Category: Data

How the 2018 election affected your workweek

Blue wave? Red wall? We’ll leave the political analysis of the 2018 midterms results to the pundits. We’re interested in how the 2018 election affected your workweek. More specifically, what happened to meetings scheduled on Election Day and the day after?  Following the 2016 election, we reported a substantial dip in meetings scheduled. With what…
Data, Meeting Scheduling, Productivity

Time Lord’s Manual: Ticker Tracking

The Time Lords Manual is a series of 1-minute reads on how to become a master of your time. (You can read the Time Lords Manifesto here). Keeping track of how you fill your day is one of the easiest ways to identify and cut down on wasted time. This theory, which we call Ticker…
Data, Time Lords

How we calculate our AI’s ROI

If you missed our webinar on “Leveraging AI for Business,” we took a look at how to know whether an AI investment is merely a flashy tech accessory, or one that can provide tangible value for your business. Here’s a quick rundown on how to discern between the two: AI with true business ROI: -Solves…
Artificial Intelligence, Data, Productivity

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 (which goes by the names Amy and Andrew Ingram) is a fully autonomous agent. To build Amy and Andrew, we’ve needed to collect and process an enormous amount of scheduling related emails (5 million and…
Computing, Data, Startup

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 take breaks, they never take a day off. x.ai’s approach to building a fully automated intelligent agent means our agents can operate with unrivaled speed and reliability. Over the past two weeks, we’ve halved the…
Artificial Intelligence, Computing, Data

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 the best practices for a given area. Some of these practices are in the areas of data science, javascript, data engineering, and user testing. Some members of a practice are highly skilled in that area,…
Artificial Intelligence, Computing, Data

Why anti-lean startups are back

We’re living in an era (once again), in which startups are taking on some really gnarly technical challenges. These companies are building self-driving cars, high-speed transportation systems, AI autonomous agents, and mining 99% of the genome that hasn’t really been understood yet in terms of how it affects the human body and disease. Many of…
Artificial Intelligence, Data, Startup

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 agreed to meet with someone, just cc amy@x.ai and she’ll take over from there. You won’t hear from her again until she’s successfully negotiated a time and place to meet. We modeled Amy and her…
Artificial Intelligence, Computing, Data

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 a database that can handle it all. Our CTO and co-founder, Matt Casey, explains how as we see more and more use cases its important to have a Schemaless database that would support the dynamically…
Artificial Intelligence, Computing, Data