Are we focusing too much on the labeling problem? Programatic labeling has been a hot area of development in the last 2 years, with Snorkel Flow leading the way, and other commercial and open-source projects appearing in this space.
Voice of the Customer Data is 🚀 Most businesses are sitting on high-quality Voice of the Customer Data , generated across a growing number of channels in the context of sales, marketing, product and operations. Examples of activities
GPT-3 in Conversational AI The first iteration of HumanFirst was a browser extension that ingested customer support live chat conversations, trained a black-box AI model that predicted what the chat agent’s next response
Help Centers are Underrated in Conversational AI. In this article, I use the term "Help Center" to refer to all types of Help Center, Knowledge-base and FAQ solutions.Help Centers are rarely a core part of the
Labeling isn't hard if you know what to label. Companies like Scale.ai (recently valued at $7B+ dollars) were able to build massive businesses  around data cleaning & labeling for AI: this is a human-intensive task, and companies flocked
Conversational AI should start with search. Let’s take an airline example: “I want to change my flight from the 3rd to the 4th”. This is one of the 1000+ requests that an airline might hear
Walking before running in conversational AI. Conversational AI is often equated with chatbots. Yet chatbots rarely do the “AI” part correctly (i.e: understanding user intents). Statements like “great conversational AI needs to move beyond dumb
Articles Building a Semantic Emoji Prediction NLU Learn one way to approach semantic Emoji prediction with cascading intents.
Articles The crux of NLU is managing the long-tail of data. Until now, building and maintaining the training data needed to support a long-tail of intents has been a difficult problem — yet this is what is needed to go from a
