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6 examples of artificial intelligence and machine learning technology you use daily

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  • Post published:May 3, 2021
  • Reading time:6 mins read

For a lot of people, the term “artificial intelligence” or “machine learning” might still seem like a page out of a science fiction novel or a scene out of a futuristic summer blockbuster starring Will Smith. Did you just picture robots and flying cars? Us too.

So does that mean artificial intelligence (AI) and machine learning (ML) technology is something we’ll only experience in the distant future? Not at all. In reality, they’ve become normal aspects of your everyday life, and have been for years. In fact, the foundations of AI started back in the 1950s.

The driving purpose of the development and evolution of AI and ML is to make everyday routines in human life smarter, faster, and better – which makes it unsurprising that many business industries are already using AI and ML technology.

A quick note: AI is the ability of computer systems to perform tasks that normally require human intelligence, and ML is a subset of AI. In other words, all machine learning is artificial intelligence, but not all artificial intelligence is machine learning.

Now, here’s a look at six different ways you’re already using AI and ML in your daily routines, whether you’ve realised it or not.

1. Web browser search

This one doesn’t surprise any of us. It’s fair to say most of us are quite trigger-happy with looking something up on a web browser; searching for answers to life’s biggest and smallest questions is after all a normal part of being human. So much so that you probably already bookmarked your usual web browser on your laptop or smartphone to be able to conduct a search faster.

Google alone reports roughly 4 billion search queries per day – that’s more than a lot! More interestingly, your search results are likely to be different from the next person. This is mostly thanks to the evolution of AI and algorithms that aim to give individuals the most helpful and relevant search results, which[DM1] [NN2]  Google breaks down in this short video. On top of that, Google Images and Google Lens famously use ML techniques to help you find related images or information.

2. Music and video streaming

Spotify, YouTube, Netflix – any streaming platform you can think of is likely powered by AI. How so? The recommended section is normally where you’ll see this at play.

These streaming platforms are sitting on a vast data set of content and user activity, much like web browsers. What you choose to play, not play, like, skip, or interact with in any way helps the platform deeply understand what your interests are, then serves you unique recommendations based on all that information.

Spotify uses advanced machine learning technology to create highly personalized content for its over 300 million active monthly listeners, as well as to help you find similar-sounding music. Netflix also uses similar technology to create tailored recommendations, but takes ML a step further by auto-generating previews and image thumbnails it thinks will most likely get you to click.

3. Social media

At the start, social media platforms were designed to show content in reverse chronological order – meaning you’ll only see what was posted around the time it was posted, and miss everything else. For a number of years now, social media platforms have switched to using an AI-based algorithm to sort and prioritise content that will uniquely matter the most to you.

Facebook uses ML to serve you relevant content (e.g. posts by friends you interact with most or events that might interest you) as well as facial recognition technology. Snapchat and Instagram popularised the use of computer vision technology to overlay filters that move with your face in real-time (think dog face filter, yeah you know the one).

The key takeaway is that AI curates your experience on social media from things like in-app behaviour and web searches. For businesses, this means that you can serve up specific content to the right people at the right time and get the most bang for your buck.

4. Navigation and commute apps

First thing you do when you need to get to someplace new? Find the best route and traffic situation on a navigation app, like Google Maps or Waze. Alternatively, you’d look in your rideshare app to see how long and how much it would take to get you there. All of this is fuelled by AI.

By using ML, Google Maps helps you predict future traffic conditions and selects the best routes to get you there safely and on time. Even Uber leverages AI and ML techniques to improve its services, most notably in enhancing location accuracy and forecasting rider demand.

5. Chatbots

You’ve encountered it before. Either from browsing a website to look for products, services or support – you’ve been greeted by a chatbot looking to help or give you more information. Once a simple piece of communication technology, chatbots have become increasingly advanced thanks to AI and ML.

While on the surface it may be hard to distinguish which type of chatbot you’re interacting with, there is a fundamental difference between a chatbot based on automation and AI. Automation chatbots can only work based on a set of predetermined rules or keywords, delivering a one-size-fits-all experience to everyone. AI chatbots are able to learn and mimic human language, meaning they can be trained to understand your query and provide answers without set responses. Drift’s AI chatbots are an example of this.

We think that’s particularly useful for businesses that get a lot of traffic on their website and may need help personalising information or support to customers.

6. Smart home systems

You’ve encountered it before. Either from browsing a website to look for products, services or support – you’ve been greeted by a chatbot looking to help or give you more information. Once a simple piece of communication technology, chatbots have become increasingly advanced thanks to AI and ML.

Not very long ago, having smart home technology would seem like an episode of the Jetsons. Still, in recent years many people have started exploring smart home technology, and that has grown rapidly since the pandemic started.

The types of smart home systems range from general management (e.g. controlling the lights or adjusting the temperature), to entertainment (e.g. “Alexa, what’s the weather like today?” or “Hey Google, play me a song by The Wiggles”), to health (e.g. monitoring the air quality in your home), to security (e.g. smart locks or threat surveillance).

Smart home systems are designed with AI and ML to continuously learn about your preferences and bring added convenience into your home, so that you can worry less about the small stuff and do more of what matters.

We can all remember our lives before AI and ML, but now we can’t imagine doing anything without them, and from what we’ve seen artificial intelligence and machine learning is here to stay. As the space continues to evolve, we’ll see it make even larger strides towards creating a more efficient and positive future for us all.

Nadia Nyaz

Nadia is a marketing and growth specialist in the tech industry, with a personal interest in organisational culture and using technology to create a more sustainable future. Since joining the Strategenics team, Nadia has focused on further developing the brand and expanding its reach to new markets.