You may have heard that today's tech companies are using machine learning to identify and filter email spam (Google), blacklist and penalize spam blogs so that users get good search results (also Google), recommend products specifically for you (Amazon), and fight fraud (IBM).
Today's post isn't about that. It's about the new, perhaps surprising ways that companies (and non-profits) are using machine learning to make smarter, faster, better products.
- Seal Mobile ID is trying to recognize the user of a mobile device based on accelerometer data (how he holds and moves the phone).
- The Online Privacy Foundation sponsored a competition to see if it's possible to predict whether someone is a psychopath based on his twitter usage. (According to the leaderboard, you kind of can.)
- Fast Iron wants to predict the auction sale price of a piece of heavy equipment — essentially create a Blue Book for bulldozers.
- Similarly, Carvana is building a model to determine if a car bought at auction is a lemon.
- Marinexplore and Cornell University are trying to identify whales in the ocean based on audio recordings so that ships can avoid hitting them.
- Dunnhumby and hack/reduce are trying to predict in advance whether a product launch will be successful or not.
- Oregon State University is looking to determine which bird species is/are on a given audio recording collected in field conditions.
- Amazon is looking for a model to "predict an employee's access needs, given his/her job role." If new employees are starting with inadequate permissions, then it is a costly time suck for them to submit access request paperwork, get supervisor approval, and get granted access by IT. If Amazon is able to create a smarter permissions system with a machine learning model, they can save quite a bit of time and money.
- Benchmark Solutions is trying to predict the trade price of U.S. corporate bonds.
- StackOverflow wants a model that will predict which new questions will be closed.
Machine learning algorithms are being used in lots of novel and interesting ways. It's becoming increasingly important for companies to harness the power of their data and use it to make smart decisions.