon cross some threshold beyond which using AI requires a leap of faith. Sure, we humans can’t always truly explain our thought processes either—but we find ways to intuitively trust and gauge people. Will that also be possible with machines that think and make decisions differently from the way a human would? We’ve never before built machines that operate in ways their creators don’t understand. How well can we expect to communicate—and get along with—intelligent machines that could be unpredictable and inscrutable?
Illustration : Adam Ferriss
The internet and social media don’t create new personalities; they allow people to express sides of themselves that social norms discourage in the “real world”.
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We may come to see face-to-face conversation as the social medium that most distorts our personalities. It requires us to speak even when we don’t know what to say and forces us to be pleasant or acquiescent when we would rather not.
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Social media have turned a species used to intimacy into performers. But these performances are not necessarily false. Personality is who we are in front of other people. The internet, which exposes our elastic personalities to larger and more diverse groups of people, reveals the upper and lower bounds of our capacity for empathy and cruelty, anxiety and confidence.
Nostalgia, to me, is not the emotion that follows a longing for something you lost, or for something you never had to begin with, or that never really existed at all. It’s not even, not really, the feeling that arises when you realize that you missed out on a chance to see something, to know someone, to be a part of some adventure or enterprise or milieu that will never come again. Nostalgia, most truly and most meaningfully, is the emotional experience—always momentary, always fragile—of having what you lost or never had, of seeing what you missed seeing, of meeting the people you missed knowing, of sipping coffee in the storied cafés that are now hot-yoga studios. It’s the feeling that overcomes you when some minor vanished beauty of the world is momentarily restored, whether summoned by art or by the accidental enchantment of a painted advertisement for Sen-Sen, say, or Bromo-Seltzer, hidden for decades, then suddenly revealed on a brick wall when a neighboring building is torn down. In that moment, you are connected; you have placed a phone call directly into the past and heard an answering voice.
Illustration : Eleni Kalorkoti
The result is that modern machine learning offers a choice among oracles: Would we like to know what will happen with high accuracy, or why something will happen, at the expense of accuracy? The “why” helps us strategize, adapt, and know when our model is about to break. The “what” helps us act appropriately in the immediate future.
It can be a difficult choice to make. But some researchers hope to eliminate the need to choose—to allow us to have our many-layered cake, and understand it, too. Surprisingly, some of the most promising avenues of research treat neural networks as experimental objects—after the fashion of the biological science that inspired them to begin with—rather than analytical, purely mathematical objects.
The Presidential order that Donald Trump signed on Friday barring all refugees and citizens from seven Muslim countries from travel to the United States was reviewed by virtually no one. The State Department did not help craft it, nor the Defense Department, nor Justice. Trump’s Secretary of Homeland Security, John Kelly, “saw the final details shortly before the order was finalized,” CNN reported. Early Saturday morning, there were reports that two Iraqi refugees had been detained upon their arrival at John F. Kennedy Airport. When a lawyer for the men asked an official to whom he needed to speak to fix the situation, the official said, “Ask Mr. Trump.” This sounded like a sign of straight goonery and incipient authoritarianism; maybe it was. But it also may have been the only reasonable answer. Few people understood what was going on.