Is Facebook the 'SkyNet' from Terminator?

The human brain is a dense network of 10 billion neurons. On average, each neuron is connected to other neurons through about 10 000 synapses. The network of neurons and synapses exchange a huge amount of data and also process information from the data in parallel and lightning speed. If we imagine each neuron as a human brain and the synapses as the internet through which share and process information today, a highly penetrated social media network such as Facebook already resembles a huge brain. Can this 'brain' take a shape of its own and become an intelligent being? All it needs is to become self aware! Can that happen?

Let's consider the hypothetical case that this could happen. It would lead us to think that someone at Facebook HQ might one day have the ability to switch on and, hopefully, also kill this self aware intelligent being (Like the fictional Skynet in Terminator). Maybe Facebook is already researching about this. Oh wait, yes! Facebook has a department called FAIR - Facebook's Artificial Intelligence Research. So, what does the director of this department, Mr. Yann LeCun think?

"Right now, even the best AI systems are dumb," LeCun told Popular Science's Dave Gershgorn. "They don't have common sense." Researchers have created artificial narrow intelligence (ANI) — programs that are very good at very specific tasks, like IBM Watson's Jeopardy-playing supercomputer or a world-champion-beating chess program. But no computer scientist or AI researcher yet knows how to make artificial general intelligence (AGI), programs that are capable of exhibiting human-level intelligence on multiple tasks. For AGI to exist, computers would need to be imbued with common sense reasoning, the ability to encounter new situations and make inferences about what's happening and what needs to be done.

LeCun told Tech Insider that one of the biggest obstacles to endowing machines with this kind of common sense is getting machines to learn in an "unsupervised manner, like babies and animals do."

"Right now, the way we train machines is 'supervised,' a bit like when we show a picture book to a toddler and tell them the name of everything," LeCun said. This kind of learning can teach the program to make connections, but not the "common sense" of why those connections exist and how they apply to other real world situations. We still haven't figured out the best way to teach AI that kind common sense yet, LeCun told Tech Insider, which means we still don't know how to make our AI any smarter.

Is Facebook right when they dismiss this possibility by saying even the best AI systems are dumb?

Or is Facebook playing dumb as the first super intelligent 'unsupervised' machine is taking shape right before their eyes?

With Huge Power Comes Huge Responsibility

In a BBC news article published yesterday, BBC's Kamal Ahmed interviewed Demis Hassabis, the head of DeepMind, Google's $800 million machine learning business and one of the world's leading authorities on the subject. In the interview, Mr. Hassabis, also Deep Mind's co-founder, has now called for a responsible debate about the role of ethics in the development of artificial intelligence.

"I think artificial intelligence is like any powerful new technology," Mr Hassabis said, "It has to be used responsibly. If it's used irresponsibly it could do harm".

Mr Hassabis was responding to concerns about the development of artificial intelligence raised, among others, by Elon Musk, the technology entrepreneur and a DeepMind investor, and Professor Stephen Hawking. 

In other news covered by BBC on 15th September 2015, they point out that by 2050 some experts believe that machines will have reached human level intelligence. Thanks, in part, to a new era of machine learning, computer are already starting to assimilate information from raw data in the same way as the human infant learns from the world around her. It means we are getting machines that can, for example, teach themselves how to play computer games and get incredibly good at them (work ongoing at Google's DeepMind) and devices that can start to communicate in human-like speech, such as voice assistants on smartphones. Computers are beginning to understand the world outside of bits and bytes.

The article summarizes a timeline of Artificial Intelligence as listed below.

AI Timeline

• 1951 - The first neural net machine SNARC was built and in the same year, Christopher Strachey wrote a checkers programme and Dietrich Prinz wrote one for chess.

• 1957 - The General Problem Solver was invented by Allen Newell and Herbert Simon.

• 1958 - AI pioneer John McCarthy came up with LISP, a programming language that allowed computers to operate on themselves.

• 1960 - Research labs built at MIT with a $2.2m grant from the Advanced Reserch Projects Agency - later known as Darpa

• 1960 - Stanford AI project founded by John McCarthy.

• 1964 - Joseph Weizenbaum created the first chatbot Eliza, which could fool humans but repeated back what was said to her.

• 1968 - Arthur C. Clarke and Stanley Kubrick immortalised Hal, that classic vision of a machine that would match or exceed human intelligence by 2001.

• 1973 - A report on AI research in the UK formed the basis for the British government to discontinue support for AI in all but two universities.

• 1979 - The Stanford Cart became the first computer-controlled autonomous vehicle when it circumnavigated the Stanford AI lab.

• 1981 - Danny Hillis designed a machine that utilised parallel computing to bring new power to AI.

• 1980s - Backpropogation algorithm allowed neural networks to start being able to learn from their mistakes.

• 1985 - Aaron, an autonomous painting robot, was shown off.

• 1997 - DeepBlue, IBM's chess machine, beat then world champion Garry Kasparov.

• 1999 - Sony launched the AIBO, one of the first artificially intelligent pet robots.

• 2002 - The Roomba, an autonomous vacuum cleaner, was introduced.

• 2011 - IBM's Watson defeated champions from TV game show Jeopardy.

• 2011 - Smartphones introduced natural language voice assistants - Siri, Google Now and Cortana.

• 2014 - Stanford and Google revealed computers that could interpret images.