An artificial Age is coming upon the shores of the world at an exponential rate, and if things don’t slow down – there will be no going back. Big Tech companies like Google, Microsoft, and Apple are all working on “new” technologies that in collusion with Big Government Divisions like the CIA will paint a very, very 1984 picture of the USA.
Imagine a world where your smartphone doesn’t just track your phone calls, and your pictures but rather every single word you say. Imagine a world where every single thought, action, and emotion was recorded and deciphered by the likes of the CIA. Rather than expand the divisions of government for cyber warfare, the government is looking to expand its branches in Artificial Intelligence.
Artificial Intelligence (AI) is categorized into two sections, Generalized AI and Specialized AI. Technically those terms refer to the same monster. Except the two sections pertain to different smaller divisions within Artificial Intelligence.
Generalized AI –
Artificial general intelligence (AGI) is the intelligence of a (hypothetical) machine that could successfully perform any intellectual task that a human being can. It is a primary goal of artificial intelligence research and an important topic for science fiction writers and futurists. Artificial general intelligence is also referred to as “strong AI”, “full AI” or as the ability of a machine to perform “general intelligent action”.
Some references emphasize a distinction between strong AI and “applied AI” (also called “narrow AI” or “weak AI”: the use of software to study or accomplish specific problem solving or reasoning tasks. Weak AI, in contrast to strong AI, does not attempt to perform the full range of human cognitive abilities.
Specialized AI is where an artificial intelligence is geared toward specific tasks whereas generalized AI tries to encompass the entirety of human cognition. For example, in regards to video games – the Artificial Intelligence is equipped to beat the human player. Some key examples of specialized Artificial Intelligence are Google’s AI which beat the world champion at the Chinese game of Go. Go is an Asian game that is famous for its deep complexity, unlimited possibility of moves and strategic thinking. Unlike previous AI victories — such as Deep Blue’s defeat of chess grandmaster Garry Kasparov in 1997, or IBM Watson’s Jeopardy triumph in 2011 — Google’s DeepMind programmed AlphaGo to be capable of (teaching itself,) not just carrying out a set of fixed moves or activities.
Artificial Intelligence, is a rapidly growing field and giving the machines power to teach themselves will result in disaster. Obama even specified a few of those scenarios in the November issue of Wired. (See videos below)
Artificial Intelligence’s ability to play games isn’t the intention of this report, but rather the game’s show the progress in exponential steps of specialized AI.
DeepMind by Google
Google’s DeepMind AI, is now capable of teaching itself rather than having a human input new algorithms and programming; which means that the AI can learn from information it already possesses. DeepMind technology is based on the parent company of Google, Alphabet’s, hybrid system called Differential Neural Computer or (DNC). The system uses a neural net to parse the data.
Neural Networks (also referred to as connectionist systems) are a computational approach which is based on a large collection of neural units loosely modeling the way the brain solves problems with large clusters of biological neurons connected by axons. Each neural unit is connected with many others, and links can be enforcing or inhibitory in their effect on the activation state of connected neural units.
In other words, instead of the AI having to learn every possible outcome to find the solution, DeepMind can derive an answer from prior experience, unearthing the answer from its internal memory rather than from outside programming. Meaning that the Artificial Intelligence can remember “experiences” and apply that into processing the problem at hand.
Conversational Speech Recognition
With Google programming the DeepMind to “think like a human,” Microsoft has taught their AI to understand conversations on par with Humans. Microsoft’s Artificial Intelligence and Research division developed a speech recognition system that makes the same or fewer errors than professional transcriptionists. The researchers reported a word error rate (WER) of 5.9 percent, down from the 6.3 percent WER the team said just last month.
The 5.9 percent error rate is about equal to that of people who were asked to transcribe the same conversation, and it’s the lowest ever recorded against the industry standard Switchboard speech recognition task. Essentially meaning that Microsoft’s program or AI could interpret a full-on conversation and decipher almost perfectly exactly what the conversation entailed.
Virtually every word in every conversation within reach of a microphone could soon be understood by an AI, and “remembered” by another AI all connected through the ‘Neural Net’ of Google or a Government. The two tech giants have created and practically perfected machines that can both remember and learn; plus hear and interpret. But what about the visuals?
Enter IARPA and DARPA
Facial recognition software has vastly improved since it’s beginning. The government is heavily invested in perfecting the methodology it uses on its citizens. In fact, due to IARPA’s Projects ‘Janus,’ and ‘Thor’ tricking biometric face scanners will soon be a thing of the past. Especially under Project Thor which is designed to identify “spoofers,” by aiming to stop the so-called presentation attacks. These “attacks” make it difficult for biometric databases to identify subjects correctly. This might involve using a prosthetic to either hide the subject’s real prints or to present someone else’s.
Thor is set to go into effect in 2017 and run for at minimum four years.
While IARPA and DARPA build programs which will enable continuous surveillance of American citizens, the CIA is selling surveillance software to public schools to track children and teenagers. The company Geofeedia consistently sold surveillance technology, typically only bought by police, to a high school in a northern Chicago suburb, less than 50 miles from where the company was founded in 2011.
In the fall of 2014, the Lincolnshire-Prairie School District paid Geofeedia $10,000 to monitor the social media posts of children at Adlai E. Stevenson High School.
“We did have for one year a contract with Geofeedia,” said Jim Conrey, a spokesperson for Lincolnshire-Prairie School District. “We were mostly interested in the possibility of trying to prevent any kind of harm, either that students would do to themselves or to other students.”
Conrey said the district simply wanted to keep its students safe. “It was really just about student safety; if we could try to head off any potential dangerous situations, we thought it might be worth it,” he said.
The software monitored social media posts and was operated by police liaison stationed on the school ground. While the school claims it was for the “safety of its students” the software tracked every post and location each teenager made. While the claims they school had roughly “no use” for the software, the truth is the CIA-backed company Geofeedia did.
The actual software is outwardly presented as a tool for location-based marketing—and counting among its client’s companies such as Dell and CNN. Geofeedia derives a significant portion of its revenue from U.S. law enforcement and intelligence agencies. Over 500 law enforcement agencies use the company who also received an investment from the Central Intelligence Agency’s venture capital arm.
The surveillance technology uses an artificial intelligence algorithm to both predict and analyze social media content posted around the globe. The company claims “Our patented, cloud-based, location-based intelligence platform lets you predict, analyze, and act on real-time social media content by location from anywhere in the world—with a single click.” It’s rather evident that law enforcement agencies do not need this sort of tracking technology to “Respond effectively and efficiently based on real-time location-based insights,” to teenagers and children.
Furthermore, where is all of this technology coming from and what is the ‘hidden’ purpose of it? One glance at who Apple is hiring and the answer to both questions is rather clear. Apple recently employed a tech guru, Ruslan Salakhutdinov a professor at Carnegie Mellon University, who taught computers to ‘defeat humans.’
Taking it a step further than the Chinese game of Go, chess, or jeopardy; the professor taught Students at Salakhutdinov’s University to build a “bot” capable of beating humans at the “shoot ’em up game” Doom.
Doom is a series of first-person shooter video games developed by id Software. The series focuses on the exploits of an unnamed space marine operating under the auspices of Union Aerospace Corporation (UAC), who fights hordes of demons and the undead in order to survive.
Teaching an AI violence?
Without morality, a soul, and or a conscious, if that ‘bot’ were to have access to any form of computer-controlled military weaponry – the end is apparent.
In conclusion, if the Tech Giants were to collude together on say some ‘hidden project’ to build an artificial brain which practically mimicked the human brain – they are more than half way there. To add support to the previous statement, a quick examination of the BRAIN Initiative and the Human Brain Project, the answer is the answer is clear – both the tech giants and the governments of the world are working together to create a machine(s) that directly mimics that of a human brain.
- The BRAIN Initiative, (Brain Research through Advancing Innovative Neurotechnologies), is a collaborative, public-private research initiative announced by the Obama administration on April 2, 2013.
- The Human Brain Project (HBP) is a large ten-year scientific research project that aims to build a collaborative ICT-based scientific research infrastructure to allow researchers across the globe to advance knowledge in the fields of neuroscience, computing, and brain-related medicine. The Project, which started on 1 October 2013, is a European Commission Future and Emerging Technologies Flagship. The HBP is coordinated by the École Polytechnique Fédérale de Lausanne and is largely funded by the European Union. The project is based in Geneva, Switzerland.
Is it a coincidence that so much ‘progress’ is taking place directly before the Obama Administration “leaves” the White House? Or are the tech giants and governments gearing humanity up for the next phase of Artificial intelligence?
Bryan Clark. “Google’s ‘DeepMind’ AI platform can now learn without human input.” TNW. . (2016): . . http://bit.ly/2eprknB
Allison Linn. “Historic Achievement: Microsoft researchers reach human parity in conversational speech recognition.” Microsoft Blog. . (2016): . . http://bit.ly/2eommfp
Kevin Collier. “Study: 1 in 2 American Adults Already In Facial Recognition Network.” Vocativ. . (2016): . . http://voc.tv/2edrHGF
Dell Cameron. “CIA-backed surveillance software was marketed to public schools .” The Daily Dot. . (2016): . . http://bit.ly/2eprawK
Jasper Hamil. “Apple employs tech guru from university that taught computers to ‘defeat humans’.” The Sun. . (2016): . . http://bit.ly/2eyEjme
Mohana Ravindranath. “IARPA Wants To Stop You From Spoofing Facial Scans and Fingerprints.” Next Gov. . (2016): . . http://bit.ly/2eprZ8D
IARPA. “Research Programs Janus .” IARPA. . (NA): . . http://bit.ly/2eyI7nK
Jon Russell. “Google AI beats Go world champion again to complete historic 4-1 series victory.” Tech Crunch. . (2016): . . http://tcrn.ch/2ebOu3c