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.

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Pros and cons of automation

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.

AI: Our Only Weapon Against Climate Change?

Artificial Intelligence, more commonly referred to as simply AI, has been, since it’s early days, changing our lives in many ways. AI has become one of the greatest inventions of the human mind. When thinking of AI, we do not normally associate AI as being involved in helping farmers grow more crops to feed the exponentially growing population, or helping develop cancer treatment, or even keeping kids safe from trafficking and abuse by finding improper online activities. Instead we think of computers to phones, to self-driving cars and robots. However AI doesn’t just power the gadgets that we have grown so accustomed to in our daily lives, but it is increasingly being used to help solve impending social challenges.

One of these impending social issues is the quite literally hot topic – global warming. The challenges of global warming are growing by the day, as its impacts are becoming more severe and harder to manage. Melting ice caps, severe sever weather changes, extinction of species, are just a few of the consequences of the manmade climate change that is plaguing our world today. Despite widespread acceptance and awareness, the rate at which the world is embracing positive change is unfortunately not fast enough.

Fortunately there are many large companies that are setting an example by using AI to develop new ways in which to battle global warming. In fact, it seems as though AI is the only solution we have. It is helping us not only track and our present data, but also analyze our past data so that we can make informed decisions about the future. One such example is the use of AI to collect large amounts of data on land, animals, weather, ecosystems, etc… and organize it, so that scientists and governments can then determine what needs to be done, and the most cost effective ways to engage conservation methods.

We are quite surely seeing more and more AI initiatives being undertaken to help create a more eco-friendly world.

In order to reduce human influence on nature, increasing levels of human interference with natural processes are required” (Harvard University)

Whatever the downfalls of AI may be, its ability to help us against destroying our planet is perhaps its most important trait – because as hard as it may be to accept, our planet is dying and AI can help us prevent that.