Spotify brings you “the right music for every moment,” and thanks to machine learning, they do it well. There are over 180 million active users on Spotify. And, with over 83 million paid subscribers, Spotify’s share of the streaming market is 40% (and growing). How do they do it? On AI at Work, Spotify’s Machine Learning Leader, David Murgatroyd, shared stories and lessons they have learned.
Topics: machine learning
When the average consumer sees headlines like DeepMind's AlphaGo AI becoming the most formidable Go player in the world, they often wrongly conclude that all artificial intelligence solutions are as dominant in their respective fields, and that they achieve that dominance almost immediately.
At Talla, we have an automation platform for support teams that automates much of the support process away. It's a combination of a very different knowledge base (although we work with other KBs) and a chatbot. What is unique about our product is that you don't have to script out anything. You don't have to build bot decision trees. The bot learns from your Support documentation like a human would. Then it connects to your other Support systems to take action. Instead of a search engine, it's an action and automation engine that you can control from a web, or chat interface. (Plug: If that sounds cool, get a demo.)
One question that we often hear is, “How is Q&A in Talla different than search?” While both are ways of finding information that you’re looking for, Q&A gives users a specific answer to their question, whereas search provides a list of possible places that your answer might be. Search makes you do the work of finding the answer by digging through the results. Ask yourself: Would you rather have the treasure in front of you or a handful of maps that might lead to it?
Customer support is one of the most challenging, time-consuming, and costly aspects of any business, but artificial intelligence software can help make your customer support team more efficient. Below are five steps in your tech support workflow that AI can speed up, simplify, or streamline.
Every time technology shifts, people are caught off guard and there is this phase in the market where the new technologies are being thought of using the old frameworks. That’s where we are with AI today. Buyers are looking at enterprise AI software like it’s one of the SaaS solutions they bought in 2014. It’s not.
Artificial intelligence technology has matured to the point you can entrust AI bots to handle many customer service functions, but new AI tech means new AI bugs that many organizations have never seen before. Below are some of the most famous cases of "good bots gone bad" and the underlying bugs you need to prepare for when AI takes the reins of your customer interactions.
You’ve likely heard the saying, “Change is the only constant.” This is certainly true for the world of work today. The future of work is a topic that gets a lot of attention in the mainstream media, specifically around negative scenarios and the dangerous idea of us all ending up jobless as technology takes over.
Topics: Future of Work
Every time a sales representative responds to a prospect with the words "I don't know," your knowledge base has failed. While most knowledge base solutions aren't designed to explicitly support sales teams, there are still steps you can take to optimize your knowledge base content for sales success.
“You have to approach technology as: How does it benefit someone’s day? You’re trying to save them time or money or improve their general outlook on their customers. How do you take AI and make processes better, make the information better, make the workflows better?” -- Jim O’Neill