Think you’re good at chess, Jeopardy!, or Go? Champions in each of these games thought so until defeated by computers running machine learning (ML) and artificial intelligence (AI). 

Google’s AI company DeepMind defeated Go world champion Se-do in 2016 with its AlphaGo AI system. IBM’s Watson trounced the long winning streak of Jeopardy! champ Ken Jennings in 2011. Fortunately for Jennings it didn’t hurt his career — Jeopardy named him a guest co-host of the show in September and this month officially extended it for the remainder of the season. IBM also made history in 1997 with its Deep Blue, which beat world chess champion Garry Kasparov.

Applications for machine learning extend far beyond games. In fact, IBM used Watson to tackle other projects: assisting in the treatment of lung cancer patients at New York’s Memorial Sloan-Kettering Cancer Center; conversing with kids via smart toys; teaming up with education company Pearson to tutor college students; even helping H&R Block customers file their taxes.

Overview of IBM Watson Studio | IBM Data and AI

Machine learning touches on a number of industries and an expansive list of applications. Below you can get a taste of how it’s used.

Machine Learning Examples

  • Ranking posts on social media
  • Searching for the best answers to questions
  • Enabling business intelligence
  • Creating smart recommendation engines
  • Patient sickness predictions
  • Sorting, tagging, categorizing photos
  • Determining credit worthiness
  • Targeting emails
  • Customer lifetime value assessments
  • Improving herbicide techniques for farming

 Dawn Kawamoto contributed reporting to this story.

 

What Exactly Is Machine Learning?

Machine learning is a subset of the broader concept of artificial intelligence. 

Under AI, intelligent machines simulate human thinking capabilities and behaviors. AI basically makes it possible for computers to learn from experiences and perform human-like tasks.

Machine learning, however, is the part of AI that allows machines to learn from the hoards of data it receives without explicitly being programmed. ML, for example, can make predictions using statistical algorithms and perform tasks beyond what it was explicitly programmed for. 

“It’s just a tool, but it’s a really important tool.”

“It’s not magic,” Greg Corrado, a senior research scientist at Google, has said of machine learning. “It’s just a tool, but it’s a really important tool.”

And this tool is responsible for many recent advancements in the field of computer science. We’ve seen machine learning used to make image recognition and text translation possible. 

Other applications include email spam and malware filtering, traffic predictions, medical diagnosis and virtual personal assistants. 

“We are using machine learning and AI to build intelligent conversational chatbots and voice skills.” Mitul Tiwari, co-founder of PassageAI, told Forbes. “These AI-driven conversational interfaces are answering questions from frequently asked questions and answers, helping users with concierge services in hotels, and to provide information about products for shopping. Advancements in deep neural networks or deep learning are making many of these AI and ML applications possible.”

 

How Companies Are Using Machine Learning

Many industries stand to benefit from machine learning and we’re already seeing the results. Here are 16 machine learning examples from companies across a wide spectrum of industries, all applying ML to the creation of innovative products and services.

 

Machine Learning applications Capital One
Image: Shutterstock

Detecting Online Fraud 

How it’s using machine learning: Financial institution Capital One uses machine learning to detect, diagnose and remediate anomalous app behavior in real time. It also uses the technology as part of its anti-money laundering tactics to adapt quickly to changes in criminals’ behaviors.

 

quora machine learning examples
Quora

 

Matching Answers to Queries

How it’s using machine learning: Quora, a social media question and answer website, uses machine learning to determine which answers are pertinent to your search query. The company ranks answers based on results from its machine learning, such as thoroughness, truthfulness and reusability, when seeking to give the best response to a question.

 

civis analytics machine learning example application
Civis Analytics

Gaining Business Intelligence

How it’s using machine learning: Data analytics company Civis Analytics incorporates machine learning into the mix when it helps businesses make informed decisions about ways to identify, attract and engage its customers.

 

yelp service industry machine learning
Yelp

Sorting, Tagging and Categorizing Photos

How it’s using machine learning: Online reviews site Yelp relies on machine learning to sort through tens of millions of photos users upload to its site and then uses the technology to group them into various categories, such as, food, menus, inside the establishment or outside photos.

 

waymo transporation machine learning
Waymo

Making Self-Driving Vehicles Smart

How it’s using machine learning: Waymo’s self-driving vehicles use sensors that collect hordes of data that its machine learning technology crunches to help guide the vehicle on how it should respond when faced with various situations from a red light to a human walking across the crosswalk.

 

duolingo education machine learning
Duolingo

Timing Customer Notifications

How it’s using machine learning: Duolingo, a free language learning app, incorporates machine learning into its technology that assists language learners. Data collected from your answers undergoes Duolingo’s statistical model that predicts how long you will remember a certain word before needing a refresher course. Duolingo, as a result, knows when to ping you with a suggestion to retake the course.

 

label insight machine learning example application
Label Insight

Personalizing Food Product Information

How it’s using machine learning: Label Insight manages a database of over 200,000 product nutrients, 400,000 product ingredients and 9 million product claims. It’s product metadata platform uses machine learning to give a personalized view of each food product, such as ingredients, suppliers, and supply chain history, which, in turn, aims to help you make a decision whether to purchase the item.

 

fit analytics meachine learning examples applications
Fit Analytics

Assisting in Apparel Purchases

How it’s using machine learning: Fit Analytics, which helps consumers find the right sized clothes, uses machine learning to make recommendations on the best-fit styles. It also uses ML to assist brands in gaining insights into their customers from popular styles to average customer measurements.

 

Machine Learning applications AWS
Image: Shutterstock

Enhancing Cloud Services 

How it’s using machine learning: Amazon’s cloud service AWS offers free machine learning services and products such as its Amazon SageMaker to help developers and data scientists build, train and deploy ML models. AWS also offers Amazon Rekognition, which uses machine learning to identify objects, people, text, and activities in both images and videos.

RelatedWhat Is Deep Learning?

 

netflix entertainment machine learning
Netflix

Recommending Products and Services

How it’s using machine learning: Netflix uses machine learning to analyze the viewing habits of its millions of customers to make predictions on which streaming video shows you may likely enjoy the most and make recommendations based on those predictions.

 

Machine learning applications Trading Technologies
Image: Trading Technologies

Stock Market Trading

How it’s using machine learning: Trading Technologies, a futures trading platform, uses machine learning to identify trading behavior that could result in regulatory inquiries.

 

Dive DeeperMachine Learning in Edtech

 

asos retail machine learning
Asos

Calculating the Lifetime Value of a Customer

How it’s using machine learning: Fashion retailer Asos uses machine learning to determine the customer lifetime value (CLTV). This metric estimates the net profit a business receives from a specific customer over time. Machine learning aids Asos in determining which customers are likely to continue buying its products and which customers are likely to have low CLTV, which in turn could affect Asos offering them free shipping or other promotions.

 

deserve machine learning examples applications
Deserve

Assessing Creditworthiness

How it’s using machine learning: Deserve, a fintech company, uses machine learning for its creditworthiness assessment technology. Students and others who are first-time credit card applicants often do not have a credit history. Deserve’s machine learning technology takes into account other factors like an applicant’s current financial health and habits.

 

Dive DeeperMachine Learning's Important Role in Finance

 

twitter machine learning examples applications
Twitter

Ranking Posts on Social Media

How it’s using machine learning: Social media giant Twitter relies on machine learning to prioritize tweets that are the most relevant to you. Twitter’s ML now ranks tweets with a relevance score based on what you engage with the most and other metrics. High ranking tweets are placed at the top of your feed, so you’re more likely to see them.

Dive Deeper5 Machine Learning in Healthcare Examples

 

blue river technology agriculture machine learning examples applications
Blue River Technology

Identifying Plants

How it’s using machine learning: Blue River Technology, an agtech company, is grafting together machine learning and computer vision to differentiate between crops and weeds, as well as achieve proper spacing between plants. The company’s See & Spray rig targets specific plants and sprays them with herbicide or fertilizer.

 

hubspot machine learning example application
HubSpot

Improving Sales and Marketing Efficiency

How it’s using machine learning: Marketing, sales and service business software provider HubSpot uses machine learning in a number of ways. It gives content marketers insight into what search engineers associate their content with to assigning predictive lead scores for sales teams to use when assessing which customers are ready to purchase their products.

 

Where Else Will You See Machine Learning?

Businesses outside the AI industry, including retail, logistics and transportation, will benefit from the increased efficiency and unlocked potential of machine learning, said Andrew Ng, co-founder of Coursera and former leader of Google Brain and Baidu AI Group, 

And while integrating AI can be daunting and is a “big journey” for non-tech companies, Ng said at MIT Technology Review’s annual AI conference, “jumping in is not hard.”  

The key, he said, is starting small. 

“The only thing better than a huge long-term opportunity is a huge short-term opportunity. We got a lot of those right now.” 

Ng is also the founder and CEO of Landing AI, a company that helps build AI and machine learning resources for businesses that might not have the means or tech savvy to build them on their own. 

Matthew Johnsen, a content writer at IBM, predicts that we’ll start seeing more businesses selling machine learning as a service, just as Landing AI does, which in turn could lead to even greater adoption of machine learning in the future.

“As this technology advances,” Johnsen writes, “more businesses will embrace the AI revolution.”

Images are via Shutterstock, company websites and social media.

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