4 min read

Hyperledger Sawtooth 1.0, an implementation of AlphaGoZero, enhancements in PostgreSQL 11, SAS AI offerings, and more in today’s top stories around machine learning, blockchain, and data science news.

 

1.  Hyperledger Sawtooth 1.0, the second blockchain framework from Hyperledger, is now production ready

Hyperledger announced the availability of their second blockchain framework, Hyperledger Sawtooth 1.0. It is the latest open source digital ledger project, after Hyperledger Fabric which reached version 1.0 in July 2017.

Sawtooth 1.0 is equipped with several new enterprise features:

  • On-chain governance – Users can now utilize smart contracts to vote on blockchain configuration settings such as the allowed participants and smart contracts.
  • Advanced transaction execution engine – The engine can process transactions in parallel to accelerate block creation and validation.
  • Support for Ethereum – Sawtooth runs solidity smart contracts and allows integration with Ethereum tooling.
  • Dynamic consensus – Users can also upgrade or swap the blockchain consensus protocol on the fly, enabling the integration of more scalable algorithms as they are available.

Interested users can download the code here. They can also read the official documentation here.

2. Minigo: An open-source implementation of the AlphaGoZero algorithm

Minigo is a pure Python implementation of a neural network-based Go AI, using TensorFlow. It is inspired by DeepMind’s AlphaGo algorithm. Minigo is based on Brian Lee’s MuGo, which is a pure Python implementation of the first AlphaGo paper. The project provides a clear set of learning examples using Tensorflow, Kubernetes, and Google Cloud Platform for establishing Reinforcement Learning pipelines on various hardware accelerators. It reproduces the methods of the original DeepMind AlphaGo papers through an open-source implementation and open-source pipeline tools. The project aims to provide their contributions in the form of data, results, and discoveries for the benefit of the Go, machine learning, and Kubernetes communities.

More information is available at the official Github repo.

3. PostgreSQL 11 plans to add enhancements to Partitioning & Indexes

PostgreSQL 11 would be releasing this year, and the team plans to add some enhancements to partitioning and indexes. The whole idea is to allow Partitioned tables to have Referential Integrity, by way of Primary Keys and Foreign Keys, and some additional tweaks can be expected.

Foreign Keys (FKs) are implemented using row Triggers, so Triggers would allow them to be executed on Partitioned Tables.

Primary Keys are implemented using Unique Indexes, so an addition of indexes would allow them to be unique.

Following are some set of features and the order in which they have to be implemented:

  • Create Index on Partitioned Tables
  • Allow Unique Index on Partitioned Tables
  • Create Triggers on Partitioned Tables
  • Allow FKs on Partitioned Tables

To have a detailed read on this news visit the website.

4. SAS launches new AI offerings for Text Analytics, Data Mining, and Machine Learning

SAS, an analytics software development firm, has released a variety of new offerings for its SAS Viya Platform. This includes SAS Visual Text Analytics and significant enhancements to SAS Visual Data Mining and Machine Learning.

SAS Visual Text Analytics is a modern and flexible framework which can perform text mining, contextual extraction, categorization, sentiment analysis and search operations. It extracts value from unstructured data using NLP, machine learning, and linguistic rules.  The software allows users to prepare data for analysis, visually explore topics, build text models and deploy them within existing systems or business processes.

Apart from this, there are also enhancements in SAS Visual Data Mining and Machine Learning. It now offers an end-to-end visual environment for data access, data wrangling, sophisticated model building, and deployment. It has an in-memory, distributed processing to solve critical business queries. It also supports programming from popular open source languages like Python and R.

5. Cisco advances its intent-based networking with new analytics services

Cisco has introduced three new analytics tools to advance its intent based networking services. These analytics services are powerful assurance products spanning the entire networking portfolio.

  • Network Assurance Engine, which continually verifies network health and uses models to pinpoint issues with the network. It uses continuous verification of the entire network to help keep a business running as intended, even as the network changes dynamically. Cisco’s ACI and Tetration connect to the Network Assurance engine to link network and application monitoring.
  • DNA Center Assurance, which is a service that connects users and application behavior to make predictions. DNA Center Assurance provides problem isolation so IT teams can find a root cause quickly, replicate problems and offer guided remediation.
  • Meraki Network Health, which is a cloud IT management tool to automate network and IT operations. The tool finds poor performing access points and provides insights to improve service.

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