Author: Intel Software - Bewertung: 3x - Views:11
Intel's AI PC software stack simplifies AI development and deployment. It offers a comprehensive suite of tools and frameworks, including OpenVINO, ONNX Runtime, WebNN, and PyTorch, for seamless model integration. With the AI PC Development Kit and AI Playground, developers can easily experiment, prototype, and build AI applications, unlocking the potential of AI on PCs.
Discover how Intel's AI PC software stack is revolutionizing AI development and deployment, offering a suite of tools and frameworks that enable seamless model deployment and an out-of-the-box AI PC experience. Learn about the end-to-end model deployment flow, including runtimes and frameworks such as OpenVINO™, ONNX Runtime, WebNN, and PyTorch. Leverage tools and solutions like the AI PC Development Kit and AI Playground for experimentation, rapid prototyping, and building AI applications. This session empowers you to harness the full potential of AI on PCs, driving innovation for developers and customers.
Intel Innovation: https://intel.ly/46ixwbA
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Intel AI PC https://www.intel.com/content/www/us/en/products/docs/processors/core-ultra/ai-pc.html
How to get started:https://docs.openvino.ai/2024/get-started.htmlhttps://docs.openvino.ai/2024/_static/download/OpenVINO_Quick_Start_Guide.pdf
OpenVINO Samples
https://github.com/openvinotoolkit/open_model_zoo/blob/master/demos/README.md
OpenVINO ecosystem framework support:
HuggingFace
• OpenVINO space in HuggingFace – FP16, INT8 and INT4 preconverted models ready for deployment! https://huggingface.co/OpenVINO
• Option 1: Use OpenVINO GenAI to run models from HuggingFace https://docs.openvino.ai/2024/learn-openvino/llm_inference_guide/genai-guide.html
• Option 2: Use Optimum-Cli to run models from HuggingFace https://docs.openvino.ai/2024/learn-openvino/llm_inference_guide/llm-inference-hf.html
ONNX
• Option 1Conver ONNX model to OV format (IR) https://docs.openvino.ai/2024/openvino-workflow/model-preparation/convert-model-onnx.html
• Option 2: Use ONNX models thru OpenVINO ONNX Execution Provider https://onnxruntime.ai/docs/execution-providers/OpenVINO-ExecutionProvider.html
Pytorch
• Option 1: Convert pytorch model to OpenVINO format (IR) (recommended for best performance) https://docs.openvino.ai/2024/openvino-workflow/model-preparation/convert-model-pytorch.html
• Option 2: Use pytorch models with Torch.compile https://docs.openvino.ai/2024/openvino-workflow/torch-compile.html
LangChain
• Example of LLMs inference with LangChain and OpenVINO https://python.langchain.com/docs/integrations/llms/openvino/
• Reference RAG implementation with OpenVINO and LangChain https://docs.openvino.ai/2024/notebooks/llm-rag-langchain-with-output.html
LlamaIndex
• Example of LLMs inference with LlamaIndex and OpenVINO https://docs.llamaindex.ai/en/stable/examples/llm/openvino/
• Reference RAG implementation with OpenVINO and LlamaIndex https://docs.openvino.ai/2024/notebooks/llm-rag-llamaindex-with-output.html
Pytorch 2.5 support for Intel GPUs
https://pytorch.org/blog/intel-gpu-support-pytorch-2-5/
AI PC Dev Kits
https://www.intel.com/content/www/us/en/developer/topic-technology/ai-pc/dev-kit.html
AI Playground
https://github.com/intel/AI-Playground
GIMP on Intel® Core™ Ultra Mobile Processors
https://www.intel.com/content/www/us/en/developer/articles/tool/enable-ai-for-gimp-core-ultra-mobile-processors.html
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Empowering AI PC’s with Intel’s AI Software Stack | Tech Talk | Innovation Selects | Intel Software

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