I call them that anyway, sounds sexy to me
Moderators: Blip, The_Metatron
Two guys who have no specialist knowledge in AI?Macdoc wrote:That would be media as the info carriers...
Just mind the emergent sentient neural networks....Rise of the Machines is real and a threat ....Musk and Hawking think so.
I don't even know how to successfully swing a cat video round the internet. How do you distinguish the knowledge from the fake news? I'm the sort of arsehole who doesn't care what shit the users are throwing at each other. It's all just bits and bloops to me. The users don't deserve their computers.Keep It Real wrote:OT Vaz.....how do we spread around the knowledge? That's the objective....maybe you can hook up a bot or something before they cap u age 40 lol
I certainly call myself one, but I know shit about how to go viral, or to how to get them sweet network effects. I'm personally of the opinion that it's random. The reason Facebook is so successful is the reason Richard Branson is so successful: there isn't a reason; it isn't about merit; it's about dumb fucking luck. If merit was the arbiter in technology, this world would be a very different place.Keep It Real wrote:Brainwash dem. Happy campers innit. Thought you said you are a programmer?
Destroyallsoftware?Keep It Real wrote:Baaaaaaaaaaaaaaaaaaaaaaaaad software. Do it Vaz.
In addition to heavyweights like Hawking and Musk, the prominent physicist and billionaire founder of SpaceX and Tesla Motors, the letter was signed by top researchers at the Massachusetts Institute of Technology, Google and other institutions.
Artificial intelligence (AI) research has explored a variety of problems and approaches since its inception, but for the last 20 years or so has been focused on the problems surrounding the construction of intelligent agents – systems that perceive and act in some environment. In this context, “intelligence” is related to statistical and economic notions of rationality – colloquially, the ability to make good decisions, plans, or inferences. The adoption of probabilistic and decision-theoretic representations and statistical learning methods has led to a large degree of integration and cross-fertilization among AI, machine learning, statistics, control theory, neuroscience, and other fields. The establishment of shared theoretical frameworks, combined with the availability of data and processing power, has yielded remarkable successes in various component tasks such as speech recognition, image classification, autonomous vehicles, machine translation, legged locomotion, and question-answering systems.
As capabilities in these areas and others cross the threshold from laboratory research to economically valuable technologies, a virtuous cycle takes hold whereby even small improvements in performance are worth large sums of money, prompting greater investments in research. There is now a broad consensus that AI research is progressing steadily, and that its impact on society is likely to increase. The potential benefits are huge, since everything that civilization has to offer is a product of human intelligence; we cannot predict what we might achieve when this intelligence is magnified by the tools AI may provide, but the eradication of disease and poverty are not unfathomable. Because of the great potential of AI, it is important to research how to reap its benefits while avoiding potential pitfalls.
The progress in AI research makes it timely to focus research not only on making AI more capable, but also on maximizing the societal benefit of AI. Such considerations motivated the AAAI 2008-09 Presidential Panel on Long-Term AI Futures and other projects on AI impacts, and constitute a significant expansion of the field of AI itself, which up to now has focused largely on techniques that are neutral with respect to purpose. We recommend expanded research aimed at ensuring that increasingly capable AI systems are robust and beneficial: our AI systems must do what we want them to do. The attached research priorities document gives many examples of such research directions that can help maximize the societal benefit of AI. This research is by necessity interdisciplinary, because it involves both society and AI. It ranges from economics, law and philosophy to computer security, formal methods and, of course, various branches of AI itself.
In summary, we believe that research on how to make AI systems robust and beneficial is both important and timely, and that there are concrete research directions that can be pursued today.
while avoiding potential pitfalls.
Industry Urges United Nations to Ban Lethal Autonomous Weapons in ...
https://spectrum.ieee.org/.../industry- ... mous-wea...
Aug 21, 2017 - Today (or, yesterday, but today Australia time, where it's probably already tomorrow), 116 founders of robotics and artificial intelligence companies from 26 countries released an open letter urging the United Nations to ban lethal autonomous weapon systems (LAWS).
Weapons systems that make their own decisions are a very different, and much broader, category. The line between weapons controlled by humans and those that fire autonomously is blurry, and many nations—including the US—have begun the process of crossing it. Moreover, technologies such as robotic aircraft and ground vehicles have proved so useful that armed forces may find giving them more independence—including to kill—irresistible.
https://www.wired.com/story/sorry-banni ... practical/
Return to Parenting & Education
Users viewing this topic: No registered users and 1 guest