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News 2016
This are archived News of 2016.
See the actual news at this page.
2016-12-22. V 2.0 Beta 7 Release
Highlights of this Release:
- Python API behaviour is changed to be more strict.
- New Examples and Tutorials (Artistic Style Transfer and GoogLeNet (Inception V3) ).
- New version of CNTK Evaluation library NuGet Package.
- CNTK Background Improvements.
See more in the Release Notes
Get the Release from the CNTK Releases page
2016-12-13. V 2.0 Beta 6 Release
Highlights of this Release:
- Both Windows and Linux packages are now created using NVIDIA CUDA 8.0 toolkit.
- Linux version now supports Python 3.5 (Windows support is coming soon).
- Support for training on one-hot and sparse arrays via NumPy.
- New Examples and Tutorials: Video action recognition, Finance Timeseries with Pandas/Numpy, Neural Character Language Models
- Stability Improvements and bug fixes.
See more in the Release Notes
Get the Release from the CNTK Releases page
2016-11-25. V 2.0 Beta 5 Release
Highlights of this Release:
- The Windows binary packages are now created using the NVIDIA CUDA 8 toolkit, see the release notes for details. The CNTK-Linux binary packages are still built with CUDA 7.5. The Linux support for Cuda8 will follow shortly!
- Performance enhancements for evaluation of bitmap images through the new
EvaluateRgbImage
function in the managed Eval API. - A new version of the CNTK Nuget package is available.
- Stability Improvements and bug fixes, i.e. decreased memory footprint in CNTK Text Format deserializer.
- We continue to improve documentation and tutorials on an ongoing basis, in this release we added a Sequence-to-Sequence tutorial.
See more in the Release Notes
Get the Release from the CNTK Releases page
2016-11-21. V 2.0 Beta 4 Release
Highlights of this Release:
- New ASGD/Hogwild! training using Microsoft’s Parameter Server (Project Multiverso)
- Distributed Scenarios now supported in CNTK Python API
- New Memory Compression mode to reduce memory usage on GPU
- CNTK Docker image with 1bit-SGD support
- Stability Improvements and bug fixes
See more in the Release Notes
Get the Release from the CNTK Releases page
2016-11-11. V 2.0 Beta 3 Release
Highlights of this Release:
- Integration with NVIDIA NCCL. Works with Linux when building CNTK from sources. See here how to enable
- The first V.2.0 Prerelease Nuget Package for CNTK Evaluation library
- Stability Improvements and bug fixes
See more in the Release Notes
Get the Release from the CNTK Releases page
2016-11-03. V 2.0 Beta 2 Release
Highlights of this Release:
- Feature tuning and bug fixing based on the feedback on Beta 1
- Changes in the Examples and Tutorials based on the same feedback
- New Tutorial on Reinforcement Learning
See more in the Release Notes
Get the Release from the CNTK Releases page
2016-10-25. New CNTK Name, new Web Site and V 2.0 Beta 1 Release
CNTK becomes The Microsoft Cognitive Toolkit. See more at our new Web Site.
With the today's Release we start delivering CNTK V2 - a major upgrade of Microsoft Cognitive Toolkit.
Expect a set of Beta Releases in the Coming Weeks.
Highlights of this Release:
- CNTK can now be used as a library with brand new C++ and Python APIs
- New Python Examples and Tutorials
- Support of Protocol Buffers serialization
- Support of Fast R-CNN algorithm
- New automated installation procedures
- Improvements in CNTK Evaluation library including support of CNTK APIs
See more in the Release Notes. You will find there links to the materials about the new features.
Get the Release from the CNTK Releases page
2016-10-03. V 1.7.2 Binary release
This is a Hot Fix Release. It affects all users of Model Evaluation Library
If you are NOT using Model Evaluation Library you may skip this release.
If you ARE using Model Evaluation Library we strongly recommend installing version 1.7.2 instead of any previous version you might be using.
See Release Notes for details.
2016-09-28. V 1.7.1 Binary release
Highlights of this Release:
- Two Breaking Changes related to Layers library default initialization and
fsAdagrad
gradient-normalization scheme - Improvements in BrainScript
- Enabling of Deterministic Algorithm enforcement
- Improvements in Model Evaluation including the support of Evaluation for Azure Applications
- Different Performance improvements
- Multiple bug fixes
See more in the Release Notes (including the full list of bugs fixed)
Get the Release from the CNTK Releases page
2016-08-31. V 1.7 Binary release
Highlights of this Release:
- Improvements in BrainScript (new library of predefined common layer types; common random-initialization types; GRUs)
- Support of NVIDIA cuDNN 5.1 and cuDNN RNN
- Improvements in readers and deserializers
- Additions to Evaluator library (Eval Client Sample, strong name for EvalWrapper)
- New unit tests incl. Linux support
- Python API Preview (since V.1.5)
- Multiple bug fixes
See more in the Release Notes
Get the Release from the CNTK Releases page
2016-08-29. Two new Tutorials are available:
Image recognition (CIFAR-10) and Language understanding (ATIS).
2016-08-10. We have significantly simplified handling of Gated Recurrent Units (GRU). Read more in the corresponding article.
2016-07-15. V 1.6 Binary release
Highlights of this Release:
- Deconvolution and Unpooling operations
- MKL Support (improved CPU performance)
- CNTK Model Evaluation runtime library for Windows and Linux
- OpenCV 3.1 (more efficient image preprocessing)
- Simple Python support
- Various bug fixes & optimizations
See more in the Release Notes
Get the Release from the CNTK Releases page
2016-07-12. We have further expanded Licensing options for CNTK 1bit-SGD and related components. See the details at the Wiki page. These new options are an extension of the new CNTK 1bit-SGD License that we have announced on Jun 23, 2016.
2016-07-05. CNTK now supports Deconvolution and Unpooling.
2016-06-23. New License Terms for CNTK 1bit-SGD and related components.
Effective immediately the License Terms for CNTK 1bit-SGD and related components have changed. The new Terms provide more flexibility and enable new usage scenarios, especially in commercial environments. Read the new Terms at the standard location. Please note, that while the new Terms are significantly more flexible comparing to the previous ones, they are still more restrictive than the main CNTK License. Consequently everything described in Enabling 1bit-SGD section of the Wiki remains valid.
2016-06-20. A post on Intel MKL and CNTK is published in the Intel IT Peer Network
2016-06-16. V 1.5 Binary release. NuGet Package with CNTK Model Evaluation Libraries.
NuGet Package is added to CNTK v.1.5 binaries. See CNTK Releases page and NuGet Package description.
2016-06-15. CNTK now supports building against a custom Intel® Math Kernel Library (MKL). See setup instructions on how to set this up for your platform.
2016-06-10. See CNTK v.1.5 binary release announcement in the official Microsoft Research Blog
2016-06-08. V 1.5 Binary release
CNTK v.1.5 binaries are on the CNTK Releases page
2016-06-01. An updated version of the network-description language has been made available under the new BrainScript Network Builder, which features full expression parsing, recursive functions, and more.
2016-05-19. A 1-hour talk describing CNTK, how to use it, and how it works, has been posted at Presentations.
2016-05-16. An example illustrating Using CNTK with ResNet is added to the codebase. The example contains some pre-trained models that can be used in various applications.
2016-05-16. CNTK Wiki now has FAQ Page
2016-05-05. CNTK now supports BlockMomentum Stochastic Gradient Descent (SGD) algorithm.
See the details in the Multiple GPUs and machines Wiki section
2016-05-03. New transformations are implemented for Image Reader.
See the description in the Image Reader Wiki section
2016-04-25. V 1.1 Binary release
CNTK v.1.1 binaries are on the CNTK Releases page
2016-04-12. CNTK is available as Azure Virtual Machines and Docker Containers
2016-04-12. Added support for ND convolution and ND pooling and CPU support for cudnn
layout in convolution, pooling and batch normalization nodes.
Read documentation on convolution, pooling and batch normalization nodes.
2016-04-05. CUDA7.5 support for Windows Build: Windows project files have been updated to automatically utilize CUDA 7.5 if present
2016-03-24. New Text Reader (CNTKTextFormatReader) is available
Read description here https://github.com/Microsoft/CNTK/wiki/CNTKTextFormat-Reader
2016-02-29. Added ZIP files support to the ImageReader
Examples: https://github.com/Microsoft/CNTK/wiki/Image-reader
Updated build steps at https://github.com/Microsoft/CNTK/wiki/Setup-CNTK-on-your-machine
2016-02-29. Added documentation for the ImageReader https://github.com/Microsoft/CNTK/wiki/Image-reader
2016-02-17. CNTK Contribution Guidelines are published
Check it out here: https://github.com/Microsoft/CNTK/wiki/Contributing-to-CNTK
2016-02-15. The first part of CNTK tutorial is published.
You can find it here: https://github.com/Microsoft/CNTK/wiki/Tutorial
2016-02-10. Binary release
Most up-to-date binaries are on the CNTK Releases page
2016-01-26. First binary release after the move to GitHub is published (GPU only).
2016-01-25 13:00 GMT. CNTK new repository in GitHub went public! Together with GitHub repository a new CNTK web site http://www.cntk.ai/ also became available.