When artificial intelligence first came about in the first computing machines, computing was restricted by technology and computing power. The easiest way to get around giving intelligent functions to a machine was to give it basic sets of rules. These finite set of rules took up small amounts of memory, and could be used dependent on the input and goal. The rules could be combined to create more complex functions, exponentially increasing the amount of total functions available.
The current computing grew from these beginnings, now using complex algorithmic and recursive functions using basic rules to further increase the amount of computing possibilities. The search for true artificial intelligence, one comparable to our amount of intelligence and conscious awareness, is in the works. A robotic creation using transistors and circuits and algorithmic programming whilst having the conscious and cognitive abilities that humans possess is the end goal. We know so far that even the most advanced artificial intelligence makes semantic and perceptual errors about the physical world.
The problem with creating an artificial intelligence like our own is the rule-based computing which is the seed of modern computing intelligence. The seed planted was a rule-based one, and since we used these seeds to grow modern computing, we now have this type of computing available. I strongly believe this rule-based computing will never allow for true human-based artificial intelligence to be used. Human cognition and consciousness is not a rule-based system, and rule-based systems are not able to perform the amount and type of processing that the human mind does.
The human mind processes information in bottom-up and top-down processes by integrating sensory info and semantic knowledge in integration centers of the brain. The mind can take this info and again reanalyze in in a seemingly subjective fashion, or by applying further conscious reason to perform a reaction to the input info. The mind has the ability to consciously engage ideas in the brain in a way that doesn’t seem to obey rules.
Humans can be argued to be mostly a tabula rasa (blank slate) at birth, with arguably some innate abilities; perhaps there are some undefined “rules”. To create a “fully grown” and “mature” robot instantaneously, as well as endow it with all the knowledge of the world and processing an adult human would possess is a disastrous thought. We can’t program a mature robot, we need to grow it. Create a robot with the ability to learn, and to perform connections by repeated pairings of stimuli. A robot would be endowed with the learning abilities of which humans possess, so that it may learn connections in the world and be endowed with human-type knowledge and ability. The way we “program” robots now with artificially intelligent algorithms does not begin to scratch the surface of human knowledge ability.
A robotic creation as a “newborn” with very few programmed rules besides rules for stimuli pairing, feature detection, whilst integrating the perceptual info similar in fashion to how the info bonds and integrates in the human brain is essential. No need for large highly complex algorithmic programs, we set a few basic algorithms, and allow the robot to “learn” the world on its own. While this is a long process, I believe it is the closest approximation to a human-like artificial intelligence. We bare the robot, and allow it to grow and mature in the human world by interaction with the world and gaining knowledge in the fashion that we do. This is the only way to create a robot which can be perceptually and semantically comparable to a human.
This post was inspired by this video on cognitive science: https://youtu.be/0T_nOzpBYxU
iOS app by Tim Sears for iPhone X lets you make your own Augmented Reality face masks which you can draw or import an image from your camera roll:
Face Maker Augmented Augmented is an exciting new way to shape the face around you. Using the TrueDepth camera technology of the iPhone X, along with new capabilities of ARKit, you can create incredible face experiences like never before.
More Here
the last evening was a cool sightseeing tour, absolutly HOT #love #instagood #photooftheday #beautiful #fashion #happy #tbt #cute #followme #like4like #selfie #summer #fun #smile #style #amazing #sun #bestoftheday #pretty #cool #funny #ootd #potd #holiday #lifestyle #일상 #sweet #happiness #awesome #travel
Latest Nat & Friends showcases a selection of web based experiments exploring sound and music (plus a couple of Google assistant easter eggs):
Music is a fun way to explore technologies like coding, VR, and machine learning. Here are a few musical demos and experiments that you can play with – created by musicians, coders, and some friends at Google.
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There’s been some interesting developments recently in adversarial training, but I thought it would probably be a good idea to first talk about what adversarial images are in the first place. This Medium article by @samim is an accessible explanation of what’s going on. It references this talk by Ian Goodfellow, asking if statistical models understand the world.
Machine learning can do amazing magical things, but the computer isn’t looking at things the same way that we do. One way to exploit that is by adding patterns that we can’t detect but that create enough of a difference in the data to completely fool the computer. Is it a dog or an ostrich?
There’s been quite a lot of research into finding ways round this problem as well as exploiting it to avoid facial recognition or other surveillance. And, like I said, there’s been some interesting recent developments that I hope to talk about here.
https://medium.com/@samim/adversarial-machines-998d8362e996#.n7j43766v
Polish website just used a screenshot of Avina in an article about AI. I’m dying.
Digital comic by Andre Bergs features animated frames which you can change the angle by tilting the device, and created using the Unity engine:
A post shared by André Bergs (@andre.bergs) on Oct 3, 2017 at 8:19am PDT
A post shared by André Bergs (@andre.bergs) on Sep 15, 2017 at 9:06pm PDT
Protanopia is a digital comic for Ipad and Iphone. Created as an experiment into the possibilities of digital comics. Using elements from 3D and 2D animation in a realtime game engine, it creates an unique visual style, whilst still having a familiar feeling.
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Apple Patents for Automatic 3D Avatar Creation and Emotional States
Something to expect in the future in regards to online identity (both of which were filed today):
A three-dimensional (“3D”) avatar can be automatically created that resembles the physical appearance of an individual captured in one or more input images or video frames. The avatar can be further customized by the individual in an editing environment and used in various applications, including but not limited to gaming, social networking and video conferencing.
I wonder if this will be connected to Apple’s purchase of depth sensor company Primesense [Link to patent file]
Methods, systems, and computer-readable media for creating and using customized avatar instances to reflect current user states are disclosed. In various implementations, the user states can be defines using trigger events based on user-entered textual data, emoticons, or states of the device being used. For each user state, a customized avatar instance having a facial expression, body language, accessories, clothing items, and/or a presentation scheme reflective of the user state can be generated.
[Link to patent file]
Hands-On Python & Xcode Image Processing: Build Games & Apps ☞ http://go.learn4startup.com/H1iINoD7z
#DeepLearning
SP. 114 - Ghost in the Shell (2017)
Repairing the robotic hand.