Effloresce Stomachum

Stomachum is our own framework for data management and optimization. We use Cerebrums API bridge and libraries to create large database systems that are much more efficient than other AI systems. Stomachum is designed to hold storage in the future in an offline environment and create a hardware set for build out of the Effloresce suite.

Framework: Effloresce Stomachum Framework Version: 0.01a Framework Update: Jan 24 2024 Framework: Effloresce Stomachum Framework Version: 1.0b WORK: Pillar data files to MySQL instead of flat .imp files. Design Pillar system for deeper learning profiles (half pillers), compression with CUDA and RAM combined. Move .01 data to new JBOD system.

Work Flow:

Compression:

Effloresce has a very unique system of compressing data, using its in-house pillars framework and deep learning models the older and more data in the database (Effloresce Knowledge) the greater the compression will be. It is important to understand that the compression of a file is for AI storage, the file would not be able to be used when its compressed in its native format, for example we compress thousands of MP4 files for AI machine learning, these MP4s are compressed with the pillars framework and stored on a HD these "packages" or file could not be viewed without being put back into pillars. We understand that the pillars technology could be used in the future on stand alone systems but for now its only on Stomachum in Effloresce

Sample compression data:

Video File MP4 (compressed): Codec: H264, Frame Rate: 60, Frame Size / Resolution: 1920 x 1080p Uncompressed Size on Disk: 130267 MB Stomachum 0.008a size: 70112 MB - 60155 MB savings - 1.85:1 Ratio - 46.17% Compression

Video File RAW: 4K ProRes 4444, Frame Rate: 30, Resolution: 4k. Uncompressed Size on Disk: 979658 MB Stomachum 0.009a size: 120014 MB - 859644 MB savings - 8.17:1 Ratio - 87.75% Compression