Microsoft AI products

sasha uritsky

May 28, 2017

Microsoft product strategy has always been and still remains that of ‘zero alternative’. Their ultimate policy is for their customers to have no choice but to embrace only Microsoft products. Consequently they created and are offering products and solutions in (almost) every segment of IT enterprise and consumer market, including, but certainly not limited to, their own data base, their own cloud services, operating system, office tools, programming language, and many more.

Not only do Microsoft offer wide variety of products, they tie them up together in a unified ecosystem that makes it easy for components to connect and interact. At the same time, this ecosystem is hostile to non-Microsoft products.

Microsoft strategy for the burgeoning, fast growing AI segment is similar:

Create products to address all parts of the AI market, add them to the ecosystem to ensure easy compatibility from within and difficulty of use from outside.

Currently the products on offer are:

- Microsoft AI engine, called LUIS. It is supposed to compete with other major industrial AI systems such as IBM Watson, and has similar training methodology. It offers webhook interfacing via endpoints.

- Microsoft chatbot building platform, called, surprisingly, Microsoft Bot Platform. It addresses the popular demand for easy chatbot design and provides seamless connectivity with main user interfaces, such as web interface, SMS, mobile, and messaging platforms.

- In addition Microsoft offers their own messaging platform in Skype.

The main advantage of using Microsoft AI products is the built-in connectivity with user interfaces.

The main disadvantage is in their ‘zero alternative’ policy - once you’ve chosen a Microsoft product you are likely will be forced to choose only Microsoft products for the duration of your project.

Interested in reading more? Check out our other blogs:

The Curious Case of AI Technology

The notion of Artificial Intelligence has been around for a while.

Yet, unlike other prominent technological innovations such as electric cars or the processor speed, its progress has not been linear.

In fact, as far as industrial impact is concerned, there were times when allegedly there was no progress at all.

The widespread fascination with AI started several generations ago, in 80-s of the last century. This is when a pioneering work of Noam Chomsky on computational grammar led to a belief that human language capabilities in particular, and human intelligence in general, can be straightforwardly algorithmized. The expectation was that the AI-based programs will have a significant and lasting industrial impact.

But despite unabridged enthusiasm and significant amount of effort the practical results were minuscule. The main outcome was disappointment and AI become somewhat of a dirty word for the next 20 years. The research became mostly confined to scientific labs, and although some notable results have been achieved, such as development of neural networks and Deep Blue machine beating acting world champion in chess, the general community was largely unaffected.

The situation started to change about 5-10 years ago with a new wave of industrial research and development.

We now experience somewhat of a renaissance of AI with bots, semantic search, self-service systems, intelligent assistant programs like Siri are taking over. In addition, optimists of science are bragging confidently about reaching singularity during our lifetime.

The progress this time seems to be genuine indeed. There are indisputable breakthroughs, but even more impressive is the width of industries adopting AI solutions, from social networks to government services to robotics to consumer apps.

For the first time AI is expected to have a huge impact on the community in general.

There is this vibe around AI which hasn’t been felt in years. And with power comes responsibility, as they say, - prominent thinkers such as Stephen Hawking raised their voice against the dangers of powerful AI for humanity. Still, as far as current topic is concerned, this is all part of the vibe.

Despite all the plethora of upcoming opportunities, it is important to observe that we are yet to advance from anticipation stage. AI has not became a major industrial asset, an AI firm has not reached a unicorn status, and despite the fact that major industrial players such as IBM are pivoting towards fully-fledged AI-based model it has not manifested itself in business results.

We are still waiting for AI-based technology to disrupt the global community.

The overall expectation is that it is about to happen. But it hasn’t happened yet.

Easy Yet Untapped Revenue Channel for Hotels Worldwide

There are many travelers looking for hotels and places to stay on social web. Every day.

Take Twitter, for example:

Or this:

People are genuinely looking for help. Surprisingly though only few are getting it. According to nmodes data less than 12% of Twitter travel requests are being answered. The rest - lost opportunities for hotels and businesses in the hospitality industry.

And how big is this opportunity anyway?

nmodes Twitter data shows that every 15 min somebody expresses intent of going to, or visiting New York. Most of these travelers need a place to stay there.

Every 33 min - intent of traveling to London.

Every 54 min - intent of traveling to Paris.

We started Twitter recommendation service @nmodesHelps and were encouranged by the results. 72% of those that received our travel recommendations reacted by thanking us and expressing their gratitude. This reinforced our assumption that people seek travel advice on Twitter, accept it as an instant value, and are prepared to act upon it.

The hotels that are ready to move fast to monetize this opportunity will benefit the most.