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Daniel Hennes

A.I. XPRIZE - 3 views

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    TED is sponsoring an A.I. XPRIZE. The goal? Develop an artificial intelligence that jumps on stage and gives a 3min talk on a random topic...
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    I am going to propose that the rules include in addition something practical - like washing the dishes... If we are to foster progress, let's finally do so in the right direction...
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    This sort of reminds me of Hinton's paper from some years ago:
    http://www.cs.utoronto.ca/~ilya/pubs/2011/LANG-RNN.pdf

    Train it on previous TED talks and let it run TED talk - like gibberish. It would probably be of similar value. He had a nice one on the meaning of life but I can't find it anymore.
Daniel Hennes

NASA's Asteroid Grand Challenge Series - 1 views

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    NASA's new crowdsourcing initiative to find asteroid threats.
Guido de Croon

Will robots be smarter than humans by 2029? - 2 views

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    Nice discussion about the singularity. Made me think of drinking coffee with Luis... It raises some issues such as the necessity of embodiment, etc.
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    "Kurzweilians"... LOL.

    Still not sold on embodiment, btw.
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    The biggest problem with embodiment is that, since the passive walkers (with which it all started), it hasn't delivered anything really interesting...
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    The problem with embodiment is that it's done wrong. Embodiment needs to be treated like big data. More sensors, more data, more processing. Just putting a computer in a robot with a camera and microphone is not embodiment.
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    I like how he attacks Moore's Law. It always looks a bit naive to me if people start to (ab)use it to make their point. No strong opinion about embodiment.
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    @Paul: How would embodiment be done RIGHT?
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    Embodiment has some obvious advantages. For example, in the vision domain many hard problems become easy when you have a body with which you can take actions (like looking at an object you don't immediately recognize from a different angle) - a point already made by researchers such as Aloimonos.and Ballard in the end 80s / beginning 90s. However, embodiment goes further than gathering information and "mental" recognition. In this respect, the evolutionary robotics work by for example Beer is interesting, where an agent discriminates between diamonds and circles by avoiding one and catching the other, without there being a clear "moment" in which the recognition takes place. "Recognition" is a behavioral property there, for which embodiment is obviously important. With embodiment the effort for recognizing an object behaviorally can be divided between the brain and the body, resulting in less computation for the brain. Also the article "Behavioural Categorisation: Behaviour makes up for bad vision" is interesting in this respect. In the field of embodied cognitive science, some say that recognition is constituted by the activation of sensorimotor correlations. I wonder to which extent this is true, and if it is valid for extremely simple creatures to more advanced ones, but it is an interesting idea nonetheless.

    This being said, if "embodiment" implies having a physical body, then I would argue that it is not a necessary requirement for intelligence. "Situatedness", being able to take (virtual or real) "actions" that influence the "inputs", may be.
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    @Paul

    While I completely agree about the "embodiment done wrong" (or at least "not exactly correct") part, what you say goes exactly against one of the major claims which are connected with the notion of embodiment (google for "representational bottleneck"). The fact is your brain does *not* have resources to deal with big data. The idea therefore is that it is the body what helps to deal with what to a computer scientist appears like "big data". Understanding how this happens is key.

    Whether it is the problem of scale or of actually understanding what happens should be quite conclusively shown by the outcomes of the Blue Brain project.
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    Wouldn't one expect that to produce consciousness (even in a lower form) an approach resembling that of nature would be essential?
    All animals grow from a very simple initial state (just a few cells) and have only a very limited number of sensors AND processing units. This would allow for a fairly simple way to create simple neural networks and to start up stable neural excitation patterns. Over time as complexity of the body (sensors, processors, actuators) increases the system should be able to adapt in a continuous manner and increase its degree of self-awareness and consciousness.
    On the other hand, building a simulated brain that resembles (parts of) the human one in its final state seems to me like taking a person who is just dead and trying to restart the brain by means of electric shocks.
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    Actually on a neuronal level all information gets processed. Not all of it makes it into "conscious" processing or attention. Whatever makes it into conscious processing is a highly reduced representation of the data you get. However that doesn't get lost. Basic, low processed data forms the basis of proprioception and reflexes. Every step you take is a macro command your brain issues to the intricate sensory-motor system that puts your legs in motion by actuating every muscle and correcting every step deviation from its desired trajectory using the complicated system of nerve endings and motor commands. Reflexes which were build over the years, as those massive amounts of data slowly get integrated into the nervous system and the the incipient parts of the brain.

    But without all those sensors scattered throughout the body, all the little inputs in massive amounts that slowly get filtered through, you would not be able to experience your body, and experience the world. Every concept that you conjure up from your mind is a sort of loose association of your sensorimotor input. How can a robot understand the concept of a strawberry if all it can perceive of it is its shape and color and maybe the sound that it makes as it gets squished? How can you understand the "abstract" notion of strawberry without the incredibly sensible tactile feel, without the act of ripping off the stem, without the motor action of taking it to our mouths, without its texture and taste? When we as humans summon the strawberry thought, all of these concepts and ideas converge (distributed throughout the neurons in our minds) to form this abstract concept formed out of all of these many many correlations. A robot with no touch, no taste, no delicate articulate motions, no "serious" way to interact with and perceive its environment, no massive flow of information from which to chose and and reduce, will never attain human level intelligence.

    That's point 1. Point 2 is that mere pattern recogn
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    All information *that gets processed* gets processed but now we arrived at a tautology. The whole problem is ultimately nobody knows what gets processed (not to mention how). In fact an absolute statement "all information" gets processed is very easy to dismiss because the characteristics of our sensors are such that a lot of information is filtered out already at the input level (e.g. eyes). I'm not saying it's not a valid and even interesting assumption, but it's still just an assumption and the next step is to explore scientifically where it leads you. And until you show its superiority experimentally it's as good as all other alternative assumptions you can make.

    I only wanted to point out is that "more processing" is not exactly compatible with some of the fundamental assumptions of the embodiment. I recommend Wilson, 2002 as a crash course.
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    These deal with different things in human intelligence. One is the depth of the intelligence (how much of the bigger picture can you see, how abstract can you form concept and ideas), another is the breadth of the intelligence (how well can you actually generalize, how encompassing those concepts are and what is the level of detail in which you perceive all the information you have) and another is the relevance of the information (this is where the embodiment comes in. What you do is to a purpose, tied into the environment and ultimately linked to survival). As far as I see it, these form the pillars of human intelligence, and of the intelligence of biological beings. They are quite contradictory to each other mainly due to physical constraints (such as for example energy usage, and training time).

    "More processing" is not exactly compatible with some aspects of embodiment, but it is important for human level intelligence. Embodiment is necessary for establishing an environmental context of actions, a constraint space if you will, failure of human minds (i.e. schizophrenia) is ultimately a failure of perceived embodiment.

    What we do know is that we perform a lot of compression and a lot of integration on a lot of data in an environmental coupling. Imo, take any of these parts out, and you cannot attain human+ intelligence. Vary the quantities and you'll obtain different manifestations of intelligence, from cockroach to cat to google to random quake bot. Increase them all beyond human levels and you're on your way towards the singularity.
johannessimon81

Computing with RNA - 0 views

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    After a discussion this morning on robust computing and possible implementations in biological systems I found this really nice result (from 2008) on molecular RNA computers that get assembled within cells and perform simple functions. Of course by having different types of computers within the same cell one could go on to process the output of the other and more complex computations could be executed... Food for thought. :-)
Thijs Versloot

Autonomous drones flock like birds (video) #Nature - 2 views

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    A Hungarian team has created the first drones that can fly as a coordinated flock. The researchers watched as the ten autonomous robots took to the air in a field outside Budapest, zipping through the open sky, flying in formation or even following a leader, all without any central control.
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    old news, but wow .... Nature is becoming more and more like a magazine and less and less a scientific journal. This stuff is highly irrelevant but to the group that did it.
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    this is not a nature paper but just an article on their website - the papers they provide as references are all old
Guido de Croon

Robot termites able to build various structures - 0 views

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    Nice application of swarm robotics for building various structures. See the video at: http://www.youtube.com/watch?v=LFwk303p0zY Their compilation process of a desired structure into local behavior rules seems of most interest.
johannessimon81

Big data, bigger expectations? - 1 views

johannessimon81

Innovative Birds Are Also Less Flexible Learners - 1 views

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    Innovative individuals are less flexible learners while innovative species are also at the same time more flexible.
Guido de Croon

Robot dragonfly DelFly Explorer avoids obstacles by itself - 1 views

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    TU Delft researchers have developed the DelFly Explorer, the world's first Micro Air Vehicle with flapping wings that can avoid obstacles by itself. The uniqueness of this achievement lies in the DelFly Explorer's very low weight (20 grams, i.e. a few sheets of paper), and this opens up new possible applications for both smaller and larger MAVs.
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    I'm kinda curious what you used for processing power there. Is that a DSP?
Thijs Versloot

Challenges for #AI in #Smartgrids - 0 views

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    The Northeast Blackout of 2003 that forced the shut-down of over 100 power plants and affected 55M people - the largest black-out in US history - was precipitated by a single overloaded transmission line, in Ohio, sagging and touching overgrown vegetation.
Tom Gheysens

Computer searches web 24/7 to analyze images and teach itself common sense - 0 views

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    Now this is a step in the right direction of the discussion we had in one of the wednesday meetings "thoughts of a biologist part 1"
    :)
johannessimon81

IBM Speech Recognition, 1986 - 0 views

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    Interesting historical perspective. Progress since the late '80 really seems to be fairly slow.
    ?: Do we need to wait for the singularity until speech recognition works without flaws?
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    funny - tried just yesterday the one built in on mavericks: sending one email took three times as long at least as typing it
    And now my speech PowerPoint

    Funny, trade trust yesterday they're built in speech recognition in Mavericks sending one e-mail to at least three times a talk as long as typing it. Well this was actually quite okay and relatively fast cheers nice evening
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    "I thought I would give it a try on my android sexy seems to work pretty well and I'm speaking more less at normal speed"

    Actually I was speaking as fast as I could because it was for the google search input - if you make a pause it will think you finished your input and start the query. Also you might notice that Android thinks it is "android sexy" - this was meant to be "on my Android. THIS seems to work...". Still it is not too bad - maybe in a year or two they have it working. Of course it might also be that I just use the word "sexy" randomly... :-\
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    The problem is that we don't yet understand how speech in humans actually works. As long as we merely build either inference or statistical language models we'll never get perfect speech recognition. A lot of recognition in humans has a predictive/expectational basis to it that stems from our understanding of higher lvl concepts and context awareness. Sadly I suspect that as long as machines remain unembodied in their perceptual abilities their ability to either properly recognize sounds/speech or objects and other features will never reach perfection.
Tom Gheysens

New theory of synapse formation in the brain - 2 views

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    I have no idea if an algorithm based on this already exists, but it would certainly be a good one for autonomous AI, I think.

    I think an algorithm based on this should be able to select his own input parameters and reject them if they are not stimulated any further or integrate them in the algorithm if they are continiously stimulated... this could enable self learning, etc.
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    By steering the neuron's back to an intermediate activity level the mechanism probably optimizes their efficiency within the network (after all a neuron that fires all the time is just as useless as one that never fires).
johannessimon81

3,000 Years of Human History, Described in One Set of Mathematical Equations - 2 views

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    Reminds me of psychohistory in Asimov's Foundation trilogy
johannessimon81

Software Makes 3-D Models From Any Photo - 3 views

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    Video shows how easy the process is and how cool the results look. Does anybody know a potential scientific application for such image processing?
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    this is very impressive indeed ... looks like the manual steps they are doing could be automatised, can't they?
johannessimon81

Scientist controls colleague's hand in first human brain-to-brain interface - 1 views

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    The telepathic cyborg lives, sort of. University of Washington scientists Rajesh Rao and Andrea Stocco claim that they are the first to demonstrate human brain-to-brain communication. Rao sent a signal into a Stocco's brain via the Internet that caused him to move his right hand.
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