What makes Cooldimi bot different?
Written by Kuldip S. Pabla, co-founder and CTO of Cooldimi
The Yale University Professor David Gelenter's view is The Danger is not Machines Becoming Humans, but Humans Becoming Machines
As a result, Cooldimi's unique approach involves creating super intelligent bots by blending artificial intelligence alongside human intelligence, which is irreplaceable in bots technology for the time being.
A bite-sized content is what a bite-sized snack is as compared to a normal sized meal. By analogy, the bite sized content came up with the advent of the millennials generation. They do not like long articles, long videos; they like shorter articles, shorter videos (5 minutes max versus 30 minutes).
One of the customers - a popular science center- shared that they have a website that they continuously update. However, the customer has experienced lower web traffic that has been going down, though their site is continuously updated and has excellent contents. In my discussion, I suggested a messenger based interface, where the users can ask for smaller, shorter questions, and the responses are smaller, shorter and relevant answers. The customer would love to use that service. More important for desktops, laptops, tablets you need to open the website. In Cooldimi solution, all you need is to send a message, ask a question and then you get back the relevant responses. The customer marketing representative also would like to know whether their marketing campaign are successful or not. In addition they liked this idea, as is so focused to the point, because youngsters with a limited attention span would like to use messengers rather that browse entire websites looking for a specific answer.
They want to understand what is the real meaning of the questions people have (Gap Analysis) - What people really mean? What questions they should really ask, and they don’t?
Most of the bots - according to some sources they estimate close a million bots floating the Internet - are rule based. I would say between 80% to 90% bots are rule based. They behave exactly how they are programmed to. They cannot learn and cannot respond to anything they do not know.
The next generation of bots is when a user can communicate in natural language, the way speak. This is also referred to as Natural User Interface (NUI), like GUI. So if I say for example: What is the price of apples? or How much the apples cost? , while the intention is the same, different users may ask it in many different ways. Using Natural Language Understanding (NLU), the second generation bots can understand intentions and can answer the queries even if they are not programmed to answer so. These bots can also be continuously trained to augment their smartness.
That said, these bots cannot do what a human can do - understand emotions and sentiments. Humans in a face to face interaction, can see the gestures, voice inflections, the body language. One can see whether the person I am talking to is happy or not, maybe she or he is frustrated or enthusiastic . These are important cues in sales interaction.
But when talking to a broad audience of humans, how would an inanimate bot fine tune these conversations? It has to be done through sentiment analysis, and this is how a bot from cooldimi stands out. Not just we analyze sentiments, we use the cues to improve bot behavior to make it smarter.
What is Cooldimi?
"Cooldimi is a stealth mode startup in based out of Silicon Valley. Cooldimi's bot platform is focused on enabling conversational commerce by using Chatbots. Cooldimi thinks that AI machine learning Chatbots will not replace human beings in the near future.The Yale University Professor David Gelenter's view is The Danger is not Machines Becoming Humans, but Humans Becoming Machines
As a result, Cooldimi's unique approach involves creating super intelligent bots by blending artificial intelligence alongside human intelligence, which is irreplaceable in bots technology for the time being.
What is "bite-sized content"?
One of the customers - a popular science center- shared that they have a website that they continuously update. However, the customer has experienced lower web traffic that has been going down, though their site is continuously updated and has excellent contents. In my discussion, I suggested a messenger based interface, where the users can ask for smaller, shorter questions, and the responses are smaller, shorter and relevant answers. The customer would love to use that service. More important for desktops, laptops, tablets you need to open the website. In Cooldimi solution, all you need is to send a message, ask a question and then you get back the relevant responses. The customer marketing representative also would like to know whether their marketing campaign are successful or not. In addition they liked this idea, as is so focused to the point, because youngsters with a limited attention span would like to use messengers rather that browse entire websites looking for a specific answer.
They want to understand what is the real meaning of the questions people have (Gap Analysis) - What people really mean? What questions they should really ask, and they don’t?
Why a Cooldimi bot is different?
The next generation of bots is when a user can communicate in natural language, the way speak. This is also referred to as Natural User Interface (NUI), like GUI. So if I say for example: What is the price of apples? or How much the apples cost? , while the intention is the same, different users may ask it in many different ways. Using Natural Language Understanding (NLU), the second generation bots can understand intentions and can answer the queries even if they are not programmed to answer so. These bots can also be continuously trained to augment their smartness.
That said, these bots cannot do what a human can do - understand emotions and sentiments. Humans in a face to face interaction, can see the gestures, voice inflections, the body language. One can see whether the person I am talking to is happy or not, maybe she or he is frustrated or enthusiastic . These are important cues in sales interaction.
But when talking to a broad audience of humans, how would an inanimate bot fine tune these conversations? It has to be done through sentiment analysis, and this is how a bot from cooldimi stands out. Not just we analyze sentiments, we use the cues to improve bot behavior to make it smarter.
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