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…
Category: Data
Why more expensive doesn’t always mean better features, particularly for scheduling assistants
In many realms, the higher the price tag the more advanced the feature set. The rule of thumb is more…
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…
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…
The Data Science that Animates Amy
Data science is at the core of Amy Ingram, our AI personal assistant, and Data Scientists make up a big…
From Zero to Hero: Onboarding New Engineers
Building great tech teams is a really tough challenge. A lot of engineers underestimate how hard it can be. But…
Deep Learning at x.ai
Deep learning is a field within machine learning which uses algorithms that contain many layers of processing and transformations. x.ai…
What AlphaGo’s amazing victory doesn’t tell you about AI in 2016
[pullquote align=”right” cite=”” link=”” color=”” class=”” size=””]AI, today, is seamlessly woven into our daily lives.[/pullquote] AlphaGo’s recent defeat of champion…