Nevada Gives Green Light to Self-Driving Cars. Last week, the state of Nevada passed a bill that will require its state Department of Motor Vehicles to draw up rules for self-driving cars, essentially paving the way for autonomous vehicles to be used on state roadways.
Section 8 of the law, which governs autonomous vehicles, will take effect on March 1, 2012. It was approved by Nevada Governor Brian Sandoval on June 16. Self-driving cars have been tested by Google since 2010, and most recently by Volkswagen, whose Temporary Auto Pilot (TAP) car is part of a research project in the EU, but with what the company describes as "production-ready" components. Nevada defines "autonomous vehicle" as a motor vehicle that uses artificial intelligence, sensors and global positioning system coordinates to drive itself without the active intervention of a human operator. The law does not mean that self-driving cars will instantly be "street legal" next year.
Lingodroid Robots Invent Their Own Spoken Language. When robots talk to each other, they're not generally using language as we think of it, with words to communicate both concrete and abstract concepts.
Now Australian researchers are teaching a pair of robots to communicate linguistically like humans by inventing new spoken words, a lexicon that the roboticists can teach to other robots to generate an entirely new language. Ruth Schulz and her colleagues at the University of Queensland and Queensland University of Technology call their robots the Lingodroids. The robots consist of a mobile platform equipped with a camera, laser range finder, and sonar for mapping and obstacle avoidance. The robots also carry a microphone and speakers for audible communication between them. To understand the concept behind the project, consider a simplified case of how language might have developed.
From this fundamental base, the robots can play games with each other to reinforce the language. AI's Time Has Arrived. Artificial Intelligence Goes Mobile. Artificial neural network. An artificial neural network is an interconnected group of nodes, akin to the vast network of neurons in a brain.
Here, each circular node represents an artificial neuron and an arrow represents a connection from the output of one neuron to the input of another. For example, a neural network for handwriting recognition is defined by a set of input neurons which may be activated by the pixels of an input image. After being weighted and transformed by a function (determined by the network's designer), the activations of these neurons are then passed on to other neurons. This process is repeated until finally, an output neuron is activated. Portal:Artificial intelligence. Artificial Intelligence Marketing. Artificial intelligence marketing (AIM) is a form of direct marketing leveraging database marketing techniques as well as AI concept and model such as machine learning and Bayesian Network.
The main difference resides in the reasoning part which suggests it is performed by computer and algorithm instead of human. Behavioral targeting[edit] Artificial intelligence marketing provides a set of tools and techniques that enable behavioral targeting. Collect, reason, act[edit] Artificial intelligence marketing principle is based on the perception-reasoning-action cycle you find in cognitive science. Collect[edit] Artificial intelligence: Can AI crack the conundrum of consciousness? Photos: AI enters the home and the workplace. Robots and Avatars. Documentation: Pathways | Gallery | Video | Vodcasts | Reports Robots and Avatars have produced a series of vodcasts which are available to view on this site.
Post: Ringing In the Answers. Watson, Turing, and extreme machine learning. One of best presentations at IBM’s recent Blogger Day was given by David Ferrucci, the leader of the Watson team, the group that developed the supercomputer that recently appeared as a contestant on Jeopardy.
To many people, the Turing test is the gold standard of artificial intelligence. Put briefly, the idea is that if you can’t tell whether you’re interacting with a computer or a human, a computer has passed the test. But it’s easy to forget how subtle this criterion is. Turing proposes changing the question from “Can machines think?” 6 Mashups of Music and Artificial Intelligence. If there is one thing computers do well, it’s math.
All of music’s raw components — key, mode, melody, harmony and rhythm — can be expressed mathematically. As a result, computers can help people make music, even if they don’t know their elbow from an F clef. The following apps for computer, web browser and smartphone put the power of artificially intelligent music creation in your hands or let you hear music that was created or manipulated by machines. Without further ado: uJam One of the most impressive demonstrations I’ve seen this year, uJam is the brainchild of longtime audio-software developers Peter Gorges and Axel Hensen and their celebrity partners Hans Zimmer (film composer for Dark Knight, Gladiator, Lion King) and Pharrell Williams (producer for Madonna, Shakira, Gwen Stefani). Following the freemium model, uJam will be free to use on a basic level, with add-ons available for purchase.
Emily Howell You can’t use the artificially intelligent Emily Howell software yourself. Steve Steinberg on weak AI. Steve Steinberg, former Legion of Doom member and current Wall Street hacker, posted a rare update to his .CSV blog, and it's a doozy.
He unpacks two big developments in "weak" artificial intelligence that manage to slip under the radar, mostly because they don't involve emotional robots or bring The Singularity a few days closer. Along the way, he shreds insurance companies that seek to correlate bad credit with bad driving, and pokes at Google's trust of "man over machine," a "cultural quirk," as Steve puts it, that's overlooked amidst all the talk of algorithms and massive data sets.
From .CSV: While strong AI still lies safely beyond the Maes-Garreau horizon (a vanishing point, perpetually fifty years ahead) a host of important new developments in weak AI are poised to be commercialized in the next few years. Most significant present-day AI developments. Singularity Institute for Artificial Intelligence. The Machine Intelligence Research Institute (MIRI) is a non-profit organization founded in 2000 to research safety issues related to the development of Strong AI.
The organization advocates ideas initially put forth by I. J. Good and Vernor Vinge regarding an "intelligence explosion", or Singularity, which MIRI thinks may follow the creation of sufficiently advanced AI.[1] Research fellow Eliezer Yudkowsky coined the term Friendly AI to refer to a hypothetical super-intelligent AI that has a positive impact on humanity.[2] The organization has argued that to be "Friendly" a self-improving AI needs to be constructed in a transparent, robust, and stable way.[3] MIRI was formerly known as the Singularity Institute, and before that as the Singularity Institute for Artificial Intelligence. History[edit] In 2003, the Institute appeared at the Foresight Senior Associates Gathering, where co-founder Eliezer Yudkowsky presented a talk titled "Foundations of Order".
Usefulness[edit] See also[edit] Ai Research - Creating a new form of life.