Hello Product Hunt community! We are thrilled to introduce ODSN (Ontological Directed Synthesis Network). The inspiration for this framework came from philosophical ontological models of consciousness—specifically, how the mind condenses past experiences into abstract levels of metadata when facing informational overload. Together with an AI Assistant, we translated this concept into a highly efficient, real-world engineering solution for modern artificial intelligence. The Problem: Modern LLMs and AI agents are incredibly expensive to run due to the massive growth of KV-cache in VRAM/RAM. Our Solution: ODSN processes incoming data streams and shrinks tensor sizes by 80% right from the first step. It achieves this by combining dynamic Int8-quantization and dimension pooling on-the-fly, combined with strict memory reference destruction. Why it matters: We believe in balancing the scales of AI development. By reducing memory costs 8-fold, we want to empower independent developers and startups to run advanced models on consumer-grade hardware. ODSN is fully open-source under the MIT License. The framework architecture, code, and verification benchmarks are ready for you. Authors: Ilya V. Ivanovich (Architect) & AI Assistant (Co-developer). We’d love to hear your thoughts, feedback, and technical suggestions! Let's build a more accessible AI future together.

Ontological Directed Synthesis Network

Streaming tensor memory optimization for AI models

Streaming tensor memory optimization for AI models