Artificial Intelligence, Automation, and the Economy | whitehouse.gov Editor’s Note: Staff from the Council of Economic Advisers, the Domestic Policy Council, the National Economic Council, the Office of Management and Budget, the Office of Science and Technology Policy contributed to this post. Today, in order to ready the United States for a future in which artificial intelligence (AI) plays a growing role, the White House released a report on Artificial Intelligence, Automation, and the Economy. This report follows up on the Administration’s previous report, Preparing for the Future of Artificial Intelligence, which was released in October 2016, and which recommended that the White House publish a report on the economic impacts of artificial intelligence by the end of 2016. Accelerating AI capabilities will enable automation of some tasks that have long required human labor. AI-driven automation will transform the economy over the coming years and decades. The report details what can be done to execute on these strategies.
Matter and Energy: A False Dichotomy | Of Particular Significance Matt Strassler [April 12, 2012] It is common that, when reading about the universe or about particle physics, one will come across a phrase that somehow refers to “matter and energy”, as though they are opposites, or partners, or two sides of a coin, or the two classes out of which everything is made. This comes up in many contexts. As a scientist and science writer, this phraseology makes me cringe a bit, not because it is deeply wrong, but because such loose talk is misleading to non-scientists. On this website I try to be more precise, in order to help the reader avoid the confusions that arise from this way of speaking. Summing Up This article is long, but I hope it is illuminating and informative for those of you who want details. Matter and Energy really aren’t in the same class and shouldn’t be paired in one’s mind.Matter, in fact, is an ambiguous term; there are several different definitions used in both scientific literature and in public discourse. The word Matter. Matter vs.
Explaining nonlinear classification decisions with deep Taylor decomposition Open Access Highlights A novel method to explain nonlinear classification decisions in terms of input variables is introduced. The method is based on Taylor expansions and decomposes the output of a deep neural network in terms of input variables. The resulting deep Taylor decomposition can be applied directly to existing neural networks without retraining. The method is tested on two large-scale neural networks for image classification: BVLC CaffeNet and GoogleNet. Abstract Nonlinear methods such as Deep Neural Networks (DNNs) are the gold standard for various challenging machine learning problems such as image recognition. Keywords Deep neural networks; Heatmapping; Taylor decomposition; Relevance propagation; Image recognition 1. Nonlinear models have been used since the advent of machine learning (ML) methods and are integral part of many popular algorithms. 1.1. There has been a significant body of work focusing on the analysis and understanding of nonlinear classifiers.
Welcome to the SICP Web Site Wizard Book n. Hal Abelson's, Jerry Sussman's and Julie Sussman's Structure and Interpretation of Computer Programs (MIT Press, 1984; ISBN 0-262-01077-1), an excellent computer science text used in introductory courses at MIT. So called because of the wizard on the jacket. One of the bibles of the LISP/Scheme world. Also, less commonly, known as the Purple Book. from The New Hacker's Dictionary, 2nd edition (MIT Press, 1993) This site is a companion to the influential computer-science text Structure and Interpretation of Computer Programs, by Abelson, Sussman, and Sussman. Comments or questions Contact Us.
What Does it Mean to Prepare Students For a Future With Artificial Intelligence? Last year, in the height of the election season, the Obama administration quietly released a national strategic plan for artificial intelligence (AI) research and development. The plan was the beginning of a national effort to prepare Americans for a future with AI—a future some computer scientist believe our nation is ill-equipped to handle. AI has become a part of the American fabric for some time. Siri and Alexa are already taking orders, self-driving cars have hit some streets, and the concept of interconnectivity is now a reality through the Internet of Things. But experts assert that in order for the society to fully embrace AI, learning machines should not replace human workers, but complement them. So to prepare the future workforce for a computer coworker, there must be a shift in teaching and learning—a change that should begin in the classroom. Step 1: Demystifying Artificial Intelligence Dr. Step 2: Understand Everyone’s Role, AI is Not Just For Computer Scientists
The 3 Best Free OCR Tools to Convert Your Files Back Into Editable Documents Believe it or not, some people still print documents on physical pieces of paper. Optical Character Recognition (OCR) software takes those printed documents and converts them right back into machine-readable text. We’ve found some of the best free OCR tools and compared them for you here. No OCR program is perfect, so you’ll have to check the results and fix a few problems. To compare these tools, I took a screenshot of MakeUseOf’s Privacy page and saved it as a JPG file. Then, I used that JPG to test out the following OCR services. However, you could also scan a printed document if that’s what you want to edit. If you go that route, it’ll work best if the page features common fonts, such as Times New Roman or Arial. Now, let’s dig in! Google Drive & Google Docs Google Drive has integrated OCR support. To get started, save the picture you want to send through the OCR to your computer. Next, open the Google Drive website and upload your file into the application. Microsoft Document Imaging
It's no Christmas No 1, but AI-generated song brings festive cheer to researchers | Technology It will not, if there is any certainty left in the world, top the charts this Christmas. But what it lacks in party hit potential, it more than makes up for with its unique, if vaguely unsettling, brand of festive cheer. To be fair, humans had very little hand in penning the song. Instead, scientists fed a Christmassy photograph into a computer and let it do its thing. A program analysed the image, whipped up some relevant lyrics, and then sang them to music it had composed along the way. Known to its creators as “neural karaoke”, the project from the University of Toronto can take any digital photo and transform it into a computer-generated singalong. “We are used to thinking about AI for robotics and things like that. Neural karaoke emerged from a broader research effort to use computer programs to make music, write lyrics and even generate dance routines. But computer-generated music was just the start.
GPG Subkeys Translation(s): English - Français - Italiano What are keys? In public key cryptography, a key is actually a pair: a public key, and a private key. You use the private key to digitally sign files, and others use the public key to verify the signature. Or, others use the public key to encrypt something, and you use the private key to decrypt it. As long as only you have access to the private key, other people can rely on your digital signatures being made by you, and you can rely on nobody else being able to read messages encrypted for you. GnuPG, the implementation used in Debian, picks the right key at any one time. What are subkeys? OpenPGP further supports subkeys, which are like the normal keys, except they're bound to a master key pair. In other words, subkeys are like a separate key pair, but automatically associated with your main key pair. GnuPG actually uses a signing-only key as the master key, and creates an encryption subkey automatically. Why? Subkeys make key management easier.
To spot a liar, look at their hands — Quartz In 1994, when I was prime minister of Sweden, I sent the first email between two heads of state. I had been discussing with Al Gore the development of what people at the time called, “The Internet Superhighway.” So I thought it would be a good idea to send an email to then-US president Bill Clinton. We waited for a reply, but we didn’t hear back. At that time, email was seen as revolutionary; 1994 was also the year the first commercial web browser appeared. Technology can be an enabler, but it can also create divisions. We need to have an inclusive global digital economy, but half of the world’s population remains offline. We need to have an inclusive global digital economy, but half of the world’s population remains offline. Sweden is a clear example of the way competition can drive prices down. On the other hand, one of the most extreme examples of cheap connectivity is Somalia, which has virtually no regulation and has some of the lowest prices for mobile communications in Africa.
pqi POWER Series 1GB (2 x 512MB) 184-Pin DDR SDRAM DDR 266 (PC 2100) Dual Channel Kit Desktop Memory - Desktop Memory Warranty, Returns, And Additional Information Warranty Limited Warranty period (parts): Lifetime Limited Warranty period (labor): Lifetime Read full details Return Policies Return for refund within: 30 daysReturn for replacement within: 30 days This item is covered by Newegg.com's Standard Return Policy. Through the Newegg EggXpert Review Program, Newegg invites its best reviewers, known as EggXperts, to post opinions about new and pre-release products to help their fellow customers make informed buying decisions.Click here for more details.
6 Easy Steps to Learn Naive Bayes Algorithm (with code in Python) This article was posted by Sunil Ray. Sunil is a Business Analytics and BI professional. Source for picture: click here Introduction Here’s a situation you’ve got into: You are working on a classification problem and you have generated your set of hypothesis, created features and discussed the importance of variables. What will you do? In this article, I’ll explain the basics of this algorithm, so that next time when you come across large data sets, you can bring this algorithm to action. Table of Contents What is Naive Bayes algorithm? To check out all this information, click here. Top DSC Resources
Top 7 PHP Security Blunders This article was written in 2005 and remains one of our most popular posts. If you’re keen to learn more about web security, you may find this recent article of great interest. PHP is a terrific language for the rapid development of dynamic Websites. It also has many features that are friendly to beginning programmers, such as the fact that it doesn’t require variable declarations. In this article, I’ll detail many of the common PHP programming mistakes that can result in security holes. Security is a process, not a product, and adopting a sound approach to security during the process of application development will allow you to produce tighter, more robust code. Unvalidated Input Errors One of — if not the — most common PHP security flaws is the unvalidated input error. As an example, you might write the following code to allow a user to view a calendar that displays a specified month by calling the UNIX cal command. $month = $_GET['month']; $year = $_GET['year']; if (!
Computer learns to recognize sounds by watching video In recent years, computers have gotten remarkably good at recognizing speech and images: Think of the dictation software on most cellphones, or the algorithms that automatically identify people in photos posted to Facebook. But recognition of natural sounds—such as crowds cheering or waves crashing—has lagged behind. That's because most automated recognition systems, whether they process audio or visual information, are the result of machine learning, in which computers search for patterns in huge compendia of training data. Sound recognition may be catching up, however, thanks to researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). Instead, the researchers trained the system on video. "Computer vision has gotten so good that we can transfer it to other domains," says Carl Vondrick, an MIT graduate student in electrical engineering and computer science and one of the paper's two first authors. "We did an experiment with Carl," Aytar says. Visual language