TON Blockchain Testnet Lite Client to be Available

Telegram team hadn't confirmed the authenticity of the page and the data published on it
30 May 2019   860

Users have gained access to the test network of the Telegram Open Network (TON) blockchain platform - a preliminary version of the light client has been published.

This simplified version includes only the files needed for compilation, in particular, the RocksDB database and the Abseil library. After assembling and configuring the light client, it connects to the full node of the TON test network.

In addition, the site published step-by-step instructions for creating smart contracts in TON in the Fift programming language specially created for Telegram.

Additionally, users can familiarize themselves with the description of the TON virtual machine and blockchain platform.

It should be noted that representatives of Telegram did not publicly confirm the accuracy of the page and the data published on it.

Recall that the launch of the TON blockchain platform will take place in the third quarter of 2019. Earlier, developers reported on the successful conduct of a closed testing project.

You can get more info and download source code, configutation file, etc at the webpage.

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   199

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.