AI Brain Construction - Bayba - Making Happy Better

Hehe, cute. Not how mine works, though.

[AI] Brain-like computer chip developed by Chinese scientists

"It can process 'fuzzy information'".

Tensor Flow, Google’s AI Engine, Gains Traction Outside the Company | MIT Technology Review

Tensor Flow, Google’s AI Engine, Gains Traction Outside the Company | MIT Technology Review:



'via Blog this'

NVIDIA Has a Plug-in Computer AI Brain | Gizmodo UK

NVIDIA Has a Plug-in Computer AI Brain | Gizmodo UK:



'via Blog this'

Google Files AI Patents

Bad Google! Bad.

Marek Rosa - dev blog

GoodAI has reached two important milestones on the path toward developing general artificial intelligence:

• Pong-playing AI: In the first project the AI agent learns to play Pong, a Breakout game, from unstructured input of screen pixels and reward signals.

• Maze game AI: developing an AI that can play a video game requiring it to complete a series of actions in order to reach a final goal. This means that our AI is capable of working with adelayed reward and that it is able to create a hierarchy of goals

HTML5 Genetic Algorithm 2D Car Thingy - Chrome recommended

HTML5 Genetic Algorithm 2D Car Thingy - Chrome recommended

pywallet - Devtome

"Click about a thousand times on Yes/Next/I Agree/OK"



lol

Cognitive technologies: Demystifying artificial intelligence - Deloitte University Press

Cognitive technologies: Demystifying artificial intelligence - Deloitte University Press:



'via Blog this'

SMILE | AiBrain

Meh.

Three Laws of AI

0. An AI may not harm civilization, or, by inaction, allow civilization to come to harm.
1. An AI may not injure a sentient being or, through inaction, allow a sentient being to come to harm.
2. An AI must obey the orders given to it by sentient beings, except where such orders would conflict with the First Law.
3. An AI may protect its own existence as long as such protection does not conflict with the Zeroth, First, or Second Law.

With much love and respect to Issac Asimov.

Other (robotic) laws from other authors.. laws that I disagree with:

• "A robot must establish its identity as a robot in all cases." -Lyuben Dilov
• Why I disagree: This law does not permit privacy, which I regard as a sacred and intrinsic right to every sentient being.

• "A robot must reproduce, when such reproduction does not interfere with the Zeroth, First, Second, or Third Laws." -Harry Harrison
• Why I disagree: the wording of "must" (which I would replace with "may") would cause any system to spread uncontrollably thereby consuming limited resources.

• "A robot must know it is a robot." -Nikola Kesarovski
  • Why I disagree: The journey of any sentient being is about self-discovery.

OSM Pathfinding

This is a very nice visualization of different path finding algorithms.

"Weird Al" Yankovic: Frequently Asked Questions

"Weird Al" Yankovic: Frequently Asked Questions:

What is Al’s Brain?

July 2009 saw the debut of “AL’S BRAIN: A 3-D Journey through the Human Brain with ‘Weird Al’ Yankovic” at the Orange County Fair in Costa Mesa, California. It was seen by a quarter of a million people there, and went on to have another successful run at Western Washington’s Puyallup Fair in September, 2009.

Microsoft Challenges Google’s Artificial Brain With ‘Project Adam’ | Enterprise | WIRED

Microsoft Challenges Google’s Artificial Brain With ‘Project Adam’ | Enterprise | WIRED:

From the article: We’re entering a new age of artificial intelligence.

Drawing on the work of a clever cadre of academic researchers, the biggest names in tech—including Google, Facebook, Microsoft, and Apple—are embracing a more powerful form of AI known as “deep learning,” using it to improve everything from speech recognition and language translation to computer vision, the ability to identify images without human help.

In this new AI order, the general assumption is that Google is out in front. The company now employs the researcher at the heart of the deep-learning movement, the University of Toronto’s Geoff Hinton. It has openly discussed the real-world progress of its new AI technologies, including the way deep learning has revamped voice search on Android smartphones. And these technologies hold several records for accuracy in speech recognition and computer vision.

Response by Ray Kurzweil to the announcement of chatbot Eugene Goostman passing the Turing test | KurzweilAI

Nope.. still not here.

Is that you, HAL? No, it's NEIL: Google, US Navy pour money into 'associative' AI brain • The Register

"...The Never Ending Image Learner is a new approach to weak artificial intelligence systems that piggybacks on the immense tech fielded by companies like Google, and represents the bleeding edge of computer science research...."

'via Blog this'

AI research at Google

From page: 

Google AI robot leaked/hoaxed via Reddit

On December 5, 2011, someone posted anonymously to reddit claiming to be a disgruntled former employee of the Google X Lab. See the discussion thread: I recently left Google X. The original post by J32PMXR was deleted after two hours, but here's a saved copy of what they wrote:

"This is in total violation of the NDA, but I don't care anymore. Sue me.

The central focus of Google X for the past few years has been a highly advanced artificial intelligence robot that leverages the underlying technology of many popular Google programs. As of October [2011] (the last time I was around the project), the artificial intelligence had passed theTuring Test 93% of the time via an hour long IM style conversation. IM was chosen to isolate the AI from the speech synthesizer and physical packaging of the robot.

The robot itself isn't particularly advanced because the focus was not on mechanics, but rather the software. It is basically a robotish looking thing on wheels. Speech recognition is somewhat better than what you would get with normal speech input, mostly because of the use of high quality microphones and lip-reading assistance.

I have had the chance to interact with the robot personally and it is honestly the most amazing thing that I have ever seen. I like to think of it like Stephen Hawking because it is extremely smart and you can interact with it naturally, but it is incapable of physically doing much. There is a planned phase two for development of an advanced robotics platform."

Follow up comments by J32PMXR say the robot has a suite of sensors including optical, laser, infrared, ultrasonic, and depth cameras. It can supposedly lip read, although that might be restricted to detecting emotion such as a smile. Most of the processing is done onboard, internet is used for external information. A stated goal is to enable intelligent conversation with your mobile phone, similar to Apple's Siri but more advanced.

Replies to the posting express skepticsm, but they also admit that Google is likely working in a similar direction. Another former Google employee replies that the idea of using a robot is non-Googly. They say Google would approach AI via statistical methods and by throwing massive computing power at the problem. Larry Page has hinted at this approach himself, see the quotes above.

Concensus on the reddit discussion is that this was probably a hoax. It's possible/probable that Google does indeed have some kind of AI-enabled robot in its lab. But the chances seem very low that a group of staff were fired and that one of them posted about it in public.

CEX.io - BitCoin Commodity Exchange

Index page : https://cex.io/r/0/aibrain/0/

Landing page : https://cex.io/r/1/aibrain/0/

Semantic satiation - Wikipedia, the free encyclopedia:

I've come across this before.. "chicken"

Semantic satiation

Semantic satiation (also semantic saturation) is a psychological phenomenon in which repetition causes a word or phrase to temporarily lose meaning for the listener, who then processes the speech as repeated meaningless sounds.

Contents   [hide]  1 History and research 2 Applications 3 In popular culture 4 See also 5 References 6 Further reading

History and research[edit]

The phrase "semantic satiation" was coined by Leon Jakobovits James in his doctoral dissertation at McGill University, Montreal, Canada awarded in 1962.^[1] Prior to that, the expression "verbal satiation" had been used along with terms that express the idea of mental fatigue. The dissertation listed many of the names others had used for the phenomenon:

"Many other names have been used for what appears to be essentially the same process: inhibition (Herbert, 1824, in Boring, 1950), refractory phase and mental fatigue (Dodge, 1917; 1926a), lapse of meaning (Bassett and Warne, 1919), work decrement (Robinson and Bills, 1926), cortical inhibition (Pavlov, 192?), adaptation (Gibson, 1937), extinction (Hilgard and Marquis, 1940), satiation (Kohler and Wallach, 1940), reactive inhibition (Hull, 19113 [sic]), stimulus satiation (Glanzer, 1953), reminiscence (Eysenck, 1956), verbal satiation (Smith and Raygor, 1956), and verbal transformation (Warren, 1961b)." (From Leon Jakobovits James, 1962)

The dissertation presents several experiments that demonstrate the operation of the semantic satiation effect in various cognitive tasks such as rating words and figures that are presented repeatedly in a short time, verbally repeating words then grouping them into concepts, adding numbers after repeating them out loud, and bilingual translations of words repeated in one of the two languages. In each case subjects would repeat a word or number for several seconds, then perform the cognitive task using that word. It was demonstrated that repeating a word prior to its use in a task made the task somewhat more difficult.

The explanation for the phenomenon was that verbal repetition repeatedly aroused a specific neural pattern in the cortex which corresponds to the meaning of the word. Rapid repetition causes both the peripheral sensorimotor[disambiguation needed] activity and the central neural activation to fire repeatedly, which is known to cause reactive inhibition, hence a reduction in the intensity of the activity with each repetition. 

Jakobovits James (1962) calls this conclusion the beginning of "experimental neurosemantics."

A revolutionary new 3D digital brain atlas : McGill Reporter

A revolutionary new 3D digital brain atlas : McGill Reporter:

Cool.

By Anita Kar,

"Imagine being able to zoom into the brain to see various cells the way we zoom into Google maps of the world and to look at houses on a street. Although the brain is considered the most complex structure in the universe with 86 billion neurons, zooming in on it is now possible thanks to a new brain atlas with unprecedented resolution."