π§ Executive Overview & Core AI Research Pillars
Β
|
|
|
|
|
|
|
|
|
π¬ AI Systems Architecture & Research Compute Telemetry
|
|
| Telemetry Dimension | Operational Blueprint & AI Systems Parameters |
|---|---|
| Compute & Acceleration Infrastructure | Dedicated Linux workstation nodes β’ CUDA 12.x runtime β’ PyTorch 2.x β’ TensorRT / ONNX graph compiler acceleration |
| Autonomous Agent Orchestration | Closed-loop ReAct, Reflexion and Plan-and-Solve reasoning engines β’ Dynamic tool binding β’ Multi-agent consensus loops |
| Computer Vision & Restoration | Real-time YOLO (v5/v8/v11) object detection β’ GAN colorization / restoration (DeOldify, VCGAN) |
| RAG & Knowledge Retrieval | Dense semantic indexing β’ Atlas few-shot models β’ Knowledge-oriented reading comprehension (KoRC) |
| Extreme Neural Quantization | Low-bit weight representation (1-bit-per-weight) β’ Sub-8-bit matrix arithmetic for low-power edge deployments |
| Data Science & ML Ecosystem | High-dimensional tensor modeling β’ Scikit-Learn β’ NumPy β’ Pandas β’ PyTorch |
π Featured Open-Source Engineering Artifacts
Open Science & AI Research Sponsorship
If you find my open-source AI implementations, neural models, and development tools valuable, you may support continued independent research through:
- Ethereum (ETH):
0x526968dF2AB74d7B4132F8D68Cf1BE6D126c6f82 - Binance Smart Chain (BNB):
0x526968dF2AB74d7B4132F8D68Cf1BE6D126c6f82
- Ko-fi: ko-fi.com/danielpahlavan
- WebMoney: Donate via WebMoney
- Regional Support (Iran): Reymit β’ Coffeete
Β© 2026 Danial Pahlavan β’ Deep Learning, Computer Vision, RAG & Autonomous AI Systems