With the rise of natural disasters exacerbated by climate change, governments and agencies struggle to coordinate effective relief programs. Artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) can help. Here’s how. The cost of natural disasters is at an all-time high Natural disasters wreak havoc around the world every year. But it’s hard to appreciate the scale of this damage. Image source: NOAA As of October 2021, there have been 18 climate and weather-related disaster events in the U.S. alone, each causing more than $1 billion each, according to the ..read more

Tokenization is an interesting part of text analytics and NLP. A “token” in natural language terms is “an instance of a sequence of characters in some particular document that are grouped together as a useful semantic unit for processing.” Like the roots and branches of a tree, the whole of human language is a mess of natural outgrowths—split, decaying, vibrant, and blooming. Tokenization is part of the methodology we use when teaching machines about words, the foundational aspect of our most important invention. How Tokenization in NLP Works Imagine you want to process a sentence. One approac ..read more

Today I’m excited to share the news that Lexalytics has been acquired by InMoment, the leader in Experience Improvement (XI). If you haven’t already seen the press release it can be viewed here. For nearly two decades, Lexalytics has been a pioneer in structured and unstructured data analytics, translating text into profitable decisions with our natural language processing (NLP), machine learning (ML), and artificial intelligence (AI) solutions for the world’s most customer-centric brands. By joining forces with InMoment, we will now be able to offer our customers a greater, industry-leading p ..read more

While much of the tech world has come through Covid-19 relatively unscathed, some tech-focused industries have definitely felt the effects of the pandemic. As an AI and NLP software vendor with clients in myriad industries — including those with a focus on restaurants, airlines and hospitality — we were certainly affected, especially early on. However, with necessity being the mother of invention, we have adapted to this “new normal” and have emerged stronger than ever. Here are the lessons we’ve learned along the way. Talent Is More Important In A Pandemic A heavy-handed, top-down management ..read more

Popular media and hype cycles are leading us to expect radical changes and perfect results from artificial intelligence. But you don’t read perfectly, so why should your AI? Let’s explore when “good” is good enough for AI. You don’t read perfectly, so why should your AI? We have high expectations of AI. If it doesn’t spit out a flawless output, it’s not good enough. But are we being unreasonable in our expectations? Sure, it’s not great when a computer mistakes a 3D-printed turtle for a rifle. And we get that you might be nervous about the defensive driving skills of your self-driving car. But ..read more

Marketing for Pharma? We’re Listening. Part of the appeal of the show Mad Men was not just its dedication to recreating the look and feel of the 1960s, but that it was a story of advertising and marketing. Those characters crafted advertising campaigns based on “expertise,” which was really just their own emotional connections to a given product. Unfortunately, while this made for great drama, it doesn’t make for the best marketing strategy—especially in today’s world where doing this would mean actively ignoring your customers. A killer instinct for what people needed but didn’t know they nee ..read more

    One of the most important and most-used functions in text analytics and NLP is sentiment analysis — the process of determining whether a word, phrase, or document is positive, negative, or neutral. The first step in getting computers to understand the sentiment of text is understanding the sentiment behind individual words and phrases. Understanding sentiment happens on multiple levels: at the most basic, a sentiment analysis engine needs to understand that words and phrases like “appalling,” “morally bankrupt,” and “terrible” are negative, and words like “stellar,” “amazing,” a ..read more

It pretty much started here: McCulloch and Pitts wrote a paper [1] describing an idealized neuron as a threshold logic device and showed that an arrangement of such devices could express any propositional logic formula.  Their neurons looked like this: What this neuron does is fire if both of its excitatory inputs are active—unless the inhibitory input (with the black dot) is active.  McCulloch and Pitts would later go on to write a paper with Lettvin and Maturana [2] that showed how the neurons in a frog’s eye computed very specific environmental features. These were exciting times ..read more

(originally posted on Customer Think) COVID-19 has had an extensive impact on the hospitality industry. Shelter-in-place restrictions, along with event cancellations, reductions in business travel, and widespread job losses have altered how and why people travel. Faced with lower occupancy, shifting safety measures, and catering to an increasingly local clientele, hotels, and hotel-adjacent businesses are having to rethink their business models. Since 89% of businesses compete mainly on customer experience, it’s vital that hospitality providers deliver on guest expectations. A solid Voice of t ..read more

Text analytics, also called known also by text mining, has countless applications. Businesses are taking advantage of text analytics to update their service offerings, improve compliance, get ahead of PR disasters, and more. Here are 5 examples of the industries taking advantage of text analytics in 2021. 1. Hospitality Hotels live and die by their reviews. Reviews are not only crucial to whether someone books a stay, but they also give valuable insight into what a business is doing well – or not. And while the hospitality industry has been decimated over the COVID-19 pandemic, the quickening ..read more