A.I. Powered Chatbots in the Enterprise

The world is moving faster than ever with technology increasing that rate of speed. And now your customers want answers in real time. Using AI to enable chat features on your website gives you a direct line of communication with these customers. For many, waiting is not an option and it’s so easy to click over to your competitor’s page.

Here’s a real-life example. I recently ordered a running vest for an upcoming ultramarathon. I had been waiting a couple weeks for the vest to arrive and began thinking something was wrong with my order. So, I opened the vendor’s page to check on it. I was clicking through the support section of it when in the lower right-hand corner, a familiar animation appeared.

It was a chat feature!

Through my interaction with the chat feature, I was able to explain the issue and walk through the steps to correct my order. It was a great customer experience from my end. And an expedient one for the vendor. My issue was handled in a quick and frictionless manner, creating a happy customer for them. This is one of the reasons why the chat feature makes real-time customer service a game changer for the customer experience.

How much of that conservation was with a person or an AI-enabled Chatbot? To me, it didn’t matter. 

What is a Chatbot?

Chances are you have interacted with a Chatbot while searching for help on a website or mobile application. Have you ever thought about how much of that interaction was with a human or machine?

A chatbot is a software application used to engage with humans mostly through text. We’re all proficient at this technology, through our smartphones or through instant messaging as on Slack, Teams, Skype, or if you are as old as me, AOL Messenger. The difference is that instead of your co-worker or a friend on the other end, it is an application.

Now we’ve stated that this conversation mostly happens through text. The focus here, however as AI- enabled voice technology continues to grow, these conversations will happen more through text-to-speech in the future. With the understanding that Chatbot technology is a software application mimicking human conversation, let’s look at the surprisingly long history of chatbots.

The Long History of Chatbots

Did you know the history of Chatbots goes back as early as the 1950s? Alan Turing, the pioneering British WWII Enigma codebreaker, also considered to be the father of computer science, published a paper on what is now termed the “Turing Test” in 1950. Turing proposed to answer the question “can machines think” as tested by having a machine interact with a human — without a human knowing it is interacting with a machine. The publication of this landmark paper kicked off the technology that we now see used in modern day Chatbots. And just recently, it was announced that a new U.K currency will honor Alan Turing for his amazing work.

◉ 1961 – The IBM Shoebox was a computer that could recognize 16 spoken words

◉ 1966 – ELIZA was created in the MIT AI lab and it could demonstrate very basic communication

◉ 1996 – Clippy was an early incarnation of a Chatbot in Microsoft’s office products

◉ 2000s – The 2000’s marked a great feat again with IBM introducing Watson to the world on Jeopardy

◉ 2010s – Voice assistants like Siri and Alexa emerged with the ability to answer questions through voice technology

To this day, software engineers and computer scientists use the Turing test to evaluate their “thinking machines.” There is controversy as to whether we have yet passed the Turing test, but I’ll leave it for others to debate. The most important point for us to take away is that not only do Chatbots have a long history in artificial intelligence, but they also play a foundational role in how AI is changing nearly every industry, with increasing adoption of chatbots and other real-time human to machine interactions.

Dell Technologies for Chatbot Architectures  

At Dell Technologies, we have been working with AI technologies such as chatbots and the underlying systems that power them, including machine learning (ML) and deep learning (DL), for many years. We understand their complexities. And we also work closely with our technology ecosystem partners, including NVIDIA, to accelerate AI adoption. Together, we provide the essential architectural building blocks required for the rigors of data science.

Source: delltechnologies.com