Easily create and manage datasets via the Dataset Creators.
Visual dataset analysis via Iterative PCA or t-SNE algorithms.
Dynamic dataset gyms supported.
Visual editing of your model via drag-n-drop operations.
Easily visualize weights used.
Real-time debugging which allows you to view the data flowing through your network as you train.
Visually inspect what each layer sees from an AI perspective.
Visual blob debugging to view the data and diff contents of each blob flowing between layers.
Deep draw and deep dream generation over multiple octaves.
Neural Style Transfer (limited functionality) allows you to learn a style from one photograph and apply it to another 'content' photograph to produce a new art piece.
NOTE: Enhanced features are only available to SignalPop partners at this time.
Are you looking for a way to design, build, train and debug your AI models on your local Windows computer and easily integrate those models into your C# based product? The SignalPop AI Designer is specifically designed to help you do just that!
The SignalPop AI Designer is an AI development environment that helps develop, build, train, test and debug your MyCaffe AI models locally on your own Windows-based development PC. Even with the low-cost NVIDIA 1050ti GPU (under $250), you can start deep learning with GoogleNet or AlexNet on your local computer or laptop – without cloud charges!
SignalPop AI Designer Download – version 220.127.116.11 (9/18/2023)
Minimum System Requirements
The SignalPop AI Designer is built for Windows developers running on Windows 10/11 PC’s that have at least one NVIDIA CUDA based GPU installed. With that in mind the minimum requirements for the SignalPop AI Designer are as follows:
SignalPop AI Designer Specific Requirements
Operating System: 64-bit Windows 10/11
Hard Disk Space: 10 GB free disk space (SSD recommended)
System Memory (PC side): at least 8 GB
GPU Model: NVIDIA 1050TI or above with CUDA 11.8. CUDA support required with NVIDIA driver version 531.14 or later.
GPU Compute: compute 3.5 through 8.0 are now supported when using CUDA 11.7, CUDA 11.8, CUDA 12.0, CUDA 12.1 or CUDA 12.2 (requires driver 531.14 or later).
GPU Memory: 4 GB (8 GB or more recommended)
Multi-GPU Training: requires at least two headless TCC capable GPU’s.
Database: Microsoft SQL or SQL Express 2016 and above is recommended on Windows 10/11 running in Windows Authentication Mode.
Contact us to get access to Beta features, purchase a full-featured version or to be notified of product updates.