Google to Urge to Solve Global Problems with AI

Companies selected as part of the AI ​​Impact Challenge will share a $ 25 million grant from the company
31 October 2018   315

Google urged non-profit, scientific and public organizations to suggest ways of using AI to solve social, humanitarian and environmental problems. Companies selected as part of the AI ​​Impact Challenge will share a $ 25 million grant from Google and will be assisted by AI specialists and will participate in the Launchpad Accelerator program. In the spring of 2019, an international team of experts will help Google choose the winning projects.

Google gave examples of successfully implemented projects that AI Impact Challenge participants can focus on:

  • Protection of Nature. Daniel de Leon used machine learning to analyze 100,000 hours of sounds made by rare whale species in the Pacific. Now AI automatically recognizes and classifies these sounds. In the future, scientists hope to use it to preserve rare mammals.
  • Fighting unemployment. The Harambee Youth Employment Accelerator project has helped more than 50,000 people in South Africa find jobs that do not require special skills.
  • Flood forecasting. Google developers have combined physical modeling and machine learning to predict floods.
  • Prevent forest fires. Two high school students from California created a device that uses AI to identify areas at risk of forest fires.
  • Baby health. The Canadian company Ubenwa has developed a mobile application that determines generic asphyxia by infant crying. Timely measures help reduce the risk of negative consequences for the newborn.

For those wishing to participate, but not sufficiently knowledgeable about machine learning, the company has compiled a manual.

When it comes to the use of AI, Google’s management is committed to ethical and reputational practices. In early October 2018, the company refused to participate in the Pentagon’s tender for $ 10 billion. A spokesman for the company said that this project may be contrary to the opinion of developers on the development of artificial intelligence.

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   125

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.