23 Matching Annotations
  1. Dec 2019
  2. Oct 2019
    1. We live in an age of paradox. Systems using artificial intelligence match or surpass human level performance in more and more domains, leveraging rapid advances in other technologies and driving soaring stock prices. Yet measured productivity growth has fallen in half over the past decade, and real income has stagnated since the late 1990s for a majority of Americans. Brynjolfsson, Rock, and Syverson describe four potential explanations for this clash of expectations and statistics: false hopes, mismeasurement, redistribution, and implementation lags. While a case can be made for each explanation, the researchers argue that lags are likely to be the biggest reason for paradox. The most impressive capabilities of AI, particularly those based on machine learning, have not yet diffused widely. More importantly, like other general purpose technologies, their full effects won't be realized until waves of complementary innovations are developed and implemented. The adjustment costs, organizational changes and new skills needed for successful AI can be modeled as a kind of intangible capital. A portion of the value of this intangible capital is already reflected in the market value of firms. However, most national statistics will fail to capture the full benefits of the new technologies and some may even have the wrong sign

      This is for anyone who is looking deep in economics of artificial intelligence or is doing a project on AI with respect to economics. This paper entails how AI might effect our economy and change the way we think about work. the predictions and facts which are stated here are really impressive like how people 30 years from now will be lively with government employment where everyone will get equal amount of payment.

  3. Jun 2019
  4. May 2019
  5. Oct 2018
    1. We opt for an embedding method, since wehypothesize less independent behaviors than individuals inthe system. Embedding methods are especially adapted toproducepersonalizedpredictions (e.g. collaborative filteringapplications), by making the assumption that the behaviorfrom an individual can be predicted by collecting data frommany users

      choice of embedding methods

  6. Sep 2018
    1. We’ve got lots of telephones already. Can’t you think of anything else for your birthday? Something very special?

      This part of the dialogue creates a good view of how consumerism will be just as prominent as today if not more. when he says we've got a lot of telephones, it might suggest that they are extremely reliant on technology so in a sense the movie had correctly predicted our current addiction and reliance on mobile phones.

  7. Mar 2018
    1. But I lived, and was to live for ever!

      Maybe it's because he only drank half that he is (maybe) starting to age now.

  8. Oct 2017
    1. All our steps in creating or absorbing material of the record proceed through one of the senses—the tactile when we touch keys, the oral when we speak or listen, the visual when we read. Is it not possible that some day the path may be established more directly?

      Throughout reading this article I couldn't help but laugh at the dramatic irony of our experience as students in 2017 reading Bush's predictions for the future of mechanics and technology in 1991. He speaks with a bit of wonderment, obviously trying to shock the reader with ideas considered fantastical at the time and then undermining them as "not so fantastic;" the joke of course being that even his most fantastic ideas seem rudimentary to us. That is, until I reached this part of the article, where Bush's predictions seem to have closely aligned with those of our own in the modern era. In this quote he seems to suggest a total departure from the tactile, oral, visual, and so on. Whether explicitly or not, Bush is referencing transcendence of machine (mechanical or digital) which, when you think about it, is a "fantastic" notion even by our standards of technology in 2017.

  9. Sep 2017
    1. customer relations, where live emotion estimation could be used when a customer phones into a call center.

      Mark Andrejevic has an interesting article about this kind of cross-over between homeland security and fields like marketing and advertising. He calls the use of emotional data in sentiment analysis and predictive analytics "affective economics."

    1. His head being turned back, he passed a crook of the road, and looking forward again, beheld the figure of a man, in grave and decent attire, seated at the foot of an old tree. He arose, at Goodman Brown's approach, and walked onward, side by side with him.

      The traveler could be a work acquaintance. In the 2 sentences afterwards, by context clues, they seem to know each other fair enough by not only name but also of Brown's wife whom in past text had said they're only 3 months married.

  10. Oct 2016
    1. She clenched her fists

      she is a little emotional. i think she will kill him.

    2. A cuckoo clock!

      I predict that it is not a normal cuckoo clock

  11. Jul 2016
    1. In April 1950, Charney’s group made a series of successful 24-hour forecasts over North America, and by the mid-1950s, numerical forecasts were being made on a regular basis.

      Roughly 50 years from initial efforts to first successful forecasts.

    2. Charney determined that the impracticality of Richardson’s methods could be overcome by using the new computers and a revised set of equations, filtering out sound and gravity waves in order to simplify the calculations and focus on the phenomena of most importance to predicting the evolution of continent-scale weather systems.

      The complexity of the forecasting problem was initially overcome in the 1940's both by an improved rate of calculation (using computers) and by simplifying the models to focus on the most important factors.

    3. Courageously, Richardson reported his results in his book Weather Prediction by Numerical Process, published in 1922.

      Despite failing to predict the weather accurately, Richardson posted his results publicly. This is an important step in allowing the improvement of forecasting because it makes it possible to learn what works and what doesn't more quickly. See also Brian McGill's 6th P of Good Prediction

    4. Despite the advances made by Richardson, it took him, working alone, several months to produce a wildly inaccurate six-hour forecast for an area near Munich, Germany. In fact, some of the changes predicted in Richardson’s forecast could never occur under any known terrestrial conditions.

      Nice concise description of the poor performance and impracticality of early weather forecasting.

  12. Jun 2016
  13. Feb 2016
    1. we predicted that there would be diagnosis-by-sex interactions in subcortical structures rich in sex hormone receptors, particularly in the amygdala and hippocampus.
    2. we predicted, based on previous reports, that youths with BPD would have abnormal NA volumes22,23 and that youths with SZ would have reduced thalamic volumes.24,33 We also predicted that the BPD with psychosis group would share features with the BPD without psychosis and the primary psychotic disorder groups