Follow-Up Interview With Cobus The following is a redacted interview between Greg (CEO @ HumanFirst [https://www.humanfirst.ai]) and Cobus Greyling (www.cobusgreyling.me [http://www.cobusgreyling.me/]); in this interview, we dig deep
Practical semantic search and clustering Semantic similarity is quickly becoming a mainstream technique for working with natural language data; embedding new examples into a latent space uncovers the relationship between them. PineCone.io [pinecone.io]
Interview with Cobus Greyling [Greg] HumanFirst is a big fan of yours Cobus :) I've personally been reading your blog [cobusgreyling.medium.com] for the last two years, and have learned a lot about everything
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 [https://snorkel.ai/] leading the way, and other commercial [https://www.watchful.io/
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 [scale.com] (recently valued at $7B+ dollars [https://fortune.com/2021/04/13/scale-ai-valuation-new-funding-fundraising-data-labeling-company-startups-vc/#:~:text=Scale%20AI%2C%20a%20San%20Francisco,in%20the%20latest%20investment%20round.
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
