Its purpose is to develop products that have the potential to make a large positive impact on society. In 2006 an internal company memo said that Google wants to have the world's top AI research laboratory.
He says that Google are currently applying these networks to other applications too, such as image recognition, language modeling, and machine translation. Deep networks, also known as deep belief networks, are a type of artificial neural network. It is unknown whether this is the standard production configuration in all Google data centers. Driverless Car - this project is currently being led by Google engineer Sebastian Thrun, director of the Stanford Artificial Intelligence Laboratory and co-inventor of Google Street View.
Thrun's team at Stanford created the robotic vehicle Stanley which won the 2005 DARPA Grand Challenge and its US$2 million prize from the United States Department of Defense. The team developing the system consisted of 15 engineers working for Google, including Chris Urmson, Mike Montemerlo, and Anthony Levandowski who had worked on the DARPA Grand and Urban Challenges.
Majel wasn't necessarily developed within Google X, it might simply have been a standard Google research project. They've also speculated on interfacing all of the world's information directly to your brain. AI happens it's going to be a lot of computation and not so much clever algorithms but just a lot of computation. Larry Page has been quoted as saying that "when artificial intelligence happens it will be not so much clever algorithms but just a lot of computation". As of January 2012 it was estimated that Google has around 1.8 million servers housed in its data centers worldwide.


It turns out that the Google platform has more computational power than the world's largest supercomputer. 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. The robot itself isn't particularly advanced because the focus was not on mechanics, but rather the software.
I have had the chance to interact with the robot personally and it is honestly the most amazing thing that I have ever seen.
Follow up comments by J32PMXR say the robot has a suite of sensors including optical, laser, infrared, ultrasonic, and depth cameras.
Replies to the posting express skepticsm, but they also admit that Google is likely working in a similar direction.
But the chances seem very low that a group of staff were fired and that one of them posted about it in public. Solve for X is a forum to encourage and amplify technology-based moonshot thinking and teamwork.
Initially, much of the blogosphere and mainstream media reported this as being the same as Google X. They have often talked about making Google Search artificially intelligent so that it understands exactly what information you're seeking.
But in a paper released in 2009 it was suggested that each server contained two dual-core processors.
As of October [2011] (the last time I was around the project), the artificial intelligence had passed the Turing Test 93% of the time via an hour long IM style conversation.
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.


It can supposedly lip read, although that might be restricted to detecting emotion such as a smile. This went into effect on March 1, 2012, and the Nevada Department of Motor Vehicles issued the first license for a self-driven car in May 2012. We don't know what the processor specifications are, but we do know that Google tends to use cheap, low-performance hardware and lots of it. This is a fair comparison too because Google does in fact view their platform not as a collection of data centers, but as a single supercomputer.
IM was chosen to isolate the AI from the speech synthesizer and physical packaging of the robot. 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.
If we make an educated guess that each processor runs at 2 GHz, and we know the number of processors per server, and the number of servers, then we can make an estimate of the total computational power.
The total power of the platform, however, is not yet sufficient to run a complete human brain simulation - supposing that the same simulation architecture were used as in the Blue Brain Project. In a few years time the Google platform should be sufficiently powerful to run a complete simulation of a human brain, including displays of intelligence and self-awareness.
A stated goal is to enable intelligent conversation with your mobile phone, similar to Apple's Siri but more advanced.



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