Big companies have been engaged in an arms race for years when it comes to harnessing the power of machine learning (ML) to remain relevant and competitive. And most of these companies use the technology behind their customers’ backs for obvious reasons. (Check out the link to find out more on what is machine learning.)
Here are the top businesses that now actively use ML in their operations and will rarely go public about it. The purposes are various, from sharpening their business analytics and improving their services to boosting security and expanding their share of the market pie.
Spotify, the world’s largest on-demand audio streaming service, has recently bought several data analytics startups to help bolster their Ai- and ML-powered projects. The largest experiment Spotify has so far conducted with tremendous success is the so-called Discover Weekly playlist.
Through Discover Weekly, on Mondays, millions of Spotify users get access to a mixtape of 30 new tracks based on their search history, taste, and third-party data. The recommendations are generated through machine learning and rarely miss the target. Discover Weekly has proven a huge success, as it has enabled users to learn about artists they have never heard of before while giving lesser-known artists much-needed exposure.
Amazon has been using AI for years to better understand customer behavior, but in recent years machine learning and automation have reached new heights at the Seattle-based online retail giant. Machine learning-backed product recommendations account for at least 35% of the retailer’s global sales.
Amazon reportedly uses ML to better understand how its customers think and why they are interested in a specific product. If the company manages to understand the context of a transaction, it is able to recommend related products and services that customers will likely purchase as well.
Machine learning has also enabled Amazon to make “sustainable packaging decisions” that helped trim the global amount of outbound packaging by 33% since 2015, without harming customer experience.
Tesla has taken the world by storm with its cutting-edge electric vehicles, batteries, and autonomous cars. Tesla founder Elon Musk unveiled that the tech company is working on a proprietary AI to (probably) help enhance Tesla cars’ autonomous driving capabilities through the controversial Autopilot software. No other details are known about the new AI, but Musk warned that it could leave countless people without jobs and even spark WW3.
Tesla harvests immense amounts of data on their users and cars, such as traffic speed, weather and road conditions, the health of car components, and even driver’s hand placement and decision making in the car. The data is beamed into the company’s cloud, where AI, through machine learning algorithms, processes the data and beams new instructions to the entire fleet of Tesla cars (through software patches) and helps improve each individual car’s Autopilot system. The end goal is to create a fully autonomous electric car, which has been Musk’s dream all along.
The explosive transformation of a modest San Francisco-based startup into the world’s largest accommodation provider over the span of just 14 years is also due to AI and machine learning. Airbnb is reportedly using ML to tell trustworthy guests from untrustworthy guests before they even manage to make a reservation.
What is more, the company’s Engineering & Data Science team has developed AI-powered chatbots that can answer guests’ questions when hosts are not online by analyzing user intent with surprising accuracy. For instance, smart bots can display nearby tourist attractions if a guest asks the host for recommendations. They can also help guests make and cancel reservations with zero human input.
Pinterest has grown into 250 million plus monthly users and more than 170 billion pinned items, so curating the content is nearly impossible to an army of people alone. But with the help of ML, the social media service has managed to become a success by analyzing trends, understanding user behavior, and recommending relevant pins and pinboards users had no idea existed.
The service’s prediction capability becomes more accurate the more people pin. Pinterest’s ML algorithms are so advanced that the service has been able to predict the likelihood of an interaction with a certain pin by a specific user since 2015. This tech is the reason the pins with the greatest relevance for a user are mysteriously placed at the top of the user’s home screen ever since.