artificial general intelligence


ARTIFICIAL INTELLIGENCE

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In the era of science and technology, there is much hype about Artificial Intelligence. Everything is superseding by Artificial Intelligence, in every possible sphere of work. To match the pace of this era, we must know what actually Artificial Intelligence, i.e. Artificial Intelligence is the field of computer science, which enables the computer to behave, think, act, and respond as human being. Why is it called so is another point of interest.


Machine Reasoning and the Rise of Artificial General Intelligences: An Interview With Bart Selman - Future of Life Institute

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From Uber's advanced computer vision system to Netflix's innovative recommendation algorithm, machine learning technologies are nearly omnipresent in our society. They filter our emails, personalize our newsfeeds, update our GPS systems, and drive our personal assistants. However, despite the fact that such technologies are leading a revolution in artificial intelligence, some would contend that these machine learning systems aren't truly intelligent. The argument, in its most basic sense, centers on the fact that machine learning evolved from theories of pattern recognition and, as such, the capabilities of such systems generally extend to just one task and are centered on making predictions from existing data sets. AI researchers like Rodney Brooks, a former professor of Robotics at MIT, argue that true reasoning, and true intelligence, is several steps beyond these kinds of learning systems.


Two faces of Artificial Intelligence

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At its core Artificial Intelligence is about teaching computers to do what humans can do with the expectation that computers will do those things better. Examining the history of technological progress it is possible you will not live long enough to see Artificial Intelligence change the world. Assuming AI is something that will change the world and that is in no way assured. In a best case scenario Artificial General Intelligence (AGI) will be system capable of tapping the sum of human knowledge to answer questions which are currently beyond us and generate ideas which we are incapable of. AGI relies on a breakthrough yet to be made so in the near term we can expect that slivers of task specific Artificial Intelligence will be embedded into software, services and products in the same fashion that databases are now embedded in the such things.


Jennifer Zhu Scott: AI's Risks Come From People, Not Killer Robots

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"Self-aware robots with Artificial General Intelligence will destroy humanity." We all have heard this version of artificial intelligence (AI) dystopia in science fiction, movies or even from respected scientists and philosophers. But I argue a completely different version of AI dystopia could arrive much sooner. So soon, it could be within our or our children's lifetime. Unfortunately, most of us are distracted by the binary thinking of machine versus human, bedazzled every time some new technological capacities are achieved, and neglect to pay thoughtful attention to this forthcoming unfolding crisis.


Book Review: Architects of Intelligence

IEEE Spectrum Robotics Channel

Artificial intelligence seems to be the go-to solution to every problem there is (technological in nature or otherwise), and it's only getting worse. A staggering number of both startups and established companies are loudly proclaiming how AI, or machine learning, or deep learning, or whatever is absolutely going to make everything faster, better, cheaper, fairer, and so on. The reason that this sort of breathless and inevitably shallow media-driven enthusiasm for artificial intelligence is effective is because there's just enough of a general understanding of AI for people to know that it can do some cool things, but not so much of an understanding for people to question what it's actually capable of, or whether applying to to a specific problem is a good idea. This is not to say that a lack of understanding is anyone's fault, really: it's hard to define what AI even is, much less communicate how it works. And without the proper context, there's no way to make an informed judgement about the future potential of artificial intelligence.


This is when AI's top researchers think artificial general intelligence will be achieved

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At the heart of the discipline of artificial intelligence is the idea that one day we'll be able to build a machine that's as smart as a human. Such a system is often referred to as an artificial general intelligence, or AGI, which is a name that distinguishes the concept from the broader field of study. It also makes it clear that true AI possesses intelligence that is both broad and adaptable. To date, we've built countless systems that are superhuman at specific tasks, but none that can match a rat when it comes to general brain power. But despite the centrality of this idea to the field of AI, there's little agreement among researchers as to when this feat might actually be achievable.


This is when AI's top researchers think artificial general intelligence will be achieved

#artificialintelligence

At the heart of the discipline of artificial intelligence is the idea that one day we'll be able to build a machine that's as smart as a human. Such a system is often referred to as an artificial general intelligence, or AGI, which is a name that distinguishes the concept from the broader field of study. It also makes it clear that true AI possesses intelligence that is both broad and adaptable. To date, we've built countless systems that are superhuman at specific tasks, but none that can match a rat when it comes to general brain power. But despite the centrality of this idea to the field of AI, there's little agreement among researchers as to when this feat might actually be achievable.


A beginner's guide to AI: Human-level machine intelligence

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This (currently) five part feature should provide you with a very basic understanding of what AI is, what it can do, and how it works. The guide contains articles on (in order published) neural networks, computer vision, natural language processing, algorithms, and artificial general intelligence. There are few technologies that inspire the imagination like artificial intelligence. And, in the field of AI, the Holy Grail is living machines. The quest to imbue machines with the spark of life is an ancient one.


Anticipating the next move in data science – my interview with Thomson Reuters

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Thomson Reuters has a series, AI experts, where they interview thought leaders from different areas - including technology executives, researchers, robotics experts and policymakers - on what we might expect as we move towards AI. As part of that series I recently spoke to Paul Thies of Thomson Reuters, and here are the excerpts from the interview: Anticipating the next move in data science Thomson Reuters: For timely information concerning developments in data science, data mining and business analytics, KDnuggets is widely regarded as a leading outlet in the field. Created in 1993 by founder, editor and president Gregory Piatetsky-Shapiro, it is frequently cited as one of the top sources of data science news and influence by various industry watchers. Thomson Reuters: What are some use cases of data science that you find to be particularly valuable to organizations in this age of Big Data? GREGORY: Where people typically apply data science, probably not surprisingly, are in the areas of customer relationship management (CRM) and consumer analytics.


OpenAI launches reinforcement learning training to prepare for artificial general intelligence

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OpenAI today announced the launch of Spinning Up, a program designed to teach anyone deep reinforcement learning. OpenAI is well known for making funky-looking agents in virtual environments that learn how to walk on their own such as Humanoid v2 or POLO, a collaboration with University of Washington. Reinforcement learning involves providing reward signals to an agent in an environment incentivized to maximize its reward to meet a goal. RL has played a role in major AI breakthroughs such as Google DeepMind's AlphaGo and agents trained in environments like Dota 2. Spinning Up includes a collection of important reinforcement learning research papers, a glossary of terminology necessary to understand RL, and a collection of algorithms for running exercises. The program is being launched not just to help people learn how reinforcement learning works, but to make progress towards OpenAI's general goal of safely creating artificial general intelligence (AGI) by involving more people from fields beyond computer science.