In our previous post, we discussed how finance, insurance, and security companies are using AI to improve employee productivity and catch the bad guys before they commit a crime. In this post, part three of five, we’ll see how teachers are using AI to customize lesson plans, how media companies are harnessing AI for curating and creating content, and how e-commerce is using AI to make our lives easier.
It’s the work every teacher inevitably brings home. Luckily, AI can automatically grade multiple choice and fill-in-the-blank types of tests. Soon, using natural language processing, AI will even be able to grade essays.
Fixed mindset individuals believe they have innate talents that are set at birth, whereas growth mindset individuals believe that every failure is a lesson leading to improvement. Artificial intelligence can improve either mindset by providing personalized AI as a tutor. Another way EdTech companies are using AI is to generate custom content based on a student’s diagnostics. This allows for adaptive testing that tailors itself to fit a student’s unique situation.
This type of personalized learning can scale throughout a student’s career. Carnegie Learning created a software called Mika that uses a blend of cognitive science and artificial technology to provide personalized tutoring and real-time feedback.
Carnegie Learning is focusing its efforts on college students, freshman in particular, to coach them through remedial courses that will improve their chances of success. Carnegie Learning has found that the remedial learning costs colleges $6.7 billion annually.
By removing this cost burden from colleges, that value would ideally be passed onto students in the form of cheaper tuition or improved learning opportunities.
It can be overwhelming. Media companies are expected not only to keep up with the demand for content and constant change in technology.
According to Jan Kautz, senior director of Visual Computing and Machine Learning Research at NVIDIA, AI will “be able to create new personalized media, such as music according to your tastes. Imagine a future music service that doesn’t just play existing songs you might like, but continually generates new songs just for you.”
Content generation via AI could be a huge boon for media companies. Reuters uses a system it calls Reuters Tracer to automatically identify and publish breaking news stories. Their system “processes 12 million tweets every day, rejecting almost 80 percent of them as noise. The rest fall into about 6,000 clusters that the system categorizes as different types of news events. That’s all done by 13 servers running 10 different algorithms“.
According to Accenture’s Jean-Luc Chatelain, this is all just the tip of the iceberg.
“We’re still at the dawn of AI adoption,” said Chatelain. “Brands have yet to fully understand all the ways in which AI will change the marketing game.”
When Amazon launched Echo Look in 2017, it wanted to bring a personal stylist into its customers’ homes. Echo Look’s style suggestions are driven by a combination of good old fashioned human advice and machine learning. All suggestions are, of course, easily purchasable through Amazon’s online market.
This is not Amazon’s first foray into AI-driven suggestions. However, they still have a ways to go. Researchers at the University of Toronto found that, “Amazon’s AI does a reasonable job, considering the millions of items on offer. However, they are far from perfect. In our case, the AI accurately predicts what we want to buy about 5 percent of the time. In other words, we actually purchase about one out of every 20 items it recommends.”
Beyond predictive suggestions, e-commerce paragons like Alibaba and Amazon are employing AI in a variety of ways to improve the efficiency and profitability of their businesses. They are also using it to interact with their customers.
Alibaba’s customer support chatbot was “able to detect abnormal levels of order status inquiries and took only 30 minutes to provide a solution to our affected customers. AI currently helps 100 percent of our customers with inquiries, and resolves 50 percent of them completely.”
And, of course, we can’t forget about Amazon’s Alexa, which allows customers to order products from Amazon using only their voice. Alexa is powered by natural language processing and machine learning, and offers a preview of what a buyer’s experience will be in years to come as AI continues to integrate with e-commerce platforms.
In that spirit, ask Siri to remind you to check Conversica’s blog for part four of this series. We’ll be exploring how artificial intelligence is helping legal and regulatory professionals streamline their industry and improve outcomes. We’ll also see how researchers in academic circles and science can use AI to better understand the massive amounts of data being generated in their respective fields.
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