The Unreasonable Effectiveness Of Neural Machine Translation: A Breakthrough In Temporal Expression Understanding
Written by Rakesh Chada and Marcos Jimenez, data scientists at x.ai. At x.ai we strive to make pain associated with…
Category: Computing
Machine Learning Infrastructure at x.ai
For over 5 years now, at x.ai we have been applying machine learning to the problem of meeting scheduling. Our…
How Amy + Andrew differ from chatbots
Our AI Interaction Designer Diane Kim explores the crucial differences between chatbots and conversational agents.
Reflecting on our tech stack in 2017
It has been three and half years since we founded x.ai. We have built an AI scheduling assistant. Our assistant…
6 reasons why scheduling is a machine task
There are many things humans do better than machines. Scheduling meetings isn’t one of them. When we set out to…
Amy now responds to your emails 2x faster
Amy and Andrew are performing in ways that even the best human assistant can’t match: they don’t sleep, they don’t…
Aspects of Deep Learning: Activation Functions
At x.ai, we have an organizational concept called “practices.” A practice is a group of people that come up with…
A peek at x.ai’s data science architecture
Amy and Andrew are AI personal assistants who schedule meetings for you. There’s no app. Nothing to download. Once you’ve…
The role of AI trainers in teaching a machine to understand us
Our AI personal assistant Amy schedules meetings. To do this, she must have a natural language dialog with your guests…
How x.ai uses MongoDB to build Amy
Building and training your meeting scheduling assistant, Amy, from scratch requires an immense volume of data, flexible design models and…
Using the Mongo Hadoop Connector as a Translation Layer to Spark
At x.ai, the data engineering team faces a fairly classic big data problem. We have lots of data, a prerequisite…