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Deep learning, neural network architectures, model training, and bleeding-edge AI research — pushing the boundaries of what machines can learn and understand.
Watch data flow through network layers in real-time
Core competencies driving our neural AI capabilities.
State-of-the-art architectures for vision, language, and multi-modal understanding.
Efficient training pipelines with distributed computing, mixed precision, and LoRA adapters.
Automated neural architecture search to discover optimal model configurations for your data.
Object detection, segmentation, generation, and visual reasoning at production scale.
Large language models, embeddings, sentiment analysis, and semantic search systems.
Reward-based learning for robotics, game AI, optimization, and autonomous decision-making.
| Model | Accuracy | Latency | Parameters | Status |
|---|---|---|---|---|
| ShivAI-7B | 94.2% | 12ms | 7B | Production |
| ShivAI-13B | 96.8% | 28ms | 13B | Production |
| ShivAI-70B | 98.1% | 85ms | 70B | Research |
| ShivVision-L | 97.3% | 8ms | 2.1B | Production |