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Panel: Ben Goertzel, David Chalmers, Steve Omohundro,...

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theswayzeexpress1 Says:

Apr 21, 2013 - Darwinsitic evolution is not pure randomness though because its products are not pure randomness. It guides development through competition to find the best viable design to allow reproduction. What I'm wondering is if AI systems will compete with each other and re-design themselves so they evolve to Darwinistic principles.

Adam Ford Says:

Apr 20, 2013 - darwinistic evolution produced us, we now stand at the top of mount improbable - but that does not mean AI will use it to make itself better. Darwinistic Evolution is based on random meanderings in nearest neighboring possibilities of minute mutations, it has no foresight, or goals - an AI could completely redesign and optimize itself based on an intelligent map of possible peaks and troughs in the landscape of possible substrate and mind designs ..

Adam Ford Says:

Apr 20, 2013 - He is a cyborg - why do you wear shoes?

theswayzeexpress1 Says:

Apr 20, 2013 - I wonder if AI will ever replicate itself and if it would obey Darwinist laws of evolution in its development.

matt bastardssen Says:

Oct 23, 2012 - pass me a brewskie, eh?

Jake Swanson Says:

May 1, 2012 - Thanks for all the videos. I haven't gone through them all yet and most are way over my head. This is all new to me and has changed my perspective on life. Kind of feels like a religion in that it has given me hope and some sort of meaning to life.

eugalpiZ Ziplague Says:

Apr 30, 2012 - dogmatic haha, nice one :D

Carlos Garcia Hernandez Says:

Apr 30, 2012 - Why does he wear headphones?

Video Details

Approaches to AI - AGI Progress/Impediments - http://2011.singularitysummit.
com.au Ben Goertzel: Brain Emulation, Broad level roadmap simulation, bottleneck, lack of imaging technology, we don't know what level of precision we need to reverse engineer biological intelligence. Ed Boyed - optimal brain imageing. Not by Brain emulation (engineering/comp sci/cognitive sci), bottleneck is funding. People in the field believe/feel they know how to do it. To prove this, they need to integrate their architectures which looks like a big project. Takes a lot of money, but not as much as something like Microsoft Word. David Chalmers (time 03:42): We don't know which of the two approaches. Though what form the singularity will take will likely be dependent on the approach we use to build AGI. We don't understand the theory yet. Most don't think we will have a perfect molecular scanner that scans the brain and its chemical constituents. 25 Years ago David Chalmers worked in Douglass Hofstadter's AI lab, but his expertise in AI is now out of date. To get to Human Level AI by brute force or through cognitive psychology knows that the cog-sci is not in very good shape. Third approach is a hybrid of ruffly brain augmentation (through technology we are already using like ipads and computers etc) and technological extension and uploading. If using brain augmentation through tech and uploading as a first step in a Singularity then it is including Humans in the equation along with humanities values which may help shape a Singularity with those values. Steve Omohundro (time 08:08): Early in history AI, there was a distinction: The Neats and the Scruffies. John McCarthy (Stanford AI Lab) believed in mathematically precise logical representations - this shaped a lot of what Steve thought about how programming should be done. Marvin Minsky (MIT Lab) believed in exploring neural nets and self organising systems and the approach of throwing things together to see how it self-organises into intelligence. Both approaches are needed: the logical, mathematically precise, neat approach - and - the probabilistic, self-organising, fuzzy, learning approach, the scruffy. They have to come together. Theorem proving without any explorative aspect probably wont succeed. Purely Neural net based simulations can't represent semantics well, need to combine systems with full semantics and systems with the ability to adapt to complex environments. James Newton-Thomas (time 9:57) James has been playing with Neural-nets and has been disappointed with them not being thinks that Augmentation is the way forward. The AI problem is going to be easier to solve if we are smarter to solve it. Conferences such as this help infuse us with a collective empowerment of the individuals. There is an impediment - we are already being dehumanised with our Ipad, where the reason why we are having a conversation with others is a fact about our being part of a group and not about the information that can be looked up via an IPad. We need to careful in our approach so that we are able to maintain our humanity whilst gaining the advantages of the augmentation. --- Discussion starts time 12:05 (David) We are already becoming cyborgs in a sense by interacting with tech in our world. the more literal cyborg approach we are working on now. Though we are not yet at the point where the technology is commercialization to in principle allow a strong literal cyborg approach. (Ben) Though we could progress with some form of brain vocalization (picking up words directly from the brain), allowing to think a google query and have the results directly added to our mind - thus bypassing our low bandwidth communication and getting at the information directly in our heads. To do all this ... (Steve) EEG is gaining a lot of interest to help with the Quantified Self - brain interfaces to help measure things about thier body (though the hardware is not that good yet). (Ben) Use of BCIs for video games - and can detect whether you are aroused and paying attention. Though the resolution is very course - hard to get fine grained brain state information through the skull. Cranial jacks will get more information. Legal systems are an impediment. (James) Alan Snyder using time altering magnetic fields in helmets that shut down certain areas of the brain, which effectively makes people smarter in narrower domains of skill. Can provide an idiot savant ability at the cost of the ability to generalize. The brain that becomes to specific at one task is doing so at the cost of others - the process of generalization. Less