What Does Today’s Artificial Intelligence Look Like?

Humans have evolved in astounding ways in the last 100 years, and it’s impossible to fathom what will happen in the next 100. If we’re only in the beginning stages now, it’s exciting to think about what we could see in the next five to ten years.

But, before we put the cart in front of the horse, let’s talk about what’s happening today. While we imagine all kinds of crazy scenarios involving knowledge and unlocking the secrets of mankind, it’s best to talk about right now.

Here’s a glimpse at AI as it stands today.

AI Adapts To Our Likes

Today’s AI is data-driven which relies on extensive behavioral algorithms that adapt to what we like. For instance, when you “like” something on Facebook, the platform learns your preferences. Once it has an idea of what kind of posts, music, and movies you like, Facebook will begin to suggest content.

This method of likes and dislikes is the basis of our digital world now. You don’t have to look far for this because you interact with companies that employ these methods every day, if not every hour.

Here’s a few of the companies using smart technologies to adapt to your likes:

Amazon

Ever wonder how Amazon got so smart? Collecting massive quantities of data and making investments into Amazon’s AI algorithms are refined yearly. And, the more fine-tuned they get, the better they are at predicting what we’re interested in buying. Amazon keeps track of what you buy and suggests new items that you’ll like based on the predictive analysis of your purchases.

Alexa

Within a very short amount of time, Amazon’s Alexa has become central to many households. Alexa’s capabilities can do everything from play your favorite song, order takeout, or make a note to call the babysitter. ScaleFactor’s Marge (our own AI host) works with Alexa, too. With Alexa, people can schedule appointments, pay their bills, and order a carton of milk — all by the sound of their voice.

Netflix

Like Amazon, Netflix pays attention to your activity on their site. The platform looks at what you select, how long you binge watch a show, or if you stop watching something halfway through. The backbone of Netflix is its powerful predictive technology, which analyzes data to suggest movies and television shows you might like.

Tesla

Everyone knows that Tesla is probably the most modern vehicle on the market right now. While its electric mileage and sleek interior get a lot of attention, Tesla’s internal systems are just as incredible. Not only can a Tesla crowdsource traffic data, it can also keep a log of how you drive and even where your hands are placed. Basically, the car learns your habits and preferences.

It only makes sense that Tesla founder Elon Musk is the co-founder of OpenAI, an organization dedicated to the safe and manageable development of artificial intelligence.

Spotify

With its 100M users, Spotify is the king of streaming music. One of Spotify’s biggest strengths working with user data is that it can curate playlists for every user, every day. This service makes users feel like a friend dropped off mixtapes with new music to check out. Spotify tailors selections based on region and numbers of time an artist gets played. Every year, Spotify offers a year in review for all users, letting them know who they listened to the most and what their favorite genres of music were for the year.

Inspired by Spotify, ScaleFactor also did a 2018 Year in Review report for each of our customers, recapping their business’ financials.

Apple

Apple has sold over one billion iPhones, each of them equipped with Siri, your personal assistant. Siri uses machine-learning and gets smarter with every query and interaction. She learns what we’re trying to say and request, and does her best to match it.  

Nest

Owned by Google, Nest is a continually learning thermostat. Nest uses behavioral algorithms to learn from your heating and cooling habits. The system can anticipate your needs and also be controlled by a few swipes on your phone.

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AI and the World of Marketing

Artificial intelligence is also changing how marketing teams do things. With predictive analytics understanding outcomes before the humans do, machine learning has turned the marketing industry on its head. Much like how social media changed the landscape of what small businesses could do, AI will do the same for marketing teams.

The essential building blocks for effective marketing all rest upon one cornerstone: convert browsers into buyers who’ll love your product or service. Personalization is key here, which is better achieved with AI and machine learning.

Machine learning focuses on the specifics of data to revolutionize the consumer experience. Looking at trends and purchase patterns, machine learning can help companies identify what customers want before the customers themselves know what they want.

AI Creates Structure for Marketing Teams

Because machine learning can find out quickly what works and what doesn’t, marketing teams can work smarter and stop guessing how consumers will react. With in-depth analysis powered by machine learning, marketers can better monitor their downloads, site visitors, and page clicks on their site and social media platforms. Furthermore, they can better see what’s resonating with a specific target audience.

Real Time Is Actually Right Now

When something is doing well, machine learning can capitalize on it in real-time. The system is smart; It can suggest changes based on performance data. Marketers can look at how users are responding and tweak a word or change a photo to see if that works better. This is also known as A/B testing

Speaking of real time, ever notice when you browse for a pair of pants and those pants seemingly follow you everywhere on the Internet? That’s the power of AI — it enables “retargeted ads.”

Retargeting is cookie-based, meaning it uses a Javascript code to follow users wherever they go, reminding them about that pesky pair of slacks. Companies do this by placing a small piece of code on their site which is referred to as a pixel. The pixel is unnoticeable by visitors, but every time someone new stops by the site, the pixel drops a cookie into that customer’s browser. Later, when the customer is browsing the web, the cookie works with a retarget provider (a banner on a site) to remind that customer about whatever it was they were scanning for earlier.

Retargeting works because it focuses your advertising on people who already know your brand and have demonstrated interest.

AI Is Cost-Effective & Data-Driven

Machine learning reduces marketing costs because it drastically cuts communication costs. Instead of face-to-face, most times, customers can be kept updated via email, social media, or via other content.

When companies use AI to take a hard look at what their customers love, it enables the company to make decisions backed by data, not just intuition. Instead of adding features no one asked for, a company can see what people love about them and do more of that.This allows for companies to invest in the customer, not just the product.

What’s Next for Artificial Intelligence and Machine Learning?

Artificial intelligence will drastically benefit businesses both big and small. Both big and small businesses are exploring ways to introduce AI to their business and customers, making the playing field for artificial intelligence wide open. Who knows what’s next? In the next few years, we’ll most likely see radical developments that challenge what we know and streamline what we do. 

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