What Is AI Engine and Do I Need It?

sasha uritsky

Mar 29, 2018

Chatbots and assistant programs designed to support conversations with human users rely on natural language processing (NLP). This is a field of scientific research that aims at making computers understand the meaning of sentences in natural language. The algorithms developed by NLP researchers helped power first generation of virtual assistants such as Siri or Cortana. Now the same algorithms are made available to the developer community to help companies build their own specialized virtual assistants. Industry products that offer NLP capabilities based on these algorithms are often called AI engines.

The most powerful and advanced AI engines currently available on the market are (in no particular order): IBM Watson, Google DialogFlow, Microsoft LUIS, Amazon Lex.

All these engines use intents and entities as primary pnguistic identifies to convey the meaning of incoming sentences. All of them offer conversation flow capability. In other words, intents and entities help to understand what the incoming sentence is about. Once the incoming sentence is correctly identified you can use the engine to provide a reply. You can repeat these two steps a large number of times, thus creating a conversation, or dialog.

In terms of language processing ability and simplicity of user experience IBM Watson and Google DialogFlow are currently above the pack. Microsoft LUIS is okay too; still, keeping in mind that Microsoft are aggressively territorial and like when users stay within their ecosystem, it is most efficient to use LUIS together with other Microsoft products such as MS Bot Framework.

Using AI engine conversation flow to create dialogs makes building conversations a simple, almost intuitive, task, with no coding involved. On the flip side, using AI engine conversation flow limits your natural tendency to make conversations natural. The alternative, delegating the conversation flow to the business layer of your chatbot, adds richness and flexibility to your dialog but makes the process more comppcated as it now requires coding. Cannot sell a cow and drink the milk at the same time, can you?

Amazon Lex lacks the semantic sophistication of their competitors. One can say (somewhat metaphorically) that IBM Watson was created by linguists and computer scientists while Amazon Lex was created by sales people. As a product it is well packaged and initially looks pleasing on the eye, but once you start digging deeper you notice the limitations. Also, Amazon traditionally excelled in voice recognition component (Amazon Alexa) and not necessarily in actual language processing.

The space of conversational AI is fluid and changes happen rapidly. The existing products are evolving continuously and a new generation of AI engines is in the process of being developed.

Interested in reading more? Check out our other blogs:

The End of Digital Monitoring Paradigm

Digital industry is changing rapidly.

For the last decade analysis of social chatter and capture of consumer sentiment was considered the cutting edge of the marketing strategy. In these early days of the new era of digital information businesses were told to listen to what market is saying about them. They were educated on the importance of media monitoring and the advantages it creates for strategic growth.

This picture has become outdated.

Listening to Big Data, in all its aspects and forms, is no longer enough. After you successfully listened and understood what customer said the next natural step would be to act, or respond. And so the digital domain is now spreading to include responses, with a host of innovative technological solutions reshaping the field rapidly. Advances in artificial intelligence in particular create disruptive scalable opportunities in the space traditionally known for its slow manual progression.

Facebook was among the firstto enter the market, introducing bots into the process of connecting users with brands. Then there was Microsoft's turn.

Following these developments bots became the hottest trend in Silicon Valley in 2016.

nmodes fits seamlessly into this new world order. We deliver AI solutions that power business sales process. Our listening solution accurately monitors and captures real-time needs and interests of individual customers within the defined audience. And our Intelligent Assistant solution brings scalability to responses without compromising on quality.

The Advantage of Social Engagement for Business, in Simple Words

Much is being said about social networks and their importance for businesses. The amount of analysis, explanations, and advice keeps on growing, while the matter is being investigated from every possible angle, real and imaginary.

As for me, the need for businesses to market and sell on social can be explained by a simple argument.

Here it is.

The principle advantage of social networks for a business over other mediums is in the social networks’ potential to build trust. Traditional marketing mediums, such as TV, newspapers, internet, radio, etc. are not designed to build trust. They are information channels, or scaling vehicles, or sales means, but their primary goal is not to build trust. Social networks, on the other hand, are exactly this - a trust building tools.

And herein lies their biggest advantage in today’s market. The endless variety of options consumers have and the ever growing dissatisfaction with traditional aggressive marketing methods, such as commercials or banners, means that creating trust between businesses and their audiences is now the most efficient way to attract customers. The way that guarantees long-term sustainability and growth.

This is, simply put, the reason for businesses to embrace the social.