Machine Learning Breakthroughs Have Sparked the AI Revolution

With innumerable data and hyperefficient artificial intelligence, this takeover is coming at lightning speed

2d ago · By Luke Lango, InvestorPlace Senior Investment Analyst

It’s October 1950. Alan Turing — the generational genius who cracked the Enigma code and helped end World War II — has just introduced a novel concept.

It’s called the “Turing Test,” and it’s aimed at answering the fundamental question: Can machines think?

The world laughs. Machines — think for themselves? Not possible.

However, the Turing Test sets in motion decades of research into the emerging field of Artificial Intelligence (AI).

This is research conducted in some of the most prestigious labs in the world by some of the smartest people in the world, collectively working to create a new class of computers and machines that can, indeed, think for themselves.

Fast forward 70 years.

AI is everywhere.

It’s in your phones. What do you think powers Siri? How does a phone recognize your face?

It’s in your applications. How does Google Maps know directions and optimal routes? How does it make real-time changes based on traffic? And how does Spotify create hyper-personalized playlists for you or Netflix recommend movies?

AI is on your computers. How does Google suggest personalized search items for you? How do websites use chatbots that seem like real humans?

As it turns out, the world shouldn’t have laughed back in 1950.

The great Alan Turing ended up creating a robust foundation upon which seven decades of groundbreaking research has compounded. Ultimately, it resulted in self-thinking computers and machines not just being a “thing” — but being everything today.

Make no mistake. This decades-in-the-making “AI Revolution” is just getting started.

That’s because AI is mostly built on what industry insiders call “machine learning” (ML) and “natural language processing” (NLP) models. And these models are informed with data.

Accordingly, the more data they have, the better the models get — and the more capable the AI becomes.

Machine Learning Breakthroughs

When I say “identity,” what do you think of?

If you’re like me, you immediately start to think of what makes you, well, you — your height, eye color; what job you have, what car you drive, what shows you like to binge-watch.

In other words, the amount of data associated with each individual identity is both endless and unique.

date cloud imposed over city; AI, machine learning

Those attributes make identity data extremely valuable.

Up until recently, though, enterprises had no idea how to extract value from this robust dataset. That’s all changing right now.

Breakthroughs in artificial intelligence and machine-learning technology are enabling companies to turn identity data into more personalized, secure and streamlined user experiences for their customers, employees and partners.

The volume and granularity of data is exploding right now, mostly because every object in the world is becoming a data-producing device.

Dumb phones have become smartphones and have started producing a ton of phone usage data.

Dumb cars have become smart cars and have started producing lots of in-car driving data.

And dumb apps have become smart apps and have started producing heaps of consumer preference data.

Dumb watches have become smartwatches and have started producing bunches of fitness and activity data.

The AI Revolution

As we’ve sprinted into the “Smart World” — where every object is a data-producing smart device — the amount of data that AI algorithms have access to has exploded at lightning speed, making them more capable than ever.

Why else has AI has started popping up everywhere in recent years? It’s because 90% of the world’s data was generated in the last two years alone.

More data, better ML and NLP models, smarter AI.

It’s that simple.

And guess what? The world isn’t going to take any steps back in terms of this “smart” pivot. No. We love our smartphones and smart cars and smartwatches far too much.

Instead, society is going to accelerate in this transition. Globally, the world produces about 2.5 exabytes of data per day. By 2025, that number is expected to rise to 463 exabytes.

A New Era of Machine Learning

Let’s go back to our process.

More data, better ML and NLP models, smarter AI.

Thus, as the volume of data produced daily soars more than 185X over the next five years, ML and NLP models will get 185X better (more or less), and AI machines will get 185X smarter (more or less).

Folks, the AI Revolution is just getting started.

As my friends in the machine learning and robotics fields like to remind me, most things a human does, a machine will be able to do betterfaster and cheaper — if not now, then soon.

I’m inclined to believe them, given the advancements AI has made over the past few years with the help of data — and the exponential amount of it yet to come over the next few years.

Eventually — and inevitably — the world will be run by hyperefficient and hyperintelligent AI.

I’m not alone in thinking this. Gartner predicts that 69% of routine office work will be fully automated by 2024, while the World Economic Forum has said that robots will handle 52% of current work tasks by 2025.

The AI Revolution is coming — and it’s going to be the biggest revolution you’ve seen in your lifetime.

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