Industries are adopting artificial intelligence and machine learning on a large scale. Tech companies both big and small are working on artificial intelligence projects that will shape the future of industries such as healthcare, banking, business, education, and other sectors.
We are not at the point where everything it’s automated and run by machines, but we’re getting there. These technologies are all around us, running silently in the background and keeping operations running. AI is quietly reshaping our society, affecting the way we do things, the way we vote, the way we buy goods, and the decisions we make.
You’ve probably interacted with an AI-powered system at some point, but you didn’t know it. In a recent study, 37% of respondents said they had used an AI tool. Of those who said no, 63% had used it – they just weren’t aware of it. As technology becomes more sophisticated, this will become more prevalent.
While some AI projects, like Google Brain and Microsoft’s Cortana, are well known, there are a large number of startups working on AI in the arts. If you thought AI was taking jobs away from companies, now say hello to AI artists and musicians.
In fact, AI is even helping to decipher strange signals in the universe! here are some revolutionary artificial intelligence projects that transforming the world around us.
10 Tesla
Before we know it, self-driving and autonomous vehicles will be on our roads. Almost every company, from Google to automakers like Ford and GM, is working on self-driving technology.
The standout, at least now, is Tesla, thanks to its AutoPilot feature. You could even say that Tesla’s vehicles are some of the best ever made. One of the reasons for this sentiment is the AI and the predictability of its self-driving system. While other vendors are working hard to put this technology on the road, Tesla has already achieved the unthinkable: It’s out there, in the hands of consumers, right now.
Every day, Tesla vehicles and the AI system are getting smarter, thanks to a wealth of user and performance data and over-the-air updates.
9 Alexa
You didn’t think we were going to make a list like this without mentioning Amazon Alexa at least once, did you? Sure, it’s a voice assistant like any other when you break it down to the basics, but what Amazon is doing with the platform really makes it stand out.
Amazon calls the structure of the Alexa AI platform “conversational AI,” which allows the assistant to react and respond to queries more naturally. Of course, it seems like almost every tech company is trying to offer a more human assistant than ever before, so that’s nothing unheard of.
Alexa is worth talking about because of how open the platform is, at least to savvy developers and other brands. Thanks to a solid API and incredible support for “Alexa skills” – a kind of plug-in channel that allows you to add new apps to Alexa devices – the platform grows daily, even beyond what the official engineering team does from Amazon.
8 Netflix
Even a few years ago, it would have been unheard of to think of an entertainment company like Netflix getting into the AI game. However, the company’s efforts have helped foster one of the most complex and advanced machine learning tools on the modern market.
Netflix uses alarmingly accurate predictive measures to analyze and deliver more relevant content to viewers. It does this by analyzing past behavior and viewed content, as well as customer reactions to movies and shows. Every time you tap that little “thumbs up” after watching something on Netflix, the AI records the interaction.
As more clients use the platform and user profiles and data sets grow, the system becomes smarter and more accurate. That’s the idea behind machine learning and cognitive AI systems: They’re designed to get smarter and more adept over time as they ingest larger stores of data. The bottom line is that Netflix is leveraging technology in some very inspiring ways.
7 Microsoft’s Cortana
As you well know, Microsoft’s Cortana was born out of a need to compete with the likes of Google Assistant, Siri, and Alexa. It is a voice assistant that comes with almost all modern Microsoft products. But the name is also a nickname for the company’s large-scale AI engine.
Since its inception, Microsoft developers have been striving to optimize and improve the platform in various ways. One of the most promising arises from Microsoft’s acquisition of Semantic Machines, a relatively recent AI company. The idea is to help establish a more accurate and intelligent assistant – like Cortana – that can respond naturally to humans. Semantic Machines will drive this concept forward because its platforms rely on machine learning to help inform bots and drive customer interactions.
6 Google Brain
Formed back in 2010, Google Brain is a deep learning and AI research team at the major tech firm. Like most of Google’s teams, they have a lot of freedom, which means they can adhere to whatever agenda they like. This flexibility results in some incredibly unique artificial intelligence projects.
Of course, it’s also the main engine that Google uses for most of its products, including Google Assistant, Google’s answer to Alexa, and Siri.
One of the latest Google Brain products or developments is Smart Reply, a quick messaging tool built into Gmail that helps automate common responses. It also works with text messaging apps through the Android mobile operating system.
5 AlphaGo
AlphaGo, believe it or not, is a branch of Google’s DeepMind, another AI and machine learning project from the technology company. More specifically, it is a computer program designed to play the board game Go. There are several variants such as AlphaGo Zero, AlphaGo Master, AlphaGo Lee, and others.
In 2015, AlphaGo became one of the first computer programs in history to beat a human professional without any handicaps. The game also took place on a full-sized 19” x 19” board — which is, if you didn’t know, unprecedented. The AI and its algorithms had to account for more board space than previous versions, which involved more moves and player outcomes.
It’s notable because it shows how AI systems can compete with human efforts on a more equal footing. It is proof that AI will one day serve as a substitute for – or augmentation – human cognitive abilities.
4 Yelp
Like many of the companies on this list, Yelp is leveraging machine learning and AI to improve the experience for its user base. However, Yelp’s difference lies in the specific use of AI to better classify and categorize uploaded images.
For a computer, it is difficult to analyze an image and discern if it is inside a store or outside. But knowing this, and displaying the right images, is essential for online review platforms like Yelp. So they’ve used machine learning to automate this process and provide much more actionable reviews.
3 Pandora
Similar a Netflix, Pandora takes advantage of AI to deliver a more relevant experience to its audience – they even refer to the platform as their music DNA.
Through a wide variety of features and characteristics, each track or piece of music on the platform is analyzed, first by a group of professional musicians and audiophiles. It then receives custom tags, which help the AI provide more specific recommendations.
2 Edge case
Previously called Metrics Comparison, Edge case is an e-commerce tool designed to help improve conversion rates through the power of machine learning. The goal is to deliver a more relevant experience to customers online by using behavioral data and insights. Think of it as analogous to window shopping, only through online retailers. The platform helps people find results, even when they don’t know exactly what they want.
Honestly, who wouldn’t want casual browsing to be more rewarding and accurate?
1 IBM Watson
IBM Watson is a machine learning and cognitive AI platform used for an almost infinite number of projects. If we had to list everything it’s capable of, we’d be here all day. It is having a profound impact on banking and finance, online therapy and mental health, retail, marketing, and even customer service.
One of the most innovative uses is in the sports industry. The Toronto Raptors are utilizando la plataforma para analizar y redactar potential players based on existing skill gaps. Examine the skills, talents, personality traits, and character of current players, and use this information to evaluate potential signings.
The system then helps the team select the ideal players during scouting sessions. Recruiters enter the necessary data into the system during their observations. The system then makes predictive suggestions about which players the team should pursue.
