EOS to Release EOSIO V1.1.0

The new release is designed to lay the future scaling foundation of the blockchain platform infrastructure development
20 July 2018   1830

The developers of the EOS announced the release of the new EOSIO V1.1.0 protocol software.

The new release is designed to lay the future scaling foundation of the blockchain platform infrastructure development.

This release targets usability of the software for developers, laying a foundation for more scalable application development and support for an infrastructure team building on the EOSIO blockchain.

EOS Team

In particular, the release includes an optional MongoDB plug-in for EOSIO nodes, which makes it possible to archive blockchain data into the MongoDB database and perform highly scalable and convenient queries of this data.

Two other important updates include overload protection and the ability to quickly restore databases, as well as accelerated synchronization by avoiding attempts to transfer transactions from synchronized nodes.

Detailed documentation of the new release is available on GitHub.

TensorFlow 2.0 to be Released

New major release of the machine learning platform brought a lot of updates and changes, some stuff even got cut
01 October 2019   172

A significant release of the TensorFlow 2.0 machine learning platform is presented, which provides ready-made implementations of various deep machine learning algorithms, a simple programming interface for building models in Python, and a low-level interface for C ++ that allows you to control the construction and execution of computational graphs. The system code is written in C ++ and Python and is distributed under the Apache license.

The platform was originally developed by the Google Brain team and is used in Google services for speech recognition, facial recognition in photographs, determining the similarity of images, filtering spam in Gmail, selecting news in Google News and organizing the translation taking into account the meaning. Distributed machine learning systems can be created on standard equipment, thanks to the built-in support in TensorFlow for spreading computing to multiple CPUs or GPUs.

TensorFlow provides a library of off-the-shelf numerical computation algorithms implemented through data flow graphs. The nodes in such graphs implement mathematical operations or entry / exit points, while the edges of the graph represent multidimensional data arrays (tensors) that flow between the nodes. The nodes can be assigned to computing devices and run asynchronously, simultaneously processing all the suitable tensors at the same time, which allows you to organize the simultaneous operation of nodes in the neural network by analogy with the simultaneous activation of neurons in the brain.

Get more info about the update at official website.