It's particularly useful in workloads where time-sensitive relevance is critical. For example, an AI agent's memory especialized for long-term context retention, we could allow for graudal knowledge decay based on relevance. Older interactions would become less relevant leaving space for newer info

Basically, an L2 BTC Implementation

🔹 60% lower memory footprint than legacy UTXO systems
🔹 Thread-safe, atomic operations for secure state transitions
🔹 Merkle-based verification for provable cryptographic integrity

This is just Phase 1 🚀🚀🚀

github.com/JtPerez-Acle...

#BTC #Crypto #Web3 #Blockchain #Rust

💾 Memory Efficiency:
UTXO Cache – ~2MB per 1000 UTXOs, with negligible growth under load
State Updates – Linear scaling (~1MB per 100 participants)
Concurrent Operations – Additional ~2MB overhead for thread management
Signature Verification – Constant ~1MB regardless of participant count

⚡ Performance Highlights:
✅ UTXO Cache Updates – 0.8ms (~1250 tx/s)
✅ Merkle Proof Generation – 1.2ms (~833 proofs/s)
✅ State Transitions – 2.1ms (~476 updates/s)
✅ Concurrent Updates – 3.5ms (~285 updates/s)
✅ Signature Verification – 0.9ms (~1111 sigs/s)

⚡ Performance Highlights:
✅ UTXO Cache Updates – 0.8ms (~1250 tx/s)
✅ Merkle Proof Generation – 1.2ms (~833 proofs/s)
✅ State Transitions – 2.1ms (~476 updates/s)
✅ Concurrent Updates – 3.5ms (~285 updates/s)
✅ Signature Verification – 0.9ms (~1111 sigs/s)