Rezultati pretraživanja
  1. 4. stu 2019.

    Runtime 1.0 is available. Our new release brings CPU/GPU performance optimizations, expands the list of execution providers, accelerates ONNX model shipping, and a host of other features. Learn more details here:

  2. 24. sij 2019.

    Rumor has it deep learning models are coming to . I can neither deny or confirm rumors. Only help spread them ¯\_(ツ)_/¯.

  3. 20. ruj 2019.

    Accelerate and optimize your machine learning models using and ONNX Runtime. Hear from experts on how ONNX Runtime accelerates Bing Semantic Precise Image Search in this video:

  4. 24. sij

    ONNX.js is an open source library for running models on browsers and on Node.js. It utilizes multi-threading in a JavaScript AI inference engine to offer significant performance improvements. Learn more here:

  5. 2. lis 2019.

    Early access to object detection built in pure with -go and running on cloudrun : Feel free to use it as an API.

  6. Osobe Vidi sve

  7. 29. stu 2018.

    ONNX.js is now available, allowing web to score pre-trained models on browsers and Node.js on both CPUs and GPUs.

  8. 30. tra 2018.

    Open sourced our parser for ‘s TensorRT inference platform.

  9. Windows Machine Learning supports specific versions of the format in released Windows builds. In order for your model to work with , you will need to make sure your ONNX version is supported for the release targeted by your application.

  10. 13. sij 2019.
  11. 26. lip 2018.

    [blog] Shintaro Okada, an engineer at PFN, who is a lead developer of Menoh, posted an article about the introduction to Menoh. Menoh is a library that can read trained DNN models in the format for inference.

  12. 13. svi 2019.

    We are excited to announce that DeepStack AI Server is now available as a native app for Windows systems. Windows users can now easily run pre-built Recognition APIs, Detection APIs and add their custom , and models as Custom APIs.

  13. 31. kol 2018.

    New ONNX v1.3 release just dropped. Thanks to the great collaboration with Amazon, Microsoft and the rest of the community!!!

  14. Connect(); is 100% online, and the demos (from what I've seen!) are going to be game-changing. Register here:

  15. 27. ruj 2018.

    Small victory! Converted a model from states/weights and network to an model - intermediate representation to then go places like Keras or Tensorflow. Wrote my steps down

  16. 17. lis 2018.

    to : first refacto ok; I wrote some docs and automatic tests for implementing new operators. BatchNorm is next on the TODO (I'd really like to run inception in the browser). Any contribution is welcome (there's no small contribution)

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  17. 8. tra 2019.

    With the latest release, is the world's first server to support custom , and models in one package. With the support, you can train in any framework including and deploy to production with

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  18. 23. lis 2019.

    Learn how to build a “Visual Alert” system for an IoT camera by using Cognitive Services to train an image classifier, and exporting that model to run locally on the IoT device.

  19. 9. pro 2018.

    All trends seem right on point. and enabled solutions will continue expanding in 2019. Great work ! AI Trends: 1. AI enabled chips 2. and AI convergence 3. Neural Network Tokit interoperability 4. Automated 5. AI+DevOps = AIOps

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