Outline of artificial intelligence The following outline is provided as an overview of and topical guide to artificial intelligence: Artificial intelligence (AI) – branch of computer science that deals with intelligent behavior, learning, and adaptation in machines. Research in AI is concerned with producing machines to automate tasks requiring intelligent behavior. Branches of artificial intelligence[edit] Some applications of artificial intelligence[edit] Philosophy of artificial intelligence[edit] Philosophy of artificial intelligence Artificial intelligence and the future[edit] Strong AI – hypothetical artificial intelligence that matches or exceeds human intelligence — the intelligence of a machine that could successfully perform any intellectual task that a human being can. History of artificial intelligence[edit] Main article: History of artificial intelligence Artificial intelligence in fiction[edit] Main article: Artificial intelligence in fiction Psychology and AI[edit] Concepts in artificial intelligence[edit] 1970s[edit]
Some Thoughts On The Future Of Siri [Opinion We’ve seen the first rash of iPhone 4 reviews coming in, and they all agree on one thing: Siri is very impressive. It works because it does several things all at once. It understands what you’re saying, irrespective of your accent, and without a lot of initial training. And it understands what you mean, because it has the built-in smarts to know that if you say “Tell my wife I’m running late,” you mean “Send a text message to this particular contact with text that says I’m running late.” But this is just the start for Siri (which Apple’s acknowledged by calling it a beta). First, let’s think about new features it might support on the iPhone 4S. So the first, most immediate, improvements we can expect for Siri are a broadening of the databases it knows about and can query. Then there’s the possibility of opening Siri up to other applications on the device. How about in games? Finally, expansion beyond the iPhone 4S. I suspect yes, but for different purposes. Over to you. Related
Araucaria (software) The user interface is composed of a main window (diagramming), a schemes editor and the AraucariaDB online interface. While Araucaria helps identify the structure of an argument, it provides freedom of analysis resources. The scheme editor allows the user to create argumentation schemes, group them together and save them into a scheme set file. The AraucariaDB Online Repository can be browsed to retrieve specific arguments to fit a diagram. Because it is based on XML, a standard widely used by developers, AML content can be accessed through other software that support XML.
Our Fear of Artificial Intelligence Years ago I had coffee with a friend who ran a startup. He had just turned 40. His father was ill, his back was sore, and he found himself overwhelmed by life. “Don’t laugh at me,” he said, “but I was counting on the singularity.” My friend worked in technology; he’d seen the changes that faster microprocessors and networks had wrought. But what if it wasn’t so benevolent? No worries, you might say: you could just program it to make exactly a million paper clips and halt. Things Reviewed “Superintelligence: Paths, Dangers, Strategies” By Nick Bostrom Oxford University Press, 2014 Bostrom does not believe that the paper-clip maximizer will come to be, exactly; it’s a thought experiment, one designed to show how even careful system design can fail to restrain extreme machine intelligence. If this sounds absurd to you, you’re not alone. Yet a lot of smart, thoughtful people agree with Bostrom and are worried now. Volition The question “Can a machine think?” Insurance policy
Artificial intelligence AI research is highly technical and specialized, and is deeply divided into subfields that often fail to communicate with each other.[5] Some of the division is due to social and cultural factors: subfields have grown up around particular institutions and the work of individual researchers. AI research is also divided by several technical issues. Some subfields focus on the solution of specific problems. The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects.[6] General intelligence is still among the field's long-term goals.[7] Currently popular approaches include statistical methods, computational intelligence and traditional symbolic AI. The field was founded on the claim that a central property of humans, intelligence—the sapience of Homo sapiens—"can be so precisely described that a machine can be made to simulate it History[edit]
Developing an Outline Summary: This resource describes why outlines are useful, what types of outlines exist, suggestions for developing effective outlines, and how outlines can be used as an invention strategy for writing. Contributors:Elyssa Tardiff, Allen BrizeeLast Edited: 2013-03-01 09:20:56 Ideally, you should follow the four suggestions presented here to create an effective outline. When creating a topic outline, follow these two rules for capitalization: For first-level heads, present the information using all upper-case letters; and for secondary and tertiary items, use upper and lower-case letters. Parallelism—How do I accomplish this? Each heading and subheading should preserve parallel structure. ("Choose" and "Prepare" are both verbs. Coordination—How do I accomplish this? All the information contained in Heading 1 should have the same significance as the information contained in Heading 2. (Campus and Web sites visits are equally significant. Subordination—How do I accomplish this?
Argument map Visual representation of the structure of an argument Argument maps are commonly used in the context of teaching and applying critical thinking.[2] The purpose of mapping is to uncover the logical structure of arguments, identify unstated assumptions, evaluate the support an argument offers for a conclusion, and aid understanding of debates. Argument maps are often designed to support deliberation of issues, ideas and arguments in wicked problems.[3] A number of different kinds of argument maps have been proposed but the most common, which Chris Reed and Glenn Rowe called the standard diagram,[5] consists of a tree structure with each of the reasons leading to the conclusion. There is no consensus as to whether the conclusion should be at the top of the tree with the reasons leading up to it or whether it should be at the bottom with the reasons leading down to it.[5] Another variation diagrams an argument from left to right.[6] According to Douglas N. [edit] Diagramming written text
Artificial Intelligence Use one of the services below to sign in to PBS: You've just tried to add this video to your Watchlist so you can watch it later. But first, we need you to sign in to PBS using one of the services below. You’ll be able to manage videos in your Watchlist, keep track of your favorite shows, watch PBS in high definition, and much more! You've just tried to select this program as one of your favorites. To get you watching PBS in high definition we need you to sign in to PBS using one of the services below. You'll be able to manage videos in your Watchlist, keep track of your favorite shows, watch PBS in high definition, and much more! Don’t have a PBS Account? Creating an account is free and gets you: Access to High-Definition streamingA personal area on the site where you can access: Favorite ShowsWatchlistViewing HistoryEarly access to exciting new features
artifical intelligence diagram How to Write an A+ Research Paper This Chapter outlines the logical steps to writing a good research paper. To achieve supreme excellence or perfection in anything you do, you need more than just the knowledge. Like the Olympic athlete aiming for the gold medal, you must have a positive attitude and the belief that you have the ability to achieve it. Choose a topic which interests and challenges you. Focus on a limited aspect, e.g. narrow it down from "Religion" to "World Religion" to "Buddhism". Select a subject you can manage. Surf the Net. For general or background information, check out useful URLs, general information online, almanacs or encyclopedias online such as Britannica. Pay attention to domain name extensions, e.g., .edu (educational institution), .gov (government), or .org (non-profit organization). The recent arrival of a variety of domain name extensions such as .biz (commercial businesses), .pro, .info (info on products / organizations), .name, .ws (WebSite), .cc (Cocos Island) or .sh (St. I. I. 1. 1.
Artificial intelligence in video games AI used for video games, usually non-player characters In video games, artificial intelligence (AI) is used to generate responsive, adaptive or intelligent behaviors primarily in non-playable characters (NPCs) similar to human-like intelligence. Artificial intelligence has been an integral part of video games since their inception in the 1948, first seen in the game Nim.[1] AI in video games is a distinct subfield and differs from academic AI. It serves to improve the game-player experience rather than machine learning or decision making. During the golden age of arcade video games the idea of AI opponents was largely popularized in the form of graduated difficulty levels, distinct movement patterns, and in-game events dependent on the player's input. Modern games often implement existing techniques such as pathfinding and decision trees to guide the actions of NPCs. Many industries and corporate voices[who?] People[who?] In computer simulations of board games [edit] In modern video games
The Impact of Artificial Intelligence on R&D and Innovation For the past couple of centuries, general-purpose technologies have been the key drivers of productivity and economic growth. The steam engine, electricity and the internal combustion engine are prominent examples of GPTs in the 18th and 19th century. More recently, semiconductors, computers and the internet have led to the digital revolution of the past several decades. Beyond innovations in existing sectors, the rapidly improving price/performance of GPTs have led over time to the creation of whole new applications and industries. How about artificial intelligence? Last year I heard a simple, compelling explanation for AI as a GPT at a seminar by University of Toronto Professor Avi Goldfarb, who along with colleagues has been conducting research on the economics of machine intelligence. The computer revolution can be viewed as being all about the dramatic reductions in the cost of arithmetic calculations.