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Explora todas las tecnologías del grafo por tipo y categoría.
Por tipo
Por categoría
- Algoritmos 30
- Modelos 16
- Modelos de embedding 8
- Técnicas 35
- Prompting 10
- Frameworks 12
- Frameworks de LLM 6
- Bases de datos 3
- Bases de datos vectoriales 8
- Motores de búsqueda 4
- Infraestructura 15
- MLOps 4
- Evaluación 6
- Hardware 11
- Seguridad y alineación 6
- Aplicaciones 7
- Multimodal 5
- Agentes de IA 4
- Benchmarks 11
- Conjuntos de datos 7
11 technologies shown
- GPU hardware A processor built for massive parallelism, which is what neural network maths needs.
- A100 hardware NVIDIA's datacentre GPU that made large-model training routine.
- NVIDIA CUDA platform NVIDIA's parallel computing platform, the layer most AI software is written against.
- H100 hardware NVIDIA's datacentre GPU that became the default for training large models.
- H200 hardware Refresh of the H100 with substantially more high-bandwidth memory.
- NVLink hardware High-bandwidth interconnect between GPUs, letting them share memory directly.
- Tensor Core hardware Dedicated matrix-multiply units inside NVIDIA GPUs.
- V100 hardware The first NVIDIA GPU with tensor cores, and the one early transformers trained on.
- B200 hardware NVIDIA's Blackwell-generation datacentre GPU.
- TPU hardware Google's purpose-built accelerator for tensor arithmetic.
- MI300X hardware AMD's datacentre accelerator with a large unified memory pool.