Learn how to use Huggingface transformers library to generate conversational responses with the pretrained DialoGPT model in Python.
Chatbots have gained a lot of popularity in recent years, and as the interest grows in using chatbots for business, researchers also did a great job on advancing conversational AI chatbots.
In this tutorial, we’ll be using Huggingface transformers library to employ the pretrained DialoGPT model for conversational response generation.
DialoGPT is a large-scale tunable neural conversational response generation model that was trained on 147M conversations extracted from Reddit, and the good thing is that you can fine-tune it with your dataset to achieve better performance than training from scratch.
#chatbot #python #ai #artificial-intelligence
The critical industry that has been massively impacted by the pandemic is the healthcare sector; however, AI’s involvement has helped the industry weather the pandemic storm. The AI applications by companies bring back patients’ lives from the edge and improve diagnostics and treatment and help healthcare providers make informed decisions quickly. One such application has been developed by Hospido, India’s first holistic cancer care platform with which cancer patients can get the right treatment advice from India’s best cancer doctors, without visiting hospitals amid pandemic.
The pandemic lockdown has forced many people, including cancer patients, to avoid hospitals and discontinue their treatment due to coronavirus risk. And this is what triggered Karan Chopra, the founder of Hospido to bring out quality healthcare to these cancer patients through telemedicine and satellite treatments centres for providing the right treatment at the right time. In this article, Analytics India Magazine, got in touch with him to understand how this startup revolutionised cancer carer amid pandemic.
#startups #ai chatbot #ai chatbot transformed cancer care #ai-enabled chatbot #chatbot #chatbot ai #chatbot for pandemic #chatbot india #chatbot transformed cancer care #hospido startup
Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.
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Last year, when one of our healthcare partners (we refer to our clients as partners) were looking to build a conversational AI chatbot, I was apprehensive about guiding them. I had only worked on the level 2 (out of the 5 levels of conversational AI) type of bots. But this time our partner wanted to build a contextual/consultative AI-powered chatbot assistant.
I was concerned about how the bot would understand end-users’ problems. What features can we build to make it more humanistic? Would it be successful in replacing human care and compassion? Would it replicate the same emotions of empathy, compassion, and care?
And even if we managed to do everything, how would we know if the conversational AI chatbot is working the way we designed it? How would we define the ‘success’ of our initiative?
My apprehensions became real when I read a Forbes article about chatbots killing customer service with their clumsy conversations and limited learning capabilities. After reading the below paragraph, I realized the problem—
“The AI didn’t always get it, which was frustrating. Even more irritating—the company using the chatbot seemed to shrug the problem off. I detailed my own experience using Skyscanner’s chatbot, which often misunderstood my requests. Some of the companies I mentioned in the column appeared to shrug off my concerns.”
The problem is with organizations/management who choose to look away and see the importance of data analytics in chatbots for healthcare. They think that understanding the users’ behavior, what disappoints them, what makes them happy, is beyond the scope of their work. Because of this mindset, chatbots are still a lost cause.
Is there a solution in sight?
Yes, indeed there is. We’re at a very interesting place where we hold the future of chatbots in our hands. To make chatbots more welcoming and user-friendly, we not only need to make its software side—engineering, UX design, security—more robust. Rather, we should strive to make data analysis a part of the development process—i.e. we must constantly monitor chatbot’s effectiveness and improve features as per users’ needs.
#chatbots #ai in healthcare #conversational ai chatbot #chatbot analytics #chatbot analysis #how to measure the success of a conversational ai chatbot
It’s said that Artificial Intelligence will be just as smart as humans by 2050. Experts like Ray Kurzweil have even predicted that we’ll achieve a technological singularity by 2045.
From that point on, it’s believed that AI will start inventing Nobel Prize-winning inventions every 5 minutes. Granted it’s gonna be out of our control, but hey, at least we’ll see a revolutionary breakthrough.
We may think that these claims are outlandish and ridiculous, but if someone were to tell me in the 70s that there will be self-driving cars in the future, I would’ve wanted to smoke whatever they were smoking.
But guess what, here we are in 2020, and Tesla already has their self-driving cars on the roads right now. And these were all recently developed technologies. Did you know that the first chatbot was actually launched in 1966?
#ai-chatbot #what-is-a-chatbot #chatbot-online #chatbot #chatbot-website #facebook-chatbot #google-chatbot #best-chatbot
Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.
Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is
Syntax: x = lambda arguments : expression
Now i will show you some python lambda function examples:
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