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Feb 23, 2018
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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.
How nmodes technology is unique
nmodes AI is based on semantic algorithms. They require significantly less computational capacity compared to standard machine learning algorithms used by a majority of conversational AI systems today.
As a result, the infrastructure requirements are drastically reduced. In simple terms, what Google Home or Amazon Alexa do with the help of supercomputers or advanced computer farms, nmodes AI can do on a basic server.
And it gives nmodes ability to delegate conversational capacity to the users. With the help of nmodes AI every business (and individual) can create their own AI to handle the details of the business (products, customers, etc) not accessible from the outside.