The machines haven’t taken over. Not yet at least. However, they are seeping their way into our lives, affecting how we live, work and entertain ourselves. From voice-powered personal assistants like Siri and Alexa, to more underlying and fundamental technologies such as behavioral algorithms, suggestive searches and autonomously-powered self-driving vehicles boasting powerful predictive capabilities, there are several examples and applications of artificial intellgience in use today.
However, the technology is still in its infancy. What many companies are calling A.I. today, aren’t necessarily so. As a software engineer, I can claim that any piece of software has A.I. due to an algorithm that responds based on pre-defined multi-faceted input or user behavior. That isn’t necessarily A.I.
A true artificially-intelligent system is one that can learn on its own. We’re talking about neural networks from the likes of Google’s DeepMind, which can make connections and reach meanings without relying on pre-defined behavioral algorithms. True A.I. can improve on past iterations, getting smarter and more aware, allowing it to enhance its capabilities and its knowledge.
That type of A.I., the kind that we see in wonderful stories depicted on television through the likes of HBO’s powerful and moving series, Westworld, or Alex Garland’s, Ex Machina, are still way off. We’re not talking about that. At least not yet. Today, we’re talking about the pseudo-A.I. technologies that are driving much of our voice and non-voice based interactions with the machines — the machine-learning phase of the Digital Age.
While companies like Apple, Facebook and Tesla rollout ground-breaking updates and revolutionary changes to how we interact with machine-learning technology, many of us are still clueless on just how A.I. is being used today by businesses both big and small. How much of an effect will this technology have on our future lives and what other ways will it seep into day-to-day life? When A.I. really blossoms, how much of an improvement will it have on the current iterations of this so-called technology?
A.I. And Quantum Computing
The truth is that, whether or not true A.I. is out there or is actually a threat to our existence, there’s no stopping its evolution and its rise. Humans have always fixated themselves on improving life across every spectrum, and the use of technology has become the vehicle for doing just that. And although the past 100 years have seen the most dramatic technological upheavals to life than in all of human history, the next 100 years is set to pave the way for a multi-generational leap forward.
This will be at the hands of artificial intelligence. A.I. will also become smarter, faster, more fluid and human-like thanks to the inevitable rise of quantum computing. Quantum computers will not only solve all of life’s most complex problems and mysteries regarding the environment, aging, disease, war, poverty, famine, the origins of the universe and deep-space exploration, just to name a few, it’ll soon power all of our A.I. systems, acting as the brains of these super-human machines.
However, quantum computers hold their own inherent risks. What happens after the first quantum computer goes online, making the rest of the world’s computing obsolete? How will existing architecture be protected from the threat that these quantum computers pose? Considering that the world lacks any formidable quantum resistant cryptography (QRC), how will a country like the United States or Russia protect its assets from rogue nations or bad actors that are hellbent on using quantum computers to hack the world’s most secretive and lucrative information?
In a conversation with Nigel Smart, founder of Dyadic Security and Vice President of the International Association of Cryptologic Research, a Professor of Cryptology at the University of Bristol and an ERC Advanced Grant holder, he tells me that quantum computers could still be about 5 years out. However, when the first quantum computer is built, Smart tells me that:
“…all of the world’s digital security is essentially broken. The internet will not be secure, as we rely on algorithms which are broken by quantum computers to secure our connections to web sites, download emails and everything else. Even updates to phones, and downloading applications from App stores will be broken and unreliable. Banking transactions via chip-and-PIN could [also] be rendered insecure (depending on exactly how the system is implemented in each country).”
Clearly, there’s no stopping a quantum computer led by a determined party without a solid QRC. While all of it is still what seems like a far way off, the future of this technology presents a Catch-22, able to solve the world’s problems and likely to power all the A.I. systems on earth, but also incredibly dangerous in the wrong hands.
Applications of Artificial Intelligence In Use Today
Beyond our quantum-computing conundrum, today’s so-called A.I. systems are merely advanced machine learning software with extensive behavioral algorithms that adapt themselves to our likes and dislikes. While extremely useful, these machines aren’t getting smarter in the existential sense, but they are improving their skills and usefulness based on a large dataset. These are some of the most popular examples of artificial intelligence that’s being used today.
#1 — Siri
Everyone is familiar with Apple’s personal assistant, Siri. She’s the friendly voice-activated computer that we interact with on a daily basis. She helps us find information, gives us directions, add events to our calendars, helps us send messages and so on. Siri is a pseudo-intelligent digital personal assistant. She uses machine-learning technology to get smarter and better able to predict and understand our natural-language questions and requests.
#2 — Alexa
Alexa’s rise to become the smart home’s hub, has been somewhat meteoric. When Amazon first introduced Alexa, it took much of the world by storm. However, it’s usefulness and its uncanny ability to decipher speech from anywhere in the room has made it a revolutionary product that can help us scour the web for information, shop, schedule appointments, set alarms and a million other things, but also help power our smart homes and be a conduit for those that might have limited mobility.
#3 — Tesla
If you don’t own a Tesla, you have no idea what you’re missing. This is quite possibly one of the best cars ever made. Not only for the fact that it’s received so many accolades, but because of its predictive capabilities, self-driving features and sheer technological “coolness.” Anyone that’s into technology and cars needs to own a Tesla, and these vehicles are only getting smarter and smarter thanks to their over-the-air updates.
#4 — Cogito
Originally co-founded by CEO, Joshua Feast and, Dr. Sandy Pentland, Cogito is quite possibly one of the most powerful examples of behavioral adaptation to improve the emotional intelligence of customer support representatives that exists on the market today. The company is a fusion of machine learning and behavioral science to improve the customer interaction for phone professionals. This applies to millions upon millions of voice calls that are occurring on a daily basis.
#5 — Boxever
Boxever, co-founded by CEO, Dave O’Flanagan, is a company that leans heavily on machine learning to improve the customer’s experience in the travel industry and deliver ‘micro-moments,’ or experiences that delight the customers along the way. It’s through machine learning and the usage of A.I. that the company has dominated the playing field, helping its customers to find new ways to engage their clients in their travel journeys.
#6 — John Paul
John Paul, a highly-esteemed luxury travel concierge company helmed by its astute founder, David Amsellem, is another powerful example of potent A.I. in the predictive algorithms for existing-client interactions, able to understand and know their desires and needs on an acute level. The company powers the concierge services for millions of customers through the world’s largest companies such as VISA, Orange and Air France, and was recently acquired by Accor Hotels.
#7 — Amazon.com
Amazon’s transactional A.I. is something that’s been in existence for quite some time, allowing it to make astronomical amounts of money online. With its algorithms refined more and more with each passing year, the company has gotten acutely smart at predicting just what we’re interested in purchasing based on our online behavior. While Amazon plans to ship products to us before we even know we need them, it hasn’t quite gotten there yet. But it’s most certainly on its horizons.
#8 — Netflix
Netflix provides highly accurate predictive technology based on customer’s reactions to films. It analyzes billions of records to suggest films that you might like based on your previous reactions and choices of films. This tech is getting smarter and smarter by the year as the dataset grows. However, the tech’s only drawback is that most small-labeled movies go unnoticed while big-named movies grow and balloon on the platform.
#9 — Pandora
Pandora’s A.I. is quite possibly one of the most revolutionary techs that exists out there today. They call it their musical DNA. Based on 400 musical characteristics, each song is first manually analyzed by a team of professional musicians based on this criteria, and the system has an incredible track record for recommending songs that would otherwise go unnoticed but that people inherently love.
#10 — Nest
Most everyone is familiar with Nest, the learning thermostat that was acquired by Google in January of 2014 for $3.2 billion. The Nest learning thermostat, which, by the way, can now be voice-controlled by Alexa, uses behavioral algorithms to predictively learn from your heating and cooling needs, thus anticipating and adjusting the temperature in your home or office based on your own personal needs, and also now includes a suite of other products such as the Nest cameras.