I'm creating NeuraScribe — AI that becomes a seamless extension of your memory and thinking, helping you connect ideas and insights in ways that feel completely natural.
Explore NeuraScribe"The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it."
What if AI didn't replace human thinking, but amplified it? What if technology could learn how you process information, remember details, and make connections — then become an invisible extension of your mind?
That's the future I'm building with NeuraScribe.
A memory companion that learns your unique thinking patterns and becomes an extension of how you naturally process information.
Currently in active development, focusing on episodic memory systems and personalized knowledge graphs.
Learn more →Advancing retrieval-augmented generation and exploring how cultural context shapes AI behavior and decision-making.
Published work on memory networks, RAG systems, and ethical AI development.
View research →Advanced retrieval system achieving 94% accuracy
Built the foundation for memory-augmented AI using PyTorch and transformer models. This microservice demonstrates how AI can intelligently retrieve and contextualize information in real-time.
View technical details
- Vector embeddings with semantic search capabilities
- Multi-domain knowledge retrieval with 94% accuracy
- Optimized for real-time inference and scalability
- Integration with transformer models for contextual understanding
Efficient algorithms for real-time memory operations
Developed high-performance data structures using Red-Black Trees and Min-Heaps, achieving O(log n) complexity for memory allocation and retrieval — principles that directly inform AI memory architecture.
Interested in the future of human-AI collaboration?
Building the future of augmented cognition • Gainesville, FL