Uses: Machine Learning!
Companies Using Machine Learning in Cool Ways
Artificial intelligence and machine learning are among the most significant technological developments in recent history. Few fields promise to “disrupt” (to borrow a favored term) life as we know it quite like machine learning, but many of the applications of machine learning technology go unseen.
Want to see some real examples of machine learning in action? Here are companies that are using the power of machine learning in new and exciting ways.
- Yelp – Image Curation at Scale
Few things compare to trying out a new restaurant then going online to complain about it afterwards. This is among the many reasons why Yelp is so popular (and useful).
Yelp turned to machine learning a couple of years ago when it first implemented its picture classification technology. Yelp’s machine learning algorithms help the company’s human staff to compile, categorize, and label images more efficiently – no small feat when you’re dealing with tens of millions of photos.
- Pinterest – Improved Content Discovery
Whether you’re a hardcore pinner or have never used the site before, Pinterest occupies a curious place in the social media ecosystem. Since Pinterest’s primary function is to curate existing content, it makes sense that investing in technologies that can make this process more effective would be a priority – and that’s definitely the case at Pinterest.
In 2015, Pinterest acquired Kosei, a machine learning company that specialized in the commercial applications of machine learning tech (specifically, content discovery and recommendation algorithms).
- Facebook – Chatbot Army
Although Facebook’s Messenger service is still a little…contentious (people have very strong feelings about messaging apps, it seems), it’s one of the most exciting aspects of the world’s largest social media platform. That’s because Messenger has become something of an experimental testing laboratory for chatbots.
- Twitter – Curated Timelines
Twitter has been at the center of numerous controversies of late (not least of which were the much-derided decisions to round out everyone’s avatars and changes to the way people are tagged in @ replies), but one of the more contentious changes we’ve seen on Twitter was the move toward an algorithmic feed.
- Google – Neural Networks and ‘Machines That Dream’
These days, it’s probably easier to list areas of scientific R&D that Google – or, rather, parent company Alphabet – isn’t working on, rather than trying to summarize Google’s technological ambition.
Needless to say, Google has been very busy in recent years, having diversified into such fields as anti-aging technology, medical devices, and – perhaps most exciting for tech nerds – neural networks.
- Edgecase – Improving Ecommerce Conversion Rates
For years, retailers have struggled to overcome the mighty disconnect between shopping in stores and shopping online. For all the talk of how online retail will be the death-knell of traditional shopping, many ecommerce sites still suck.
Machine learning examples Edgecase
Edgecase hopes its machine learning technology can help ecommerce retailers improve the experience for users. In addition to streamlining the ecommerce experience in order to improve conversion rates, Edgecase plans to leverage its tech to provide a better experience for shoppers who may only have a vague idea of what they’re looking for, by analyzing certain behaviors and actions that signify commercial intent – an attempt to make casual browsing online more rewarding and closer to the traditional retail experience.
- Baidu – The Future of Voice Search
Google isn’t the only search giant that’s branching out into machine learning. Chinese search engine Baidu is also investing heavily in the applications of AI.
- HubSpot – Smarter Sales
Anyone who is familiar with HubSpot probably already knows that the company has long been an early adopter of emerging technologies, and the company proved this again earlier this month when it announced the acquisition of machine learning firm Kemvi.
- IBM – Better Healthcare
The inclusion of IBM might seem a little strange, given that IBM is one of the largest and oldest of the legacy technology companies, but IBM has managed to transition from older business models to newer revenue streams remarkably well. None of IBM’s products demonstrate this better than its renowned AI, Watson.
An example of how IBM’s Watson can be used to test and validate self-learning behavioral models
Watson may be a Jeopardy! champion, but it boasts a considerably more impressive track record than besting human contestants in televised game shows. Watson has been deployed in several hospitals and medical centers in recent years, where it demonstrated its aptitude for making highly accurate recommendations in the treatment of certain types of cancers.
Watson also shows significant potential in the retail sector, where it could be used as an assistant to help shoppers, as well as the hospitality industry. As such, IBM is now offering its Watson machine learning technology on a license basis – one of the first examples of an AI application being packaged in such a manner.
- Salesforce – Intelligent CRMs
Salesforce is a titan of the tech world, with strong market share in the customer relationship management (CRM) space and the resources to match. Lead prediction and scoring are among the greatest challenges for even the savviest digital marketer, which is why Salesforce is betting big on its proprietary Einstein machine learning technology.
The Future of Machine Learning
One of the main problems with rapid technological advancement is that, for whatever reason, we end up taking these leaps for granted. Some of the applications of machine learning listed above would have been almost unthinkable as recently as a decade ago, and yet the pace at which scientists and researchers are advancing is nothing short of amazing.
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