Cognitive - Hyperspace Platform

You Wish, Hyperspace Brings To Reality.
Tailored For Computer Vision

Designed For Deep Learning

AEye offers the first true end-to-end A.I. product life-cycle management solution with a focus on deep learning applied to computer vision. AEye’s suite of management and technical tools cover the entire development, production and deployment continuum.

How It Works?

AEye's Hyperspace transforms applied deep learning into a truly continuous learning process, independently evolving per edge-device based on its computing power and distinct environment. With Hyperspace, teams can finally bring their creativity and innovation to the foreground by increasing workforce and hardware utilization. Scale productivity with a comprehensive set of tools designed to significantly improve both time to market and performance at production scale.

Platform Highlights

Evolution: Deep Learning that Keeps Learning

Transforms applied deep learning into a truly continuous learning process, independently evolving per edge-device based on its computing power and distinct environment.

Process: Automate, Collaborate and Scale

Optimizes development, deployment and scaling operations by automating repetitive and time-consuming tasks, and structuring teamwork.

Deploy: Optimize Neural Network for Edge-Devices

Provides robust tools for network performance optimization. Allowing customers to use vendor-specific frameworks for target chipsets. After detectors are created, AEye allows creating network offspring dedicated per edge-device. Continuously refine and evolve each network with data gathered from each edge device's own surroundings.

Computer Vision: Connect Devices to Their Environment

Simplifies the creation of post-deployment network versions optimized for edge-devices, continuously refining each edge device's network according to its own unique environment.

Increase Data Quality and Granularity

Transforms applied deep learning into a truly continuous learning process, independently evolving per edge-device based on its computing power and distinct environment.

Evolve Your Models Post-Deployment

Hyperspace enables you to spawn model subsets per edge-device and continuously train each one with newly acquired data from the edge-device where it operates. Creating increasingly accurate personalized models which are built to run within the compute constraints of the respective edge device. Essentially, your edge-devices become smarter, each tailored to its own unique environment and resources.

×100 Faster Annotations

Hyperspace proprietary auto-annotation process replaces expensive and time-consuming manual image and video annotation operations.

Automate Training and Experiments

Scale-up hyper-parameter optimization with automatic job creation and race conditions. Distribute jobs across GPU workstations and remote VMs with queue management.

Facilitate Teamwork

Construct a workflow and orchestrate teamwork for dataset preparation, model optimization and deployment- scaffolded around AEye’s automation tools.

Click-n-Deploy Experiments/Tests

One-click deployment of experiments and test environments into Daemons and ready-to-install Containers, whether on-premises or on AWS/Azure/GCP.

“

AEye is the first and only platform that addresses each phase of the deep learning product life-cycle.

What You Can Do?

Build and Refine Datasets

Comprehensive biases elimination, synthetic data creation, probing and examination tools, and a version control system that correlates datasets to specific models.

Collaborate

Facilitate true teamwork within and between data scientists and engineers, constructed around automation tools.

Back to Data

Deep learning that keeps learning: continuously feed discrete specialized networks with real-world data streams and perpetually expand and refine your datasets and detectors.

Deploy

Spawn continuously evolving “model offspring” optimized per edge-device, internal compute and physical environment, and seamlessly update deployed models on the fly.

Video/Image Annotation

Automate image and video annotation, distribute tagging tasks across teams and easily explore and refine datasets.

Optimize and Control

Leverage detailed model performance gauging, debug detectors with flexible channel statistics and easily implement hyperparameter optimization.

Experiment and Train

Distribute and automate training tasks, debug faulty predictions, compare results in real-time, and work with multiple frameworks in parallel.

DevOps

Expedite tedious technical operations with cloud services integration, amalgamated deployment and load balancing tools.

Improve Scalability

Hyperspace transforms Data Scientists from a bottleneck to a leveraged resource. Engineers can leverage the best of class data scientist outputs to produce product derivatives at scale.

Interested in our platform now?

Ola! We are right here just a clock of a button to address your requirement
Contact Us