What is LotusX AI.

Big data Analytics holds significant promise for the future of the Aerospace Industry.

In 2017 LotusX has estimated over 180,000 Big Data jobs will be unfilled by 2018 in the US. Having over 20% of these jobs just in DC and Philadelphia combined and another 15% in NY City we are here in great proximity to take on this opportunity. Call Us!

Hoofar

Data Science Manager


Scale R/Python Packages

to thousands of CPUs across hundreds of machines.


Typical Use Cases

hyper-parameter search, batch prediction, and feature transformation.


Never Limited to Spark Libraries

From a single node to an elastic cluster of 100 cloud instances

No Need to Setup an AWS Account

Lotus-X leverages WorkSpace Service and will provide you with a download link to connect to the servers via X11/Active Screen. From each server LotusX AI would deploy your code across requested cluster using our own AWS account.

Execute Parameterized Commands in Parallel

Lotus-X produces and curates a comprehensive library of data visualization tools for data pertinent to Aerospace industry involving testing procedures of helicopters, fixed-wing UAVs, etc. Some libraries are already made available on the web. We also do research on data visuallization on mobile in ultra HD and on Oculus in virtual reality

Machine Learning Results Tracking and Custom Logging

Monitor the CPU/GPU/RAM utilization of each cloud resource.

Automatic model reporting and logging.

Evaluate from a list of models that have shows success on Kaggle competition.

Remote Monitoring

Lotus-X remotely monitors drones’ and rovers health conditions with a small, unobtrusive hardware plugin that tracks vital signs of the sensors and actuators, enabling immediate intervention. The in-disposable product allows for continuous, reliable, and undisturbed monitoring for up to 30 days.

How LotusX AI work.

Practical SimpleRun any local machine learning pipeline on a fleet of cloud instances without any change in your code. Zero hassles in data migration and environment setup for new cloud servers.


Framework Agnostic Compatible with any machine learning framework. Run large-scale computation on PetaBytes of data with any R / Python / Java / C++ code.


Measuring & Logging

Cloud resource (CPU/GPU/RAM) utilization tracking and machine learning experiment analysis. Transparent overview of your cloud spending for each of your task.