The amounts of information that companies have to process now are growing daily. It is simply impossible to understand it and use it for the sake of corporate success without the right automation tools. Machine learning is the technology that helps businesses to optimize and automate their processes, study hidden patterns in their data.
In this post, we are going to discuss the example of top international companies that already use ML to achieve their goals. If you’re interested to learn more about the technologies behind those solutions, check out the curated list of the most popular machine learning tools at this website.
Use cases of machine learning
Without knowing it, you benefit from machine learning technologies every day. Instagram, Twitter, Netflix, and other applications that you use and love actively apply ML to satisfy your needs. Now let us have a look at how they do that.
One of the most popular social media networks in the world uses machine learning to offer you interesting materials based on your historical data. The feed on Instagram changes constantly organizing posts in a hierarchical order.
Moreover, the company uses artificial intelligence and machine learning to fight bots and fake profiles online. ML systems block suspicious behavior.
Recently, Instagram launched two new features that can facilitate the use of the application: automatic generation of text descriptions for photos that use object recognition technology and the possibility to add alternative descriptions to photos.
Instagram will use the technology developed by Facebook AI Research to recognize objects and create descriptions for photos. A description containing a list of objects in the image will be available in the audio format as well.
The second function will allow users to independently add a detailed alternative description when uploading a photo. It will not be available under the photograph, as usual. Visually impaired Instagram users will hear alternate text using the screen reader mode.
Evernote is a widely used tool for creating notes and sharing content with others. It has an attractive interface and many features that bring value to the users.
Evernote Corporation also has a possibility to create and store notes with artificial intelligence capabilities.
The tasks of AI here are to improve search functions and perform popular tasks of users: for example, artificial intelligence scans the content of notes and reminds you that you need to complete the task.
Since in this case, universal algorithms would not be able to demonstrate correct operation, the developers used an AI that adapts to a specific user.
Spaces features are available only for corporate users. However, in the future, the company plans to add new features to the application in personal accounts.
On Mondays, the Spotify music service provides each user with their individual playlist.
The Discover Weekly recommendation system was introduced in 2015. It uses collaborative filtering, natural language processing algorithms and analyzes the music in order to match you with the perfect songs.
Spotify has become the world’s most popular music streaming service thanks to just such a powerful recommendation system. No matter how rarely you listen to music and no matter how peculiar it is, the algorithms will advise you something similar.
Many companies tried to reproduce their algorithms, for example, Apple, but they haven’t succeeded. If you want to please your ears and check the powerful capabilities of ML for yourself, check out Spotify. Here you can learn more about machine learning algorithms that make it so great.
LinkedIn launched an AI assistant that helps job seekers to create a resume: the assistant selects similar profiles in the right field and gives advice. It also suggests using various terms to make the document more informative and interesting for employers.
In addition, LinkedIn uses a combination of machine learning algorithms with the work of a human operator. This allows you to classify content by quality. ML evaluates content in two stages:
online LinkedIn classifiers mark each image and text with spam, low quality, or good quality tags in real-time;
LinkedIn classifiers that run as you read the content determine the likelihood of user engagement and the quality of the post.
All in all, LinkedIn uses AI to improve the user experience and help its users to find a job of their dreams. To provide employment consultation to millions of users would be impossible without the use of machine learning.
Salesforce.com is an American developer of the CRM system, which is provided to customers as a SaaS.
In 2017, the company launched an integration with Einstein AI and added new features to the system. Einstein is an AI-based assistant for analyzing CRM data. Its main function is to help companies identify, predict, recommend, and automate the most effective business processes. The AI assistant uses Data Mining and MO to predict the company’s future sales performance.
Also, Salesforce.com bought the startup MetaMind, specializing in machine learning and natural language processing. An algorithm developed on the basis of neural networks analyzes the English text and makes a short squeeze out of it using new words and phrases. According to journalists from the MIT Technology Review, the Salesforce algorithm produces “surprisingly cohesive and accurate” notes: The New York Times’s 345-word news story was transformed into three 50-word sentences.
The Salesforce research team paid great attention to developing a language system. They decided that a good way to get an accurate algorithm is to teach it to speak a modern language first. Then, they were planning to teach the algorithm to perform target tasks. This method allowed to obtain great results (only works for English and German). However, the creators are planning to add more languages in the future. This system can be used for translation, customer service, and any other service where accurate language recognition is important.
Nowadays, the world is increasingly controlled by digital technology. Big data, artificial intelligence, machine learning are only a small part of the daily changes in lifestyle and business. Investing in these technologies you invest in your future.