With Cortex, project teams can easily and intuitively add a wide range of data sources and then search, analyze and collaborate on those sources. Neural Concept Recognition technology, specifically built for Cortex, powers set analytics capabilities enabling end users to ask complex questions about concepts of interest in static and streaming data sources. Cortex also enables use of Vyasa’s library of deep learning analytical modules related to life sciences, healthcare, image analysis and predictive analytics.
Vyasa Vector is a library of chemistry related deep learning analytics modules available in Cortex. Drag and drop an SDF or CSV file containing SMILES string chemical structures into Cortex and get started with powerful chemistry analytics.
Neural Concept Recognition
For Cortex we’ve built proprietary deep learning technology called “Neural Concept Recognition” that can be trained on types of concepts, learn what mentions of those concept types “look like” and then find novel instances of those concepts in Big Data.
A key area of paradigm shifting capability for deep learning is in the area of image analytics. Cortex enables a range of deep learning analytics on image sets through simple drag and drop addition to Cortex. Pattern matching, object recognition and segmentation operations are all possible with Cortex.
Features & Benefits
Simple Data Integration
With Cortex we’ve turned the idea of what software is on its head. By building deep learning modules that can operate on data, we can start with A.I. and add the data instead of having to start with a database. Addition of data to Cortex is as simple as drag & drop for over 200 different file types including text (e.g. PDF, TXT, MS Word), spreadsheets (e.g. CSV, Excel), images (e.g. PNG, JPEG, TIFF) and specialized content (e.g. SDF, DICOM). Every data file you add into Cortex you can also download back out of it at any time in the future.
Data Source Cataloging
The Neural Concept Recognition engine built into each Cortex instance allows project teams to catalog not only information about the data sources that they’ve added to their system but also what concepts and relationships are present in those data sources. In so doing Cortex provides a powerful way to create a meta-data catalog of data sources.
Secure In-App Collaboration
Cortex has a secure chat service built right into it. Everyone on your team can collaborate in topic-based discussions related to the analytics being run or can direct message with each other. With Cortex’s deep linking feature any concept, data source or project result can be specifically linked to from discussion threads.
Desktop Rich Client App
Cortex runs as a secure desktop application on Windows, Mac and Linux machines against a highly-scalable cloud or on-prem LAYAR AI instance. This makes it simple to start working in the secure Cortex analytics environment with your team from a range of devices.
Project Based A.I. Analytics
Cortex is built to enable simple to use, powerful AI analytics modules in a collaborative project team environment. As such, we’ve built a library of deep learning modules into Cortex so that you can download the app, login, add data and start analysis. Projects are used in Cortex as the place where you can combine the data that you’ve added and the library of analytics modules that are available. Each module provides options for parameter optimization and a range of visualization outputs.