The Artificial Intelligence (A.I.) Adventure
The Artificial Intelligence (A.I.) Adventure
Exactly who were the creators of Artificial Intelligence (A.I.) & where are they today?
The component of AI that digs deep into the training of computers regarding methods to learn, is called "deep learning". This is where a computer is taught to recognize variations in patterns within data, these large data sets are known as "big data". Even though this may seem very futuristic it has become a regular part of life for businesses such as Microsoft, Google, and Facebook. These large companies are finding themselves caught up in a high priced race against time, as although many within the deep learning environment are budding new data scientists who want to get their foot in the door. There just does not seem to be very many competent people available, and those that are qualified can go where they want. The question is however.....
Just where did it all start?
The deep learning conspiracy
Four computer scientists, Geoffrey Hinton, Yann LeCun Yoshua Bengio and Tomi Poutanen appear to jump out as the original pioneers of A.I.
Three of them worked at their own laboratories and at a research institute in Toronto called CIFAR, bashing out the mathematics and coding for the basis of what we know A.I to be today.
They apparently jokingly called themselves the "deep learning conspiracy". For decades these three men toiled away relentlessly as A.I. and deep learning fell in to the A.I. winter. The A.I. winter was the period in time where expectations and the reality of what was actually attainable clashed. The researches did not have the computing power or the data to completely explore its potential, so the funds dried up. It seems like their commitment to deep learning and Artificial Intelligence appears to have been vindicated. As Hinton was engaged in 2013 to work as a senior researcher at Google, assigned to expand their deep learning division. Facebook appointed LeCun and IBM recruited Bengio to work with the now well known IBM Watson project.
From left to right, Geoffrey Hinton, Yann LeCun Yoshua Bengio and Tomi Poutanen.
The fruits of their labour are without a doubt starting to show up in front of the general public, with deep learning appearing all over the place. Google uses it to improve its search experience and is clearly engaged in a massive way with Deep Mind, Google's Deep Mind program a short while ago defeated a human world champion in the board game "Go", which is well-known as being one of the most challenging board games ever produced. Amazon Alexa is also now showing up in households and just about every person knows Apples' s Siri and Microsoft's Cortana.
Even the students of the three principal scientists are profiting too, with many of individuals who were not recruited by the big players being snapped up as part of the acquisition cycles of the likes of Google and Facebook. Twitter also absorbed many past graduates of the three amigos, because of its recent A.I. purchases
This huge explosion of awareness in deep learning is similar to when "big data" was instantly popular. In many ways, this is its next technology as A.I. is dependant on large quantities of data which is essential for deep learning. Conversations with A.I. experts claim that deep learning could possibly before long become the backbone of the majority of technically based products that we use on a daily basis.
Nearly half of the A.I. corporations picked up since 2011 have had Venture Capital assistance.
Almost 140 private companies trying to advance artificial intelligence technology appear to have been acquired since 2011, with well over 40 acquisitions occurring in 2016 alone (as of 10/7/2016). Corporate giants like Google, IBM, Yahoo, Intel, Apple and Salesforce, are competing in the race to acquire private A.I. corporations, with Samsung appearing to be a new entrant with its acquisition of start-up Viv Labs, which is creating a Siri-like A.I. assistant.
Google is still one of the most notable global players, with 11 transactions in the A.I. classification under its belt.
In 2013, the corporate giant picked up deep learning and neural network startup DNNresearch from the computer science department at the University of Toronto. This purchase supposedly assisted Google in making essential enhancements to its image search feature. In 2014 Google picked up British company DeepMind Technologies for some $600M . This year, it acquired visual search startup Moodstock, and bot platform Api.ai.
Apple and intel are tied for second place. intel acquired 3 start-ups this season alone: Itseez For Machine Vision Smarts, Nervana Systems, and Movidius, while Apple bought Turi and Tuplejump recently.
Twitter ranks third, with 4 significant acquisitions, the most recent being image-processing start up Magic Pony.
A.I. companies that have been purchased over the last few years.
|Dark Blue Labs||2014||DeepMind|
|Granata Decision Systems||2015|
So where are they now? The Canadian Link
It seems that all the originators of the AI explosion are in some way connected with Canada. As well as their day jobs working at Google or Facebook ect another good place to start looking is The Vector Institute. Launched in March 2017 with generous help from the Government of Canada, Government of Ontario, the University of Toronto and private organizations, Vector symbolizes an unprecedented answer to an unmatched opportunity. That is the transformative possibility of AI in fields as numerous as finance, education, environment and clean tech, retail, advanced manufacturing, transportation and health care.
Their web page states "The Vector Institute will propel Canada to the forefront of the global shift to artificial intelligence ("AI") by promoting and maintaining Canadian excellence in deep learning and machine learning more broadly, and by actively seeking ways to enable and sustain AI-based economic growth in Canada."
Chief Scientific Advisor Geoffrey Hinton provides overall vision, guidance and inspiration. Research Director Richard Zemel plays a key leadership role as we establish and build our organization. Interim Industry Services Development Director Tomi Poutanen will focus on business relationships.
Some Interesting Canadian Based AI News
Who or what is the new A.I. iStein?
iStein Neural Networks seems to be the newest kid on the block. Claiming to be able to put over 100 billion neurons in a single 4 inch high server case. Although the name sounds very "Apple" it looks like this is a new startup that is still running in stealth mode. An excerpt from one of their papers states...
"The maximum amount of usable neurons we have simulated on a standard laptop is around 3.2 billion. The server based prototype test system will accept a maximum of 128 Billion neurons. That is the equivalent of a Human + 2 Baboon brains. To give context, IBM Watson simulates 500 billion neurons using 2800 cores across 750 physical servers."
They also state "If we were to multiply our system out to the size of Watson we could simulate a maximum of 128 quadrillion neurons. However, the number of neurons is less important than the number of synapses (the connections between each neurons). In a standard 2-dimensional neural network, each neuron has access to 8 other neurons. Our optimised neural networks are able to create synapses between all neurons within the network. This vastly increases the speed and accuracy of learned data."
A video from the Godfather of A.I. Regarding CNNs and what wrong with them
Article Written By Restore Solutions : April 19th, 2017.