ChatGPT, Bard, and other AI showcases: how Conversational AI platforms have adopted new technologies

calendar Updated July 08, 2024
Maryna Bilan
Former Marketing Manager
ChatGPT, Bard, and other AI showcases: how Conversational AI platforms have adopted new technologies

On November 30, 2022, OpenAI, a San Francisco-based AI research and deployment firm, introduced ChatGPT as a research preview. Within just five days of its launch, ChatGPT achieved the remarkable feat of attracting 1 million users, which was confirmed by OpenAI’s founder, Sam Altman, via Twitter. OpenAI’s success and increasing value can be partly attributed to its partnership with Microsoft. The tech giant invested $1 billion in the company in 2019, and has plans to invest another $10 billion in the nearest future.

The technology behind ChatGPT isn’t new and is called Generative AI, but with the success of the chatbot, it has attracted even more attention. Generative AI is a branch of AI that generates various types of data such as audio, images, text, code, and more, using existing data as inspiration and creating new outputs.

ChatGPT, the latest language model from the GPT-3 series, has set new standards in the AI industry. Using only 570 GB of textual data from the web, it has trained a large comprehensive language model that represents a significant advancement in the field. ChatGPT is considered to be the largest language model ever created, with 175 billion ML parameters.

OpenAI made the API of GPT-3 available to the public on November 18, 2021, so every business has had an opportunity to use this technology and integrate this Generative AI Solutions. However, it was only after the launch of the ChatGPT showcase and everyone’s testing and trying their own use cases within it, that the world started to hear about OpenAI`s technology.

Benefits of integrating ChatGPT technologies with Conversational AI platforms or service providers

What does ChatGPT and this Generative AI technology mean for Conversational AI platforms or service providers? Is it a new market competitor, substitutor, or maybe assistant? We decided to ask ChatGPT what its own thoughts on that are.

How GPT-3 technology can help Conversational AI platforms?
How GPT-3 technology can help Conversational AI platforms?

To summarize, GPT-3 technology can enhance the functionality of Conversational AI platforms and provide:

The integration of ChatGPT itself into a conversational AI platform can significantly improve its accuracy, fluency, versatility, and user experience. To enable all the range of benefits of ChatGPT for Conversational AI platforms, providers need to integrate the technology via API, which is not available as an open source solution, but companies could submit a request using OpenAI API Waitlist, yet API for GPT-3 technology itself is available via the link.

Check out the extended Comparison of Conversational AI vs. Generative AI.

What Conversational AI platform has already adopted ChatGPT-inspired technology

According to ChatGPT’s answer, OpenAI’s GPT (Generative Pretrained Transformer) technology, of which ChatGPT is a variant, has been adopted by several conversational AI platforms. Some notable examples include:

  • Replika AI: A personal AI companion that learns to communicate with its user.
  • Haptik: A conversational AI platform for customer service and engagement.
  • Virtual Personnel: A virtual customer service agent powered by AI.
  • BotStar: A conversational AI platform for businesses to build and deploy AI-powered chatbots.
  • Botpress: An open-source conversational AI platform for building and deploying bots.

These are just a few examples of using the technology that stands behind ChatGPT, and it`s popularity in the Conversational AI market is growing rapidly as more companies recognize the benefits it can bring to their platforms.

Intercom, an Irish customer service platform, has integrated OpenAI’s GPT-3.5 technology (which was the basis for ChatGPT) into its Inbox and Articles products. Currently, 100 customers are testing the new features within the limited Beta versions. The new features include ‘Composer AI’ which helps support agents write customer responses, ‘Conversation summarization’ which summarizes customer conversations for efficient handover between agents, and ‘Article generator AI’ that generates a full article version from a summary provided by the authors. The company plans to make these features more widely available this year, marking a significant advancement in the use of conversation intelligence in customer service and content generation.

Kore.AI, a leading Conversational AI platform for optimized customer and employee experiences, has provided a comprehensive answer on how technology utilized in the ChatGPT bot Compliment Conversational AI Platforms. Features such as automatic intent recognition, and slot and entity identification are integrated with models like Open AI to provide advanced capabilities such as automatic answers to FAQs, improved human-bot interactions, and faster dialog development. In addition, large language models (LLMs) can be used by Conversational AI Platforms to generate initial GPT prompts, messages, and sample conversations, saving a significant amount of time and providing an excellent starting point for conversation designers to refine responses.

LivePerson also adds ChatGPT’s Generative AI model to the customer service bot platform. LivePerson plans to integrate LLMs into its Conversational Cloud platform. The generative AI will also be incorporated into the company’s Conversation Assist feature to keep the chatbots up-to-date. In addition, LivePerson will use generative AI in its behind-the-scenes tools to provide businesses with conversation summaries, form filling, and customer information updates during and after conversations with the chatbots. The collected data will help improve future AI systems.

Cognigy, a global leader in Conversational AI, went through all the stages of grief and evolved from denial to acceptance in a month, when in December they highlighted Showstoppers for a pureplay chatbot using generative AI, and then in January presented a product demo: with LLM-assisted bot building. Basically, the ideas behind Cognigy’s release is to assess the drawbacks of both Conversational AI and ChatGPT, and combine the most advantageous facets of the two.

That is why businesses are looking for ChatGPT alternatives, and here is the list of the most popular ones.

ChatGPT Conversational AI Alternatives businesses can elect

There exist several alternatives to ChatGPT Generative AI model in the Conversational AI industry that businesses can choose from. Some of the prominent ones include:

  • Google’s LaMDA (Language Model for Dialogue Applications), a large language model trained on a diverse range of internet text and capable of generating human-like responses to various types of questions and prompts.
  • Facebook’s Blender, a large-scale, multi-turn, multi-domain conversational AI model, pre-trained on a diverse range of internet text.
  • IBM Watson Assistant, a conversational AI platform that enables businesses to build conversational experiences for customers across any channel or device.
Top Generative AI model examples
Top Generative AI model examples

On February 6, 2023, Google unveiled the ChatGPT rival Bard – an experimental conversational AI service powered by LaMDA (Language Model for Dialogue Applications). What’s unique about this technology? Its approach is a bit different from the OpenAI since it is trained in dialogue data and focuses on three key parameters – Safety, Quality, and Groundedness. ChatGpt, however, is based on three models – code-DaVinci-002, text-DaVinci-002 (it was trained by humans who were checking, if the answer was correct), and an additional base model to understand codes. With a large number of parameters, LaMDA excels in generating responses based on freely accessible conversation data. It can handle various customer service and marketing automation tasks, and its future looks promising with the support of platforms like Amazon.

As of now, Google is concentrated on tuning its solution to provide secure service, and it has announced to start first real business testing in a month, so only after that we may have the opportunity to see real feedback from the enterprises. At the same time, companies are trying to evaluate new technologies and test their ability to level up their chatbots to Generative AI Chatbot with new, wider functionality.

We are already working on adding ChatGPT-like functionality to the existing bots of our clients. So, we do not need to throw away old flow-based bots and replace them with a new generating-AI base one. We can augment existing bots with the GPT-3 based flows on a custom fine-tuned GPT-3 model. This model can keep the focus on business-case-specific knowledge and not try to answer every question as generic ChatGPT does.

Gleb Dobzhanskiy,

VP of Engineering at Master of Code

Master of Code, as a Conversational AI solution provider and certified delivery partner of LivePerson, has extensive expertise integrating Conversational AI platforms with third-party systems to collect information about customers in order to provide a personalized omnichannel experience. OpenAI`s solution could be one of the systems, integrated into the conversational flow, starting with questions from the customer’s standpoint and ending with replies derived from Conversational AI. And here at Master of Code, we can share our expertise in Conversational AI development, building conversational solutions both voice and text within Conversation Design best practices, and integrating new technologies into the ready-made systems.

While working on each project, we collaborate with stakeholders to assess the feasibility of deploying Conversational AI solutions. This involves selecting the appropriate technology, determining the data sources and the necessary integrations, with the goal being delivering the best user experience. Undoubtedly, OpenAI`s or Google’s may be one of the technologies in this stack, since at the end of the day our main objective is to improve efficiency and address customer issues promptly and accurately.

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