My working hypothesis to explain the 21st century is that the Tofflers underestimated how pervasive future shock would be. I think somewhere in the range from 15-30% of our fellow hairless primates are currently in the grip of future shock, to some degree. Symptoms include despair, anxiety, depression, disorientation, paranoia, and a desperate search for certainty in lives that are experiencing unpleasant and uninvited change. It’s no surprise that anyone who can offer dogmatic absolute answers is popular, or that the paranoid style is again ascendant in American politics, or that religious certainty is more attractive to many than the nuanced complexities of scientific debate. Climate change is an exceptionally potent trigger for future shock insofar as it promises an unpleasant and unpredictable dose of upcoming instability in the years ahead; denial is an emotionally satisfying response to the threat, if not a sustainable one in the longer term.
all the hysteria and religious nonsense means we are in profound future shock.
The phone itself was a pretty big deal, of course, helping intimacy transcend proximity. But phone books provided a crucial element to the system: intrusiveness. In the beginning of 1880, Shea writes, there were 30K telephone subscribers in the US At the end of the year, that number had grown to 50K, and because of phone books, each one of them was exposed to the others as never before. While many American cities had been compiling databases of their inhabitants well before the phone was invented, listing names, occupations, and addresses, individuals remained fairly insulated from each other. Contacting someone might require a letter of introduction, a facility for charming butlers or secretaries, a long walk.
If I had to choose overarching themes for white people’s lists, for men, I’d go with “frat house” and for women, “escapism.” Whether one begot the other is a question I’ll leave to the reader.
jealousy: you can’t undertake technical means to outlive your partner.
Peggy’s initial response to this ambition, rooted less in scientific skepticism than in her personal judgments about the quest for immortality, has changed little in the past 20-odd years. Robin, a deep thinker most at home in thought experiments, believes that there is some small chance his brain will be resurrected, that its time in cryopreservation will be merely a brief pause in the course of his life. Peggy finds the quest an act of cosmic selfishness.
To understand why this technology is so important, and so dangerous, you need to understand its patrimony. First, although the technology is brand new, the idea is a classic, long-time geek trope. It shows up, for example, in Isaac Asimov’s Foundation Trilogy, the best-selling albeit thinly-plotted space opera, in which protagonist Hari Seldon develops the science of “psychohistory”. Just as physics can predict the mass motion of a gas, even though any individual molecule is unpredictable, psychohistory allows us to predict the future of large groups of people. (It’s not hard to see why this sort of thing appeals to the socially maladroit. Forming cliques, establishing social ties– it’s complicated and messy stuff. If only there was a mathematics that laid it all out…)
But why is this technology only emerging now, not 15 or 20 years ago? For any technology, there are only 3 possible answers to this question: Moore’s law, the Internet, or the government. In the case of crowd dynamics, we have the last 2 to thank. The Internet has made the problem tractable by providing huge, easily-collected data sets of social interactions. But the government has been the real enabler. Just follow the money: nearly every relevant research project received funding from DARPA, the Defense Advanced Research Projects Agency.
the state of “human terrain” research, and its applications. shades of psychohistory.
This will be fun to watch. And to witness the drama and handwringing of the dilettante press.
For the last 3 years, IBM scientists have been developing what they expect will be the world’s most advanced “question answering” machine, able to understand a question posed in everyday human elocution — “natural language,” as computer scientists call it — and respond with a precise, factual answer. In other words, it must do more than what search engines like Google and Bing do, which is merely point to a document where you might find the answer. It has to pluck out the correct answer itself. Technologists have long regarded this sort of artificial intelligence as a holy grail, because it would allow machines to converse more naturally with people, letting us ask questions instead of typing keywords. Software firms and university scientists have produced question-answering systems for years, but these have mostly been limited to simply phrased questions. Nobody ever tackled “Jeopardy!” because experts assumed that even for the latest artificial intelligence, the game was simply too hard: the clues are too puzzling and allusive, and the breadth of trivia is too wide.
In a canned demo, Kelly chose a sample debate topic: “The sale of violent video games to minors should be banned.” The Debater was tasked with presenting pros and cons for a debate on this question. Speaking in nearly perfect English, Watson/The Debater replied: Scanned 4 million Wikipedia articles, returning 10 most relevant articles. Scanned all 3000 sentences in top 10 articles. Detected sentences which contain candidate claims. Identified borders of candidate claims. Assessed pro and con polarity of candidate claims. Constructed demo speech with top claim predictions. Ready to deliver. It then presented 3 relevant pros and cons.
2014-10-07: If the process of science itself can be changed from the current miasma of writing 19th century style papers, lack of negative results etc towards a process of discovery where all knowledge is like wikipedia, and AI infers new things, that’d be quite something.
Scientists demonstrated a possible new path for generating scientific questions that may be helpful in the long term development of new, effective treatments for disease. In a matter of weeks, biologists and data scientists using the Baylor Knowledge Integration Toolkit (KnIT), based on Watson technology, accurately identified proteins that modify p53, an important protein related to many cancers, which can eventually lead to better efficacy of drugs and other treatments. A feat that would have taken researchers years to accomplish without Watson’s cognitive capabilities, Watson analyzed 70k scientific articles on p53 to predict proteins that turn on or off p53’s activity. This automated analysis led the Baylor cancer researchers to identify 6 potential proteins to target for new research. These results are notable, considering that over the last 30 years, scientists averaged 1 similar target protein discovery per year.
Enter blueberries as the essential ingredient, click dessert and Watson recommends similar ingredients based on food pairing chemistry. After you’ve narrowed preferences down, Watson recommends brand-new cooking ideas, based on recipes Watson has studied. And users can go more deeply into the app too, modifying Watson’s modifications. Its website calls the human-computer partnership a tool to “amplify human creativity.”
vanity sizes come to d00d brands.
Gregor J. Rothfuss 