Neural Network to Write Picture-Based Poems

Microsoft had created XiaoIce chatbot that is the neural network poet
13 August 2018   557

Microsoft has trained XiaoIce's artificial intelligence system to read the image and generate Chinese poems describing what is depicted on it. This is reported by The Next Web.

The system consists of two neural networks. One of them recognizes the details in the picture and selects keywords, and then generates a poem. The second part evaluates the total. The algorithm received a set of instructions from the researchers and worked until the best result was achieved. If it did not suit the researchers, they changed the instruction set and restarted the system.

For example, for such an image, the algorithm generates a poem:

Example Image for XiaoIce
Example Image for XiaoIce

Wings hold rocks and water lightly

in the loneliness

Stroll the empty

The land becomes soft
 

Xiaolce's Poem

According to scientists, modern Chinese poetry requires great imagination and creative use of language, which is a difficult task even for a person.

To determine the quality of the program, the researchers conducted experiments, where they offered people to choose between the poems of the Microsoft bot and other algorithms. In the overwhelming majority of participants chose the first option.

Facebook to Release PyTorch 1.0

This release added support for large cloud platforms, a C ++ interface, a set of JIT compilers
10 December 2018   106

Facebook has released a stable version of the library for machine learning PyTorch 1.0. This iteration added support for large cloud platforms, a C ++ interface, a set of JIT compilers, and various improvements.

The stable version received a set of JIT compilers that eliminate the dependence of the code on the Python interpreter. The model code is transformed into Torch Script - a superstructure over Python. Keeping the opportunity to work with the model in the Python environment, the user can download it to other projects not related to this language. So, the PyTorch developers state that the code processed in this way can be used in the C ++ API.

The torch.distributed package and the torch.nn.parallel.DistributedDataParallel module are completely redesigned. torch.distributed now has better performance and works asynchronously with the Gloo, NCCL and MPI libraries.

The developers added a C ++ wrapper to PyTorch 1.0. It contains analogs of Python interface components, such astorch.nn,torch.optim, torch.data. According to the creators, the new interface should provide high performance for C ++ applications. True, the C ++ API is still experimental, but it can be used in projects now.

To improve the efficiency of working with PyTorch 1.0, a Torch Hub repository has been created, which stores pre-trained models of neural networks. You can publish your own development using the hubconf.py file, after which the model will be available for download by any user via the torch.hub.load API.

Support for C extensions and the module torch.utils.trainer were removed from the library.

Facebook released the preliminary version of PyTorch 1.0 at the beginning of October 2018, and in two months the developers brought the framework to a stable state.