By Ximena Leyva

Toronto, Canada As well as the maple leaf, Canada is known for its sports, such as hockey, baseball, and lacrosse. What would happen to these sports if players could predict plays and get a 10-second head start?

Well, thanks to machine learning, even Cruz Azul could win a trophy. According to Eric Dong, Senior Data Scientist at IBM, this technology can be used to solve the complex problems facing society.

“One case study for IBM machine learning shows that we can help any team from any sport win with data,” said this specialist.

How does it work?

Data are analyzed from a time frame detected through animation of key moments, a soccer game in this instance. A parallel data scheme is constructed to simulate certain events in order to predict what will happen.

“Modern cameras can detect every moment of play using video provided by this technology, so these data can determine a player’s position,” explained Eric Dong.

With the help of machine learning, plays can be predicted so that a soccer team or a team from any sport can win.

In this regard, the IBM specialist says that machine learning can identify key goalscoring moments 10 seconds before they occur.

“As a company, we want to see how our data can be of use by employing Artificial Intelligence to create competitive technology in the marketplace. The data and the AI can be used in different cases,” explained Dong.

Machine learning allows models to train on datasets before being implemented, leading to an improvement in the types of associations made between data elements.

The advantage of automated learning is that it’s possible to harness algorithms and models to predict results.

Data from Cloudera, a company providing software, support, and services, show that adoption of machine learning is growing rapidly, with 47% of large companies already investing in this technology.

Hire the right staff with machine learning

In this respect, machine learning doesn’t just work for predicting plays. Companies can also use it to recruit staff.

“Based on interview transcripts, we use machine learning to help identify the best talent for jobs and the company,” said Safura Suleymanova, a data scientist at IBM, during a tour of the Machine Learning laboratory in Toronto.

This is made possible by Watson, which uses linguistic analysis to identify candidates’ personality traits, decision-making triggers, and needs based on what it knows about personality.

Machine learning transforms unstructured data into analytical metrics and applies models for filtering candidates according to their talents. This improves the team’s general skill set, eliminates hiring bias, and identifies those soft skills that are valuable to a company, such as teamwork.

IBM itself is a clear example of this hiring method.

The company’s data show that it receives at least 7,000 job applications. It uses Watson to analyze the skills, interests, and experience of thousands of candidates so that it can recommend those roles best suited to candidates, or to recommend positions that are different from those they had applied for.

“We’re seeing double-digit improvements in employee engagement and we save a hundred million dollars on human resources,” says IBM.

According to the company, 58% of large companies see data analysis as a strategic asset for their business, which is why they’re getting involved in this area.


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