Who will be the next Swiss Federal Councillor - Final update
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Tomorrow Sept 16 will be the elections for next Swiss Federal Councillor in succession of Pascal Couchepin. Here the latest coolhunting results on the blogs for the four main candidates:
Why do people collaboratively engage in innovative tasks? What’s the motivation to work together to develop something new? After all, if I do everything by myself, I will reap all the rewards for myself, and don’t have to share. Nevertheless, humans are the most social species of all, and progress is only possible by collectively creating new things “standing on the shoulders of giants”, by learning from what others have done, and apply it in novel ways. According to my colleagues at the MIT Center for Collective Intelligence Tom Malone , Rob Laubacher , and Chris Dellarocas there are three main reasons why people engage in collective intelligence systems: Money – financial gain is a strong motivator for people participating in markets and traditional organizations, either for direct payment, or for future payment, e.g. acquiring new skills. Glory – getting recognition and building up a reputation can be an important motivator. Love – love can be an important motivator, be it beca
The developers of ChatGPT built extremely useful software, putting a “Wikipedia on steroids” at our fingertips by leveraging collective intelligence in ways never seen before. In this sense, as defined by Plato and Aristotle over two thousand years ago, they are “good people”. This means they are morally good or virtuous by giving away a highly beneficial software product for free that makes many chores of the daily life of knowledge workers much easier. These AI developers are thus acting according to the golden rule (of reciprocity), treating others as they would like to be treated. The problem is that not everybody who writes AI software is a “good” person. If only one percent of AI developers acts entirely egoistic, or even malicious, there is the risk that these “bad apples” will abuse the power of AI for their own sinister purposes, without any consideration for the wellbeing of the rest of us. But what if we could turn the power of AI on these “bad apples”, to identify them be
We have been working on trying to predict market indicators for quite some time by analyzing Web Buzz , predicting who will win an Oscar, or how well movies do at the box office . Among other things we have correlated posts about a stock on Yahoo Finance and Motley’s Fool with the actual stock price, predicting the closing price of the stock on the next day based on what people say today on Yahoo Finance, on the Web and Blogs about a stock title. The rising popularity of twitter gives us a new great way of capturing the collective mind up to the last minute. In our current project we analyze the positive and negative mood of the masses on twitter, comparing it with broad stock market indices such as Dow Jones, S&P 500, and NASDAQ. We collected the twitter feeds from one whitelisted IP for six months from March 30, 2009 to Sept 4, 2009, ranging from 5680 to 42820 tweets per day. According to twitter this corresponds to a randomized subsample of about one hundredth of the full volum
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