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) …
Once upon a time if I wanted to find my way to somewhere unfamiliar, I would have pulled out a map and plotted my route. These days I just put the destination into my smartphone and let it make all the decisions. Is this a simple, practical thing to do or, by relying on increasingly smarter phones, are we allowing them to make us, day by day, a little bit dumber? I've spent the last few days at an international conference on artificial intelligence pondering just this question. We were discussing, among other things, the effect that the rise of machine intelligence is having on our brains.
Artificial intelligence (AI) has a future tech reputation that can probably speak for itself, but did you know just how much of an impact it already has on your current life? Keeping spam out of your email box may be one of the more obvious (and welcome) AI integrations. If you're social media savvy, you probably don't take the appearance of coordinated advertising across most platforms to be coincidental. You might later raise an eyebrow when the ads you're seeing on the Internet seem relevant to a conversation you had with someone over a messenger application, but you're pretty sure the people you talk to on website chat boxes are actual people. Or, maybe all of these things are part of an AI-infused reality you've grown to know and accept.
In last week's post, we discussed if machine learning was right for your business. As part of that effort, I recently went through the process of learning the ins-and-outs of machine learning and realized most information out there is technical and aimed at developers or data scientists. I thought an explanation from a non-technical person might be of interest. Machine learning is "[…] the branch of AI that explores ways to get computers to improve their performance based on experience". Let's break that down to set some foundations on which to build our machine learning knowledge.
Duplex is something that can make phone calls to create any meeting like a salon session or a restaurant booking for you by phoning those places, communicating with an individual and getting the work done. That demonstration drew a lot of laughs at the keynote, but following the dust settled, a lot of honest questions popped up because of how Duplex will try to fake being human being. The Google Duplex a fresh tool that aspires to use the technology of the Artificial intelligence (AI) to "accomplish real-world jobs over the telephone" relating to Google's developers and AI experts. For the present time, which means very specific responsibilities like making consultations, but the technology has been developed with a vision on enlargement into the areas. Spending billions to make a cool way to make meal reservations appears like something the company would do but is not a great use of the money, expertise and time.
This week's milestones in the history of technology include the coining of the term "artificial intelligence," the digitization of the Library of Congress, and the first penny paper. The first issue of Scientific American is published by Rufus Porter as a weekly broadsheet subtitled "The Advocate of Industry and Enterprise, and Journal of Mechanical and Other Improvements." In an era of rapid innovation, Scientific American founded the first branch of the U.S. Patent Agency, in 1850, to provide technical help and legal advice to inventors. A Washington, D.C., branch was added in 1859. By 1900 more than 100,000 inventions had been patented thanks to Scientific American.
There are still so many unanswered questions when it comes to the age of AI and how we can live with Artificially Intelligent machines and robots that may become more intelligent than us. How can we coexist comfortably and conveniently if one day, the machines we have created, decide to think for themselves? Do you believe in technological singularity and is it near? Here are some common ethical dilemmas we will have in the age of AI. An AI machine can be a computer or smart device and can also be known as a robot with or without appendages and can emulate human life physically.
The one risk-on strategy was the norm of the decade since the financial crisis bottom-fishing equity indexes. Machine learning can implement varied versions of this strategy. A hedge fund that was started in the late 1980s started absorbed a few years later went to be known as Renaissance Technologies, specializing in systematic trading with quantitative models derived from mathematical and statistical analyses. The fundamental process that machine learning deploys is a combination of computationally intensive statistical analytics subsequently with a neural-network-type branch which is basically classifiers. Over the years' hedge funds have lost billions of dollars owing to wrong analysis.
"Artificial intelligence" may sound futuristic, but it was actually coined in 1956 for a tech conference at Dartmouth College. Since then, the field has progressed in fits and starts as new hardware, software and ideas slowly propelled it forward. The current boom started in 2012, when a team of researchers used an artificial neural network in an image recognition competition that showed what AI could do with faster chips and more data. Like most technologies, it is littered with jargon. Artificial neural network (ANN): An algorithm that attempts to mimic the human brain, with layers of connected "neurons" sending information to each other.
A community for discussion and news related to Natural Language Processing (NLP). Natural language processing (NLP) is a field of computer science, artificial intelligence and computational linguistics concerned with the interactions between computers and human (natural) languages, and, in particular, concerned with programming computers to fruitfully process large natural language corpora.
Some of the best known examples of artificial intelligence are Siri and Alexa, which listen to human speech, recognize words, perform searches and translate the text results back into speech. But these and other AI technologies raise important issues like personal privacy rights and whether machines can ever make fair decisions. As Congress considers whether to make laws governing how AI systems function in society, a congressional committee has highlighted concerns around the types of AI algorithms that perform specific – if complex – tasks. Often called "narrow AI," these devices' capabilities are distinct from the still-hypothetical general AI machines, whose behavior would be virtually indistinguishable from human activity – more like the "Star Wars" robots R2-D2, BB-8 and C-3PO. Other examples of narrow AI include AlphaGo, a computer program that recently beat a human at the game of Go, and a medical device called OsteoDetect, which uses AI to help doctors identify wrist fractures.