AI-led or AI-assisted? AI in education is already here, but its future is still being decided. Who’s leading the space? How are they approaching AI-powered EdTech? And what does AI ethics mean in the context of education?
BERT Explained: Taking NLP to the Next Level
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BERT is the latest and greatest in Natural Language Processing technology. Our VP of Marketing, Andrea Kulkarni, stops by the blog to explain what it is and how it impacts Lexalytics.
Bias in AI and Machine Learning: Sources and Solutions
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Bias in AI causes machine learning-based systems to discriminate against particular groups. We investigated why AI bias occurs, and how to fight back.
The Crucial Piece that NPS Misses, and How to Fill the Gap
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Net Promoter Score (NPS) is great for a quick view of customer satisfaction and brand health. But NPS can be dangerously misleading. Here’s why.
Sentiment Accuracy: Explaining the Baseline and How to Test It
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How accurate can we get with automated sentiment analysis through natural language processing? Let’s run a quick test and see what we learn.
Build or Buy for Natural Language Processing?
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8 m
From customization to scalability, there’s a lot to consider when deciding whether to build or buy an NLP or system. In this article we outline the dilemma and explore the pros and cons and costs of both options.
Sentiment Analysis in Diabetes
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When it comes to medical research, scientists are increasingly turning to social media data. In this article, researchers from Sant Baba Bhag Singh University use Lexalytics to study the impact of treatment and dietary practices on patients with diabetes.
Cloud or On Premise for Data Analytics: How to Choose
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These 4 factors are driving big names back to private cloud or on premise implementations for data storage and analytics. Should you move, too?
We Used AI On 6,000 Game of Thrones Predictions
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We mined 6,000+ Season 8 Game of Thrones predictions on Reddit. Then we used our AI to analyze them. Here’s what we found.
Machine Learning Micromodels: More Data is Not Always Better
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Machine learning micromodels reduce the challenges of sourcing and annotating data while delivering better precision and accuracy than macromodels.
Stories of AI Failure and How to Avoid Similar AI Fails in 2019
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9 m
Starting a new AI project in 2019? This article has the info you need to avoid an embarrassing AI failure: stories of big AI fails, expert advice, and more.
Fight Organizational Bias with Unstructured Data
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Efforts to fight organizational bias often fall short. Lexalytics CEO Jeff Catlin explains how to use unstructured data to fight your own company’s biases.
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