Saturday, October 21, 2017

Artificial Intelligence Gluon

Last week, an interesting industry news that Microsoft and Amazon announced a surprise partnership to build AI platform (named Gluon) for an enterprise. Gluon makes it easier for developers to build AI/machine learning systems, and related Apps with open source concept.

I've an interesting dimension of this technology partnership to challenge Google's big area of AI dominance using Tensorflow.

Google TensorflowGoogle already has a head start with a tool called Tensorflow, which is free and open source and aimed at helping developers build machine learning apps. Tensorflow is immensely popular with developers.

In fact, it's the the fifth most popular project (by stars) on GitHub out of the over 2 million hosted on that site where open source projects are shared. Quick introduction video is shown at

Amazon MXNetNaturally, Amazon has a competitor to Tensorflow called MXNet.  Deep learning on AWS with MXNet, is shown at

Microsoft CNTKMicrosoft has a competitor tool for Tensorflow, called CNTK (Cognitive Tool Kit). Microsoft's open source deep-learning toolkit is shown at

Strategic Partnership
Machine learning and AI are the next big things in cloud computing, with the potential to cause significant changes to the cloud business that Amazon and Microsoft have long dominated.
Microsoft and Amazon have been known to cuddle up on other AI types of tech.

In August, the two announced they were partnering to make their two voice assistants work better together , Amazon Alexa and Microsoft Cortana.

Joint Venture GluonMicrosoft and Amazon have joined forces to help spread artificial intelligence across apps. They released a new tool for developers called Gluon as a free and open source project, meaning anyone can use it or work on it and contribute to it for free.

Gluon's role is to add a layer that makes MXNet and CNTK easier to use, work with and program. Only the MXNet version was released now; but the CNTX version of Gluon is promised to come soon. Short introduction is shown at

Ease for AI DevelopmentIn any case, the competition to create more AI tools for developers, and make them easier to use.  Demand of Artificial Intelligence in various industries, are reflected in 3 years scorecard

Saturday, September 30, 2017

Anywhere in an Hour

During Yesterday presentation at the International Astronautical Congress in Adelaide Australia, Elon Musk shared an inspirational speech on "Anywhere in earth in an hour"

Details are available at

Personally, I admire Elon's vision, commitment, building disruptive technology, enabling tech to the society usage and so on.

Sunday, September 24, 2017


Industry Graph share is led by Neo4j and Titan, the latter recently acquired by DataStax (DataStax Enterprise Graph).

Social graphs are a prime example of utilizing the graph model, Dr. Xu (PhD from UCSD) was working at Twitter till 2011, and the graph databases that were around at the time could not cope.

He has 26 patents in distributed systems & databases, led Teradata's big data initiatives, and worked on Twitter's distributed data infrastructure. So when faced with that problem, Xu saw an opportunity and went off to create a solution.

Xu founded GraphSQL in 2012 and has been working with a team of 30 engineers since.  Today GraphSQL is officially entering a new stage in its development, including a new name: TigerGraph.

The product is now generally available, a series A founding round of US$33 million is announced and a hosted version of TigerGraph based on Amazon EC2 is launching.

TigerGraph also supports different graph partitioning algorithms enabling it to split very large graphs over a distributed architecture. This can be done either automatically, or as specified by users using application-specific partitioning strategies.

There probably is a hefty price tag that goes with TigerGraph, but for the ones that can afford it, it looks like it can deliver some substantial benefits.

Thursday, August 24, 2017

C# 8.0

C# 8.0 has been previewed in Channel 9 by Mads Togersen.  Ref:

Top 5 tech highlights are:

1. Nullable Reference Types
Consider a scenario where you know that the nullable variable x isn’t actually null, but you can’t prove that to the compiler. In this case you can use x!.Method() to suppress the compiler warning about potential null reference exceptions.

2. Extension Everything
As with interfaces, you cannot define instance fields in extensions but you can simulate them using ConditionalWeakTable. You can also define static fields.

3. Default Interface Implementations
The primary benefit of default interface implementations is that you may be able to add new methods to an existing interface without breaking backwards compatibility.

4. Async Streams (a.k.a. foreach async)
This is referred to as a “pull model”. By contrast, IObservable is a “push model”, which means the producer can flood the consumer with a higher flow rate than it can handle.

5. Extension Interfaces
Extension interfaces, the ability to add new interfaces to existing classes, is also being considered.

My closing note is C# is ahead of tech capabilities and roadmap, on comparison with Java.

Tuesday, August 15, 2017

.NET Core 2.0

Happy 70th Independence Day of India to my brothers and sisters.

Coincidently, Microsoft released Visual Studio 2017 version 15.3, the release of .NET Core 2.0, and a release of Visual Studio for Mac version 7.1.

VS 2017 ver 15.3 has over 1,700 improvements and still have some work to do, but if you are using Visual Studio 2017 in a low-vision or no-vision mode, a lot has improved. For the full list of improvements check out at

.NET Core 2.0 is also released today. This is the second major version of .NET Core and this release focuses on performance improvements and expanding the set of APIs available via .NET Standard 2.0. It includes the runtime and libraries for .NET Core as well as the tools for building, debugging and running .NET Core applications.

Visual Studio for Mac version 7.1 is also available today. It adds support for .NET Core 2.0 targeting in console apps, web apps, and web services. It also enables creating .NET Standard 2.0 in library projects, to share more code across projects. Like Visual Studio 2017, a lot of the improvements in this update center on reliability.

Monday, July 31, 2017


On attending FICCI-90th annual conference, key take away is "Continuous learning to sustain the career; Continuous sharing to collaborate the industry trend". Itz applicable not only for individual but also enterprise.

More details are available at

Sunday, July 23, 2017

Yahoo Bullet

Yahoo Bullet is a highly distributed framework designed for cloud multi-tenant data centers that let you run forward-looking queries. Bullet queries act on data flowing through the system after you submit the query.

In other words, you query data that will arrive, rather than data that has already arrived. Unusual for an open source project, Bullet also includes a visual user interface, so you're not necessarily restricted to command line or third party tools. And it also has a REST API for programmatic access.

As a query engine, Bullet was designed to be light weight, adding minimal overhead as you process streams. But there is some heavy lift involved in that the raw data, formatted as Avro files, must be parsed into columns that can then be hit with SQL queries that are placed over sliding time windows.

For now, Bullet is early stage technology, available as open source through GitHub. There's no vendor support and it's not part of any tool, so you're on your own with regard to managing and integrating it. Bullet competes in a very crowded landscape of log monitoring engines such as Splunk, Logstash/Elasticsearch, and others that provide near real-time capabilities.

The challenge for getting mindshare is proving the case that forward-looking queries provide the edge in knowing your customers through the digital log file footprints they leave.