Jam – Zero Hallucination Big Data Storage Engine

What if you could offload training and inferencing onto the SSD’s SATA controller instead of a GPU?

Well it turns out you can, and the result is: lossless hyper-compression, 100x smaller files, a nearly 50,000x cost reduction in terms of terabytes learned per watt, a 44x reduction in upfront hardware costs, indirect-encryption that resists man-in-the-middle attacks, and you gain the ability to train and infer on mission critical datasets such as VMs and DNA in real-time.

By pushing AI compute to the edge of the SSD controller (away from CPU and GPU memory) we unlocked a new type of storage computing engine with far and wide practical uses.

JAM was originally developed for speeding up transfer times in industrial site-to-site datacenter backups, and to significantly reduce the memory footprint required for cross-domain learning operations, but has turned into a more general purpose archival tool.

This post is our first formal announcement since the inception of our JAM product almost 10 years ago, a public demo is provided on our website.

We are eager to hear your thoughts.