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Archive for the ‘information science’ category: Page 124

Feb 25, 2011

Security and Complexity Issues Implicated in Strong Artificial Intelligence, an Introduction

Posted by in categories: complex systems, existential risks, information science, robotics/AI

Strong AI or Artificial General Intelligence (AGI) stands for self-improving intelligent systems possessing the capacity to interact with theoretical- and real-world problems with a similar flexibility as an intelligent living being, but the performance and accuracy of a machine. Promising foundations for AGI exist in the current fields of stochastic- and cognitive science as well as traditional artificial intelligence. My aim in this post is to give a very basic insight into- and feeling for the issues involved in dealing with the complexity and universality of an AGI for a general readership.

Classical AI, such as machine learning algorithms and expert systems, are already heavily utilized in today’s real-world problems, in the form of mature machine learning algorithms, which may profitably exploit patterns in customer behaviour, find correlations in scientific data or even predict negotiation strategies, for example [1] [2], or in the form of genetic algorithms. With the next upcoming technology for organizing knowledge on the net, which is called the semantic web and deals with machine-interpretable understanding of words in the context of natural language, we may start inventing early parts of technology playing a role in the future development of AGI. Semantic approaches come from computer science, sociology and current AI research, but promise to describe and ‘understand’ real-world concepts and to enable our computers to build interfaces to real world concepts and coherences more autonomously. Actually getting from expert systems to AGI will require approaches to bootstrap self-improving systems and more research on cognition, but must also involve crucial security aspects. Institutions associated with this early research include the Singularity Institute [3] and the Lifeboat Foundation [4].

In the recent past, we had new kinds of security challenges: DoS attacks, eMail- and PDF-worms and a plethora of other malware, which sometimes even made it into military and other sensitive networks, and stole credit cards and private data en masse. These were and are among the first serious incidents related to the Internet. But still, all of these followed a narrow and predictable pattern, constrained by our current generation of PCs, (in-)security architecture, network protocols, software applications, and of course human flaws (e.g. the emotional response exploited by the “ILOVEYOU virus”). To understand the implications in strong AI first means to realize that probably there won’t be any human-predictable hardware, software, interfaces around for longer periods of time as long as AGI takes off hard enough.

To grasp the new security implications, it’s important to understand how insecurity can arise from the complexity of technological systems. The vast potential of complex systems oft makes their effects hard to predict for the human mind which is actually riddled with biases based on its biological evolution. For example, the application of the simplest mathematical equations can produce complex results hard to understand and predict by common sense. Cellular automata, for example, are simple rules for generating new dots, based on which dots, generated by the same rule, are observed in the previous step. Many of these rules can be encoded in as little as 4 letters (32 bits), and generate astounding complexity.

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Oct 25, 2010

Open Letter to Ray Kurzweil

Posted by in categories: biotech/medical, business, economics, engineering, futurism, human trajectories, information science, open source, robotics/AI

Dear Ray;

I’ve written a book about the future of software. While writing it, I came to the conclusion that your dates are way off. I talk mostly about free software and Linux, but it has implications for things like how we can have driverless cars and other amazing things faster. I believe that we could have had all the benefits of the singularity years ago if we had done things like started Wikipedia in 1991 instead of 2001. There is no technology in 2001 that we didn’t have in 1991, it was simply a matter of starting an effort that allowed people to work together.

Proprietary software and a lack of cooperation among our software scientists has been terrible for the computer industry and the world, and its greater use has implications for every aspect of science. Free software is better for the free market than proprietary software, and there are many opportunities for programmers to make money using and writing free software. I often use the analogy that law libraries are filled with millions of freely available documents, and no one claims this has decreased the motivation to become a lawyer. In fact, lawyers would say that it would be impossible to do their job without all of these resources.

My book is a full description of the issues but I’ve also written some posts on this blog, and this is probably the one most relevant for you to read: https://lifeboat.com/blog/2010/06/h-conference-and-faster-singularity

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Jun 5, 2010

Friendly AI: What is it, and how can we foster it?

Posted by in categories: complex systems, ethics, existential risks, futurism, information science, policy, robotics/AI

Friendly AI: What is it, and how can we foster it?
By Frank W. Sudia [1]

Originally written July 20, 2008
Edited and web published June 6, 2009
Copyright © 2008-09, All Rights Reserved.

Keywords: artificial intelligence, artificial intellect, friendly AI, human-robot ethics, science policy.

1. Introduction

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Apr 18, 2010

Ray Kurzweil to keynote “H+ Summit @ Harvard — The Rise Of The Citizen Scientist”

Posted by in categories: biological, biotech/medical, business, complex systems, education, events, existential risks, futurism, geopolitics, human trajectories, information science, media & arts, neuroscience, robotics/AI

With our growing resources, the Lifeboat Foundation has teamed with the Singularity Hub as Media Sponsors for the 2010 Humanity+ Summit. If you have suggestions on future events that we should sponsor, please contact [email protected].

The summer 2010 “Humanity+ @ Harvard — The Rise Of The Citizen Scientist” conference is being held, after the inaugural conference in Los Angeles in December 2009, on the East Coast, at Harvard University’s prestigious Science Hall on June 12–13. Futurist, inventor, and author of the NYT bestselling book “The Singularity Is Near”, Ray Kurzweil is going to be keynote speaker of the conference.

Also speaking at the H+ Summit @ Harvard is Aubrey de Grey, a biomedical gerontologist based in Cambridge, UK, and is the Chief Science Officer of SENS Foundation, a California-based charity dedicated to combating the aging process. His talk, “Hype and anti-hype in academic biogerontology research: a call to action”, will analyze the interplay of over-pessimistic and over-optimistic positions with regards of research and development of cures, and propose solutions to alleviate the negative effects of both.

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Jul 23, 2009

Artificial brain ’10 years away’

Posted by in categories: engineering, human trajectories, information science, neuroscience, robotics/AI, supercomputing

Artificial brain ’10 years away’

By Jonathan Fildes
Technology reporter, BBC News, Oxford

A detailed, functional artificial human brain can be built within the next 10 years, a leading scientist has claimed.

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Jul 12, 2009

Stanford MediaX: Semantic Integration, New Media, Data Visualization

Posted by in categories: business, education, events, information science

MediaX at Stanford University is a collaboration between the university’s top technology researchers and companies innovating in today’s leading industries.

Starting next week, MediaX is putting on an exciting series of courses in The Summer Institute at Wallenberg Hall, on Stanford’s campus.

Course titles that are still open are listed below, and you can register and see the full list here. See you there!

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May 30, 2009

Create an AI on Your Computer

Posted by in categories: complex systems, human trajectories, information science, neuroscience, robotics/AI, supercomputing

Singularity Hub

Create an AI on Your Computer

Written on May 28, 2009 – 11:48 am | by Aaron Saenz |

If many hands make light work, then maybe many computers can make an artificial brain. That’s the basic reasoning behind Intelligence Realm’s Artificial Intelligence project. By reverse engineering the brain through a simulation spread out over many different personal computers, Intelligence Realm hopes to create an AI from the ground-up, one neuron at a time. The first waves of simulation are already proving successful, with over 14,000 computers used and 740 billion neurons modeled. Singularity Hub managed to snag the project’s leader, Ovidiu Anghelidi, for an interview: see the full text at the end of this article.

The ultimate goal of Intelligence Realm is to create an AI or multiple AIs, and use these intelligences in scientific endeavors. By focusing on the human brain as a prototype, they can create an intelligence that solves problems and “thinks” like a human. This is akin to the work done at FACETS that Singularity Hub highlighted some weeks ago. The largest difference between Intelligence Realm and FACETS is that Intelligence Realm is relying on a purely simulated/software approach.

Which sort of makes Intelligence Realm similar to the Blue Brain Project that Singularity Hub also discussed. Both are computer simulations of neurons in the brain, but Blue Brain’s ultimate goal is to better understand neurological functions, while Intelligence Realm is seeking to eventually create an AI. In either case, to successfully simulate the brain in software alone, you need a lot of computing power. Blue Brain runs off a high-tech supercomputer, a resource that’s pretty much exclusive to that project. Even with that impressive commodity, Blue Brain is hitting the limit of what it can simulate. There’s too much to model for just one computer alone, no matter how powerful. Intelligence Realm is using a distributed computing solution. Where one computer cluster alone may fail, many working together may succeed. Which is why Intelligence Realm is looking for help.

The AI system project is actively recruiting, with more than 6700 volunteers answering the call. Each volunteer runs a small portion of the larger simulation on their computer(s) and then ships the results back to the main server. BOINC, the Berkeley built distributed computing software that makes it all possible, manages the flow of data back and forth. It’s the same software used for SETI’s distributed computing processing. Joining the project is pretty simple: you just download BOINC, some other data files, and you’re good to go. You can run the simulation as an application, or as part of your screen saver.

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Mar 12, 2009

Crowdsourced Women’s Health Books Released by CureTogether

Posted by in categories: biological, biotech/medical, information science, open access, open source

Over 300 Women Share Experiences, Treatments for Painful, Common Chronic Conditions

CureTogether, a Health 2.0 Startup based in Silicon Valley, has released the first crowdsourced books on vulvodynia and endometriosis: two common, poorly understood conditions causing daily pain for millions of women. Assembled from the input of 190 and 137 women living with these respective conditions, “Vulvodynia Heroes” and “Endometriosis Heroes” are the product of an ongoing online research study at http://www.curetogether.com.

“Patients came together and decided what symptoms and treatments they wanted to track. They went on to diligently gather detailed, quantitative data on their bodies and experiences,” said Alexandra Carmichael, co-Founder of CureTogether. “The hope of this book is to spread awareness, reach out to people in pain who may not have heard of endometriosis, and increase interest and funding for future research.”

“These heroes are pioneers not just in investigating their own condition, but in developing self-cure practices that others can follow.”, said Gary Wolf, Contributing Editor of Wired and Blogger at The Quantified Self. “Many other women who are suffering will find this very helpful and inspiring,” said Elizabeth Rummer, MSPT at the Pelvic Health and Rehabilitation Center in San Francisco. A patient with endometriosis added, “This is great. I am just starting to really appreciate what awesome power CureTogether can have.”

Endometriosis is a painful chronic condition that affects 5–10% of women, and vulvodyna affects up to 16% of women at some point in their lives. They are two of the most active condition communities at CureTogether, with information about symptoms, treatments, and causes added by over 300 women. The books are available at http://www.curetogether.com/VHeroes and http://www.curetogether.com/EHeroes.

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Jul 5, 2008

Using Vaccines more Effectively to Stop Pandemics

Posted by in categories: biological, biotech/medical, information science

If a pandemic strikes and hundreds of millions are at risk, we won’t have enough vaccines for everybody, at least not within the time window where vaccines would help. But a new strategy could help use the vaccines we have more effectively:

Researchers are now proposing a new strategy for targeting shots that could, at least in theory, stop a pandemic from spreading along the network of social interactions. Vaccinating selected people is essentially equivalent to cutting out nodes of the social network. As far as the pandemic is concerned, it’s as if those people no longer exist. The team’s idea is to single out people so that immunizing them breaks up the network into smaller parts of roughly equal sizes. Computer simulations show that this strategy could block a pandemic using 5 to 50 percent fewer doses than existing strategies, the researchers write in an upcoming Physical Review Letters.

vaccine-targeting.jpg

So you break up the general social network into sub-networks, and then you target the most important nodes of these sub-networks and so on until you run out of vaccines. The challenge will be to get good information about social networks, something not quite as easy as mapping computer networks, but there is progress on that front.

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