AI unmasked: How a chatbot is different from a voice bot

nmodes ability to accurately deliver relevant messages and conversations to businesses is based on its ability to understand these messages and conversations. Once a system understands a sentence or text, it can easily perform a necessary action, i.e. bring a sentence about buying a car to the car dealership, or a complaint about purchased furniture to the customer service department of the furniture company.

Understanding sentences is called semantics. nmodes has developed a strong semantic technology that stand out in a number of ways.

Here is how nmodes technology is different:

1. Low computational power. We don’t use methods and algorithms deployed by almost everyone else in this space. The algorithms we are using allow us to achieve high level of accuracy while significantly reducing the computational power. Most accurate semantic systems, e.g. Google’s, or IBM’s, rely on supercomputers. By comparison our computational requirements are modest to the extreme, yet we successfully compete with these powerhouses in terms accuracy and quality of results.

2. Private data sources. We work extensively with Twitter and other social networks, yet at the same time we process enterprise data.  Working with private data sources means system should know details specific only to this particular data source. For example, when if a system handles web self-service solution for online electronics store it learns the names, prices, and other details of all products available at this store.  

3. User driven solution. Our system learns from user’s input. Which makes it extremely flexible and as granular as needed. It supports both generic topics, for example car purchasing, and conversations concentrating on specific type of car, or a model.

Automation drives forward the economy. It allows businesses to scale and service large groups of customers. Automation first appeared in traditional industries, such as cotton production in England in 18th century or car conveyors in the US in early 20th century. The automation replaced physical labor.

With the invention of computers automated systems began to replace intellectual labour such as math calculations. Most of the software applications we use today can be described as automation. Online payments processing, online tickets purchasing, tax returns software, computer games, search engines, and endless other programs are all examples of software automation system.

As a next step we are now aiming at automating human decision making processing and high-level intellectual activities, historically considered to be sole domain of humans.

One interesting aspect of automation is lesser quality of service compared to manual service.

This is to be expected. If we gain in quantity we lose in quality.The gain in quantity is what automation is about - it allows to reach out to a large number of customers. Manual product or service can reach out to individuals only. The price we pay for the ability to deliver product or provide service en masse is the drop in quality.

Sometimes automation is an obvious choice. This is when the gain, the scalability, hugely outweighs the costs, lower quality. Search engine is a popular successful example. In other cases, the advantage in not so obvious. Online travel booking offers fast service without leaving the comforts of the home, but it does not often deliver the best option, such as finding the cheapest flight, and therefore many people still use ‘manual’ travel agents.