If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
I have commented before that the topic of AI Safety should be equally as much about ensuring the field of artificial intelligence is working for important goals such as climate change or reducing inequality. In this regard I find the UNDP strategy of interest. UNDP works to eradicate poverty and reduce inequalities through the sustainable development of nations. This mission is being carried out in more than 170 countries and territories. Quite recently the UNDP launched its digital strategy for 2019–2021.
The AI, Labor, and Economy Case Studies Compendium is a work product of the Partnership on AI's "AI, Labor, and the Economy" (AILE) Working Group, formed through a collaborative process of research scoping and iteration. Though this work product reflects the inputs of many members of PAI, it should not be read as representing the views of any particular organization or individual within this Working Group, or an entity within PAI at-large. The Partnership on AI (PAI) is a 501(c)3 nonprofit organization established to study and formulate best practices on AI technologies, to advance the public's understanding of AI, and to serve as an open platform for discussion and engagement about AI and its influences on people and society. One of PAI's significant program lines is a series of Working Groups reflective of its Thematic Pillars, which are a driving force in research and best practice generation. The Partnership's activities are deliberately determined by its coalition of over 80 members, including civil society groups, corporate users of AI, and numerous academic artificial intelligence research labs, but from the outset of the organization, the intention has been to create a place for open critique and reflection.
AI is capable of making music, but does that make AI an artist? As AI begins to reshape how music is made, our legal systems are going to be confronted with some messy questions regarding authorship. Do AI algorithms create their own work, or is it the humans behind them? What happens if AI software trained solely on Beyoncé creates a track that sounds just like her? "I won't mince words," says Jonathan Bailey, CTO of iZotope. "This is a total legal clusterfuck."
The techniques of deep learning have become the state of the art methodology for executing complicated tasks from various domains of computer vision, natural language processing, and several other areas. Due to its rapid development and promising benchmarks in those fields, researchers started experimenting with this technique to perform in the area of, especially in intrusion detection related tasks. Deep learning is a subset and a natural extension of classical Machine learning and an evolved model of neural networks. This paper contemplates and discusses all the methodologies related to the leading edge Deep learning and Neural network models purposing to the arena of Intrusion Detection Systems.
Whether an A.I. ought to be granted patent rights is a timely question given the increasing proliferation of A.I. in the workplace. Examples: Daimler-Benz has tested self-driving trucks on public roads, A.I. technology has been applied effectively in medical advancements, psycholinguistics, tourism and food preparation, a film written by an A.I. recently debuted online and A.I. has even found its way into the legal profession, and current interest in the question of whether an A.I. can enjoy copyright rights with several articles having already being published on the subject of A.I. and copyright rights. In 2014 the U.S. Copyright Office updated its Compendium of U.S. Copyright Office Practices with, inter alia, a declaration that the Office will not register works produced by a machine or mere mechanical process that operates randomly or automatically without any creative input or intervention from a human author." One might argue that Intellectual Property (IP) laws and IP Rights were designed to exclusively benefit human creators and inventors and thus would exclude non-humans from holding IP rights. The U.S. Copyright Office's December 2014 update to the Compendium of U.S. Copyright Office Practices that added requirements for human authorship certainly adds weight to this view.
CVonline is a resource for computer vision, machine vision, image analysis and some visual psychophysics and visual neurophysiology. Because of the improvements in the content available in Wikipedia, it is now possible to find about 1000 of the 2000 topics in CVonline. We had originally tried to create the hierarchy of CVonline inside Wikipedia so that the community could edit the structure. However, the pages were deleted. If you try to develop content in wikipedia, you might be interested in some of the problems that you will encounter.
This week's gaming news is only suitable for the comically rich. Preorder tickets to the Assassin's Creed film for 1,200, preorder OmniBus and get a real bus, and Croteam announced Talos Principle 2. Okay, that last one is fine for not-so-rich people too, as long as pondering philosophy won't throw you into an existential crisis. It's time for another iteration of "Raise money for The International," with Valve's special guest: The Compendium. For the unaware: The International is Valve's big annual Dota 2 tournament, and The Compendium is a Dota 2 item that ties into viewing the tournament in a few major ways, gives players some items, and--key to the whole thing--helps fund the prize pool for the winning teams. Last year's prize pool topped 18 million.
Nadjet Bouayad-Agha Information Technology Research Institute University of Brighton (U.K.) firstname.lastname@example.org Abstract In this paper, we report on the task of annotating the logical structure in a corpus of information leaflets. We discuss some problems for identifying this structure in that particular genre. We argue that there is a need to understand better the communicative functions of layout in that genre. Introduction This paper discusses the issues raised by the annotation of the logical structure of information leaflets. The annotated corpus is to be used for the investigation of the role of layout in the text production process, from content selection and organisation to wording, the results of which is to be integrated in a generation system producing such documents.