Prof. John McCarthy coined the term Artificial Intelligence in the year 1955 and the initial thought behind it was to stimulate every aspect of learning which can be so precisely described that a machine could do it. Recently we have seen advancements being made in the field of machine learning. After six decades now, the understanding of Artificial Intelligence has become much deeper and much more complex. Now when someone mentions AI, they could mean any of the following words: machine learning, deep learning, predictive analytics, artificial neural networks, cognitive intelligence and so on.
Decoupling the brain functions
To keep things simple, we can look at artificial intelligence as simulation of brain functions and the final goal is to create a mechanical brain. And doing that means creating a left brain and a right brain. As per research over the years, it has been discovered that the left side of the brain is responsible for more analytical tasks. The thinking from our left hemisphere of the brain is sequential, linear, functional and analytical. And thinking from the right hemisphere of the brain is contextual, metaphorical, intuition led, creative and passionate.
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Historically, left-brain orientation has been considered a more successful approach to life and this is the reason our education system rewards logical approach to things. This can also be attributed to technological advancements made in the last decade which resulted in a lot of white collar jobs. Also, most of the recent AI (Artificial intelligence) advancements have been related to Machine Learning which replicates the logical and rational thinking of the brain. But in today’s context, the big fear is that with an abundance of people with left-brain thinking, readily available information and the initial advancements being made in the AI space, is leading to automation, which is eating up a lot of white collar jobs.
While machine learning is simulating the left side of the brain, let’s look at right-brain orientation. What is common between all these great founders: Henry Ford (Ford Motor Company), Bill Gates (Microsoft), Steve Jobs (Apple), Bill Hewlett (Hewlett-Packard Company), Richard Branson (Virgin Group), Ingvar Kamprad (IKEA), Ted Turner (CNN), John Chambers (Cisco)? They all have one thing in common, i.e. they are all dyslexic! This is important because dyslexics struggle with linear reasoning but transcend in big picture thinking. And going through the list, it can be inferred that this trait has made them more successful. Though historically, people with an inclination towards right-brain thinking were under-valued but now this is coming to an end. And at the moment the second most important aspect for AI sis to replicate the right side of the brain, which is termed as Cognitive Intelligence.
Though machine learning is trying to replicate the left brain functions which is making our lives a lot simpler, it is cognitive intelligence which would make astounding breakthroughs in science at lightening speed. Unlike machine learning which would replace jobs, cognitive intelligence would create opportunities which would transform the way we live. But if it is not regulated then it may even wipe out mankind i.e. as they say with technology things become limitless.
Essentially artificial intelligence is machine learning (simulating left-directed thinking) and cognitive intelligence (simulating right-directed thinking), and everything else we know about AI would fall into one of these.
Top trends to look out for in AI
If we go back 20-30 years, and pick any science fiction movie, we’d realize all that we saw in those movies is a reality now. So if you want to know what to expect next, start following sci-fi movies!
Older sci-fi movies which predicted current trends:
– Blade Runner (1982); Technology: video calls
– Back to the Future Part II (1989); Technology: wearable tech
– Total Recall (1990); Technology: driverless car
– Minority Report (2002); Technology: gesture-based user interface
– Some of them could very well have predicted what to expect next:
– Iron man – The famous Tony Stark suit’s prototype has already been created by Richard Browning and has been funded by Tesla.
– Space travel – Interstellar & The Martians
– Techno wars – Terminator franchise, Star Wars & Transformers
Top companies are now venturing into AI
– Uber – acquired Geometric Intelligence in December 2016, a startup which helps them drive their vision of moving people and things in the physical world radically faster, safer and is accessible to all.
– Google – made its machine learning platform TensorFlow readily available for everyone
– Facebook – is working on helping bling people see photos by using AI to narrate the picture via its iOS app.
– Apple – acquired Vocal-IQ in 2015 & Emotient in early 2016. Their focus is towards using AI in facial recognition, customer’s reaction to ads, and develop Siri further on speech AI.
– Spotify – acquired MightyTV in March 2017, a startup that used artificial intelligence and Tinder-like swiping controls for content recommendations
How does the AI startup industry look like
In 2016, the total funds raised by AI startups was around $5 Billion. Sectors which attracted most of these funding were Auto Tech, Ad Sales and CRM, Business Intelligence and Analytics, Health Care, Cyber Security and Robotics.
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Most Important People in Artificial Intelligence to look out for
– Andrew Ng, Baidu – As one of the creators of the Google Brain and now Chief Scientist at Baidu, the “Google of China”, Andrew shapes the AI conversation in the two largest economies in the world.
– Greg Brockman, OpenAI: While Elon Musk chairs OpenAI, Greg is its CTO and engine for discovery on a daily basis
– Ginni Rometty, IBM: Now IBM has positioned its entire future on Watson. Ginni is turning the core focus of the 105 year company on AI.
– Yann LeCun, Facebook: Yann heads up Facebook’s AI group in New York
– Jeff Dean, Google: As the creator of MapReduce, Google Brain, TensorFlow, Jeff is at the heart of some of Google’s most important projects and will continue to make waves at the company who first coined the “AI-first” strategy.