Archive for the ‘Science fiction’ Category
I just did it. Amazing. Register at website (just name and email), they email you a link, click it, and you are presented with a list of various ebook formats (so I chose “Kindle”), then I specified which type of Kindle I had, then they gave me the URL to enter in the Kindle’s Experimental Browser. I did, saw book with instruction to touch cover to download. I touched the cover and now have the book, instantly.
Now, when I was a boy…..
It is pretty amazing. Here’s the site of the company that has the ebook downloading service.
Good post by Jason Kottke, which begins:
1. A robot/computer cannot possibly do the tasks I do.
2. [Later.] OK, it can do a lot of those tasks, but it can’t do everything I do.
3. [Later.] OK, it can do everything I do, except it needs me when it breaks down, which is often.
4. [Later.] OK, it operates flawlessly on routine stuff, but I need to train it for new tasks. . . .
As readers of science fiction know, once AI really takes hold, the advances are quite rapid, leading to many good novels about the Synchronicity. Wired has an interesting article on the state of AI, unfortunately behind a paywall (at least for me, but after subscribing I read it). One interesting point from the article:
This summer, after building an AI that cracked the game of Go, Demis Hassabis and his Google DeepMind lab revealed they had also built an AI that helps operate Google’s worldwide network of computer data centers. Using a technique called deep reinforcement learning, which underpins both their Go-playing machine and earlier DeepMind services that learned to master old Atari games, this AI decides when to turn on cooling fans inside the thousands of computer servers that fill these data centers, when to open the data center windows for additional cooling, and when to fall back on expensive air conditioners. All told, it controls over 120 functions inside each data center
As Bloomberg reported, this AI is so effective, it saves Google hundreds of millions of dollars. In other words, it pays for the cost of acquiring DeepMind, which Google bought for about $650 million in 2014. Now, Deepmind plans on installing additional sensors in these computing facilities, so it can collect additional data and train this AI to even higher levels.
Gideon Lewis-Kraus writes in the NY Times Magazine:
Four days later, a couple of hundred journalists, entrepreneurs and advertisers from all over the world gathered in Google’s London engineering office for a special announcement. Guests were greeted with Translate-branded fortune cookies. Their paper slips had a foreign phrase on one side — mine was in Norwegian — and on the other, an invitation to download the Translate app. Tables were set with trays of doughnuts and smoothies, each labeled with a placard that advertised its flavor in German (zitrone), Portuguese (baunilha) or Spanish (manzana). After a while, everyone was ushered into a plush, dark theater.
Sadiq Khan, the mayor of London, stood to make a few opening remarks. A friend, he began, had recently told him he reminded him of Google. “Why, because I know all the answers?” the mayor asked. “No,” the friend replied, “because you’re always trying to finish my sentences.” The crowd tittered politely. Khan concluded by introducing Google’s chief executive, Sundar Pichai, who took the stage.
Pichai was in London in part to inaugurate Google’s new building there, the cornerstone of a new “knowledge quarter” under construction at King’s Cross, and in part to unveil the completion of the initial phase of a company transformation he announced last year. The Google of the future, Pichai had said on several occasions, was going to be “A.I. first.” What that meant in theory was complicated and had welcomed much speculation. What it meant in practice, with any luck, was that soon the company’s products would no longer represent the fruits of traditional computer programming, exactly, but “machine learning.”
A rarefied department within the company, Google Brain, was founded five years ago on this very principle: that artificial “neural networks” that acquaint themselves with the world via trial and error, as toddlers do, might in turn develop something like human flexibility. This notion is not new — a version of it dates to the earliest stages of modern computing, in the 1940s — but for much of its history most computer scientists saw it as vaguely disreputable, even mystical. Since 2011, though, Google Brain has demonstrated that this approach to artificial intelligence could solve many problems that confounded decades of conventional efforts. Speech recognition didn’t work very well until Brain undertook an effort to revamp it; the application of machine learning made its performance on Google’s mobile platform, Android, almost as good as human transcription. The same was true of image recognition. Less than a year ago, Brain for the first time commenced with the gut renovation of an entire consumer product, and its momentous results were being celebrated tonight.
Translate made its debut in 2006 and since then has become one of Google’s most reliable and popular assets; it serves more than 500 million monthly users in need of 140 billion words per day in a different language. It exists not only as its own stand-alone app but also as an integrated feature within Gmail, Chrome and many other Google offerings, where we take it as a push-button given — a frictionless, natural part of our digital commerce. It was only with the refugee crisis, Pichai explained from the lectern, that the company came to reckon with Translate’s geopolitical importance: On the screen behind him appeared a graph whose steep curve indicated a recent fivefold increase in translations between Arabic and German. (It was also close to Pichai’s own heart. He grew up in India, a land divided by dozens of languages.) The team had been steadily adding new languages and features, but gains in quality over the last four years had slowed considerably.
Until today. As of the previous weekend, Translate had been converted to an A.I.-based system for much of its traffic, not just in the United States but in Europe and Asia as well: The rollout included translations between English and Spanish, French, Portuguese, German, Chinese, Japanese, Korean and Turkish. The rest of Translate’s hundred-odd languages were to come, with the aim of eight per month, by the end of next year. The new incarnation, to the pleasant surprise of Google’s own engineers, had been completed in only nine months. The A.I. system had demonstrated overnight improvements roughly equal to the total gains the old one had accrued over its entire lifetime.
Pichai has an affection for the obscure literary reference; he told me a month earlier, in his office in Mountain View, Calif., that Translate in part exists because not everyone can be like the physicist Robert Oppenheimer, who learned Sanskrit to read the Bhagavad Gita in the original. In London, the slide on the monitors behind him flicked to a Borges quote: “Uno no es lo que es por lo que escribe, sino por lo que ha leído.”
Grinning, Pichai read aloud an awkward English version of the sentence that had been rendered by the old Translate system: “One is not what is for what he writes, but for what he has read.”
To the right of that was a new A.I.-rendered version: “You are not what you write, but what you have read.”
It was a fitting remark: The new Google Translate was run on the first machines that had, in a sense, ever learned to read anything at all.
Google’s decision to reorganize itself around A.I. was the first major manifestation of what has become an industrywide machine-learning delirium. Over the past four years, six companies in particular — Google, Facebook, Apple, Amazon, Microsoft and the Chinese firm Baidu — have touched off an arms race for A.I. talent, particularly within universities. Corporate promises of resources and freedom have thinned out top academic departments. It has become widely known in Silicon Valley that Mark Zuckerberg, chief executive of Facebook, personally oversees, with phone calls and video-chat blandishments, his company’s overtures to the most desirable graduate students. Starting salaries of seven figures are not unheard-of. Attendance at the field’s most important academic conference has nearly quadrupled. What is at stake is not just one more piecemeal innovation but control over what very well could represent an entirely new computational platform: pervasive, ambient artificial intelligence. . .
Interesting to read at this particular time in history, when it looks as though nations are going through the story cycle, nations being one of the stories we tell ourselves. (Cf. memes, which survive if they are replicated by others—that is, only if they are “catchy” in some way, so that more people are drawn into the meme. Darwinian evolution takes care of the rest.
Josh Jones posts at Open Culture:
Kurt Vonnegut’s 1963 novel Cat’s Cradle resembles its title, a web of overlapping and entangled stories, all of which have huge holes in the middle. And the book—as have many of his slim, surrealist pop masterpieces—was read by many critics as lightweight—whimsical and sentimental. One reviewer in The New York Review of Books, for example, called Vonnegut a “compiler of easy to read truisms about society who allows everyone’s heart to be in the right place.”
Not so, argues University of Puerto Rico scholar Mark Wekander Voigt. For all its silliness—such as its Calypso-heavy “parody of a modern invented religion that will make everyone happy”—Cat’s Cradle, writes Voigt, “is essentially about the moral issues involved in a democratic government using the atom bomb.” Vonnegut’s novel suggests that “to be really ethical, to think about right and wrong, means that we must dispense with the authorities who tell us what is right and wrong.”
John, the hero of Cat’s Cradle, begins his absurdist hero’s quest by intending to write a “factual” accounting of what “important Americans had done on the day when the first atomic bomb was dropped on Hiroshima, Japan.” The references would not have been lost on Vonnegut’s contemporary readers, who would all have been familiar with John Hersey’s harrowing 1946 Hiroshima, the most popular book ever written about the dropping of the bomb, with six survivor’s stories told in a thrilling, engaging style and “all the entertainment of a well-written novel.”
Vonnegut, however, writes an alienating anti-novel, in part to demonstrate his point that “to discuss the ethical implications of dropping the bomb on Hiroshima, one should not look at the victims, but at those who were involved in developing such a bomb and their government.” Increasingly, however, it becomes harder and harder to look at anything directly. In the novel’s parody religion, Bokononism, all lies are potentially truths, all truths potentially lies. Language in the military-industrial-complex world of the bomb, Vonnegut suggests, had become as changeable and potentially deadly as the substance called “Ice-9,” a polymorph of water that can instantly turn rivers, lakes, and even whole oceans into ice.
Evoking the novel’s high-wire balancing act of goofy songs and rituals and metaphors for the global annihilation of the earth by nuclear weapons, the 2001 album above [in post at the link – LG[, Ice-9 Ballads, pairs Vonnegut with composer Dave Soldier and the Manhattan Chamber orchestra for an adaptation, of sorts, of Cat’s Cradle.. . .
I would not be surprised to see an uptick in Vonnegut’s popularity over the next few years.