Revolutionary Compression for Next-Gen AI? A Mathematical Breakthrough
Anthony Benavides’ patented approach (US Patent 12,136,933 B2) at SonicBoomKDP.com challenges fundamental compression assumptions with pure mathematics:
The Core Innovation:
Instead of traditional pattern matching, the system:
- Treats ALL binary as ONE unified number
- Converts to decimal form
- Transforms into optimized mathematical expressions
- Can leverage various bases and mathematical relationships
Why This Matters for AI:
With AI models hitting computational limits (like OpenAI’s reported Orion challenges), breakthrough compression could transform:
- Training efficiency
- Model deployment
- Storage requirements
- Processing bottlenecks
Example Transformation:
Binary: 11111111 11011000 11111111
Decimal: 16767231
Expression: Mathematical relationships/Various bases
I’m fortunate to be working on implementing Anthony’s revolutionary system. The elegance lies in its pure mathematical foundation - no patterns, no chunking, just mathematical relationships waiting to be optimized.
Could this be the breakthrough needed for next-gen AI? Visit SonicBoomKDP.com to learn more about Anthony’s innovative work.
Looking forward to exploring collaborations in this transformative space.