How Artificial Superintelligence Will Give Birth To Itself Kinja is in read-only mode. We are working to restore service. "So if you create an AI that has a terminal value of friendliness to humanity, the AI would not want to change itself in a way that caused it to be unfriendly to humanity," he says. "From there, the AGI would be interested in pursuing whatever goals it was programmed with — such as research, exploration, or finance." I think this is a mistake. There are also a lot of things that we know we are inclined to do instinctively (i.e. we do essentially have some programmed "terminal values") but that doesn't stop some people from breaking from those instincts – see for example suicide, killing our own families, etc, which are examples of people going against their survival instincts. Flagged Keep in mind that we're not talking about a human-like mind with paleolithic tendencies. Thanks for replying, I'm not sure if we're in agreement or not though — quite possibly I wasn't being clear in my first comment.
Artificial Superintelligence: A Futuristic Approach Artificial Superintelligence: A Futuristic Approach, by Roman V. Yampolskiy Indiegogo fundraiser for Roman V. Yampolskiy‘s book. The book will present research aimed at making sure that emerging superintelligence is beneficial to humanity. Many philosophers, futurologists and artificial intelligence researchers have conjectured that in the next 20 to 200 years a machine capable of at least human level performance on all tasks will be developed. Since such a machine would among other things be capable of designing the next generation of even smarter intelligent machines, it is generally assumed that an intelligence explosion will take place shortly after such a technological self-improvement cycle begins. Writing Sample: Leakproofing Singularity What others said about: Leakproofing Singularity “Yampolskiy’s excellent article gives a thorough analysis of issues pertaining to the “leakproof singularity”: confining an AI system, at least in the early stages, so that it cannot “escape”. David J.
Collaborative learning for robots (Credit: 20th Century Fox) Researchers from MIT’s Laboratory for Information and Decision Systems have developed an algorithm in which distributed agents — such as robots exploring a building — collect data and analyze it independently. Pairs of agents, such as robots passing each other in the hall, then exchange analyses. In experiments involving several different data sets, the researchers’ distributed algorithm actually outperformed a standard algorithm that works on data aggregated at a single location, as described in an arXiv paper. Machine learning, in which computers learn new skills by looking for patterns in training data, is the basis of most recent advances in artificial intelligence, from voice-recognition systems to self-parking cars. That type of model-building gets complicated, however, in cases in which clusters of robots work as teams. The robots may have gathered information that, collectively, would produce a good model but which, individually, is almost useless.
The AI Revolution: Road to Superintelligence - Wait But Why PDF: We made a fancy PDF of this post for printing and offline viewing. Buy it here. (Or see a preview.) Note: The reason this post took three weeks to finish is that as I dug into research on Artificial Intelligence, I could not believe what I was reading. It hit me pretty quickly that what’s happening in the world of AI is not just an important topic, but by far THE most important topic for our future. So I wanted to learn as much as I could about it, and once I did that, I wanted to make sure I wrote a post that really explained this whole situation and why it matters so much. We are on the edge of change comparable to the rise of human life on Earth. — Vernor Vinge What does it feel like to stand here? It seems like a pretty intense place to be standing—but then you have to remember something about what it’s like to stand on a time graph: you can’t see what’s to your right. Which probably feels pretty normal… The Far Future—Coming Soon This works on smaller scales too. 1. What Is AI?
Superintelligence A superintelligence, hyperintelligence, or superhuman intelligence is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds. ‘’Superintelligence’’ may also refer to the form or degree of intelligence possessed by such an agent. Technological forecasters and researchers disagree about when human intelligence is likely to be surpassed. Some argue that advances in artificial intelligence (AI) will probably result in general reasoning systems that lack human cognitive limitations. Others believe that humans will evolve or directly modify their biology so as to achieve radically greater intelligence. Experts in AI and biotechnology do not expect any of these technologies to produce a superintelligence in the very near future. Definition[edit] Summarizing the views of intelligence researchers, Linda Gottfredson writes: Feasibility[edit] Computational resources place another limit on present-day human cognition. Concerns[edit]
Can AI save us from AI? | Singularity HUB Can AI save us from AI? Nick Bostrom’s book Superintelligence might just be the most debated technology book of the year. Since its release, big names in tech and science, including Stephen Hawking and Elon Musk, have warned of the dangers of artificial intelligence. Bostrom says that while we don’t know exactly when artificial intelligence will rival human intelligence, many experts believe there is a good chance it will happen at some point during the 21st century. He suggests that when AI reaches a human level of intelligence, it may very rapidly move past humans as it takes over its own development. The concept has long been discussed and is often described as an “intelligence explosion”—a term coined by computer scientist IJ Good fifty years ago. “Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man, however clever. Broader and seemingly beneficial goal setting might backfire too. So, what do you think?
Nick Bostrom’s Superintelligence and the metaphorical AI time bomb Frank Knight was an idiosyncratic economist who formalized a distinction between risk and uncertainty in his 1921 book Risk, Uncertainty, and Profit. As Knight saw it, an ever-changing world brings new opportunities, but also means we have imperfect knowledge of future events. According to Knight, risk applies to situations where we do not know the outcome of a given situation, but can accurately measure the odds. Uncertainty, on the other hand, applies to situations where we cannot know all the information we need in order to set accurate odds in the first place. “There is a fundamental distinction between the reward for taking a known risk and that for assuming a risk whose value itself is not known,” Knight wrote. Sometimes, due to uncertainty, we react too little or too late, but sometimes we overreact. Artificial Intelligence may be one of the areas where we overreact. Perhaps Elon was thinking of Blake’s The Book of Urizen when he described AI as ‘summoning the demon’:
The Three Laws of Transhumanism and Artificial Intelligence Wikimedia Commons I recently gave a speech at the Artificial Intelligence and The Singularity Conference in Oakland, California. There was a great lineup of speakers, including AI experts Peter Voss and Monica Anderson, New York University professor Gary Marcus, sci-fi writer Nicole Sallak Anderson, and futurist Scott Jackisch. My speech topic was: The Morality of an Artificial Intelligence Will be Different from our Human Morality Recently, entrepreneur Elon Musk made major news when he warned on Twitter that AI could be: "Potentially more dangerous than nukes." The coming of artificial intelligence will likely be the most significant event in the history of the human species. Naturally, as a transhumanist, I strive to be an optimist. The common consensus is that AI experts will aim to program concepts of "humanity," "love," and "mammalian instincts" into an artificial intelligence, so it won't destroy us in some future human extinction rampage. Wikimedia Commons Let's face it.
On the hunt for universal intelligence How do you use a scientific method to measure the intelligence of a human being, an animal, a machine or an extra-terrestrial? So far this has not been possible, but a team of Spanish and Australian researchers have taken a first step towards this by presenting the foundations to be used as a basis for this method in the journal Artificial Intelligence, and have also put forward a new intelligence test. "We have developed an 'anytime' intelligence test, in other words a test that can be interrupted at any time, but that gives a more accurate idea of the intelligence of the test subject if there is a longer time available in which to carry it out", José Hernández-Orallo, a researcher at the Polytechnic University of Valencia (UPV), tells SINC. This is just one of the many determining factors of the universal intelligence test. The researcher, along with his colleague David L. Use in artificial intelligence Explore further: Ant colonies help evacuees in disaster zones
Darpa sets out to make computers that teach themselves The Pentagon's blue-sky research agency is readying a nearly four-year project to boost artificial intelligence systems by building machines that can teach themselves -- while making it easier for ordinary schlubs like us to build them, too. When Darpa talks about artificial intelligence, it's not talking about modelling computers after the human brain. That path fell out of favour among computer scientists years ago as a means of creating artificial intelligence; we'd have to understand our own brains first before building a working artificial version of one. But building such machines remains really, really hard: The agency calls it "Herculean". Called "Probabilistic Programming for Advanced Machine Learning," or PPAML, scientists will be asked to figure out how to "enable new applications that are impossible to conceive of using today's technology", while making experts in the field " radically more effective", according to a recent agency announcement. Image: Darpa
Clarke's three laws Clarke's Three Laws are three "laws" of prediction formulated by the British science fiction writer Arthur C. Clarke. They are: When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong.The only way of discovering the limits of the possible is to venture a little way past them into the impossible.Any sufficiently advanced technology is indistinguishable from magic. Origins[edit] Clarke's First Law was proposed by Arthur C. The second law is offered as a simple observation in the same essay. The Third Law is the best known and most widely cited, and appears in Clarke's 1973 revision of "Hazards of Prophecy: The Failure of Imagination". A fourth law has been added to the canon, despite Sir Arthur Clarke's declared intention of not going one better than Sir Isaac Newton. Snowclones and variations of the third law[edit] and its contrapositive: See also[edit] References[edit]
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]
Promises and Perils on the Road to Superintelligence Global Brain / Image credit: mindcontrol.se In the 21st century, we are walking an important road. Our species is alone on this road and it has one destination: super-intelligence. The most forward-thinking visionaries of our species were able to get a vague glimpse of this destination in the early 20th century. Paleontologist Pierre Teilhard de Chardin called this destination Omega Point. Mathematician Stanislaw Ulam called it “singularity”: One conversation on the ever accelerating progress of technology and changes in the mode of human life, which gives the appearance some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue. For thinkers like Chardin, this vision was spiritual and religious; God using evolution to pull our species closer to our destiny. Today the philosophical debates of this vision have become more varied, but also more focused on model building and scientific prediction. Promise #1: Omniscience Cadell Last