How to Navigate the Current Landscape of Conversational AI and Text Generation

OpenAI’s revolutionary chatbot ChatGPT has been making headlines in recent months, prompting tech giants such as Google and Baidu to accelerate their AI roadmaps.

ChatGPT is built on OpenAI’s GPT language model and provides a variety of functions, such as engaging in conversations, answering questions, generating written text, debugging code, performing sentiment analysis, translating languages ​​and more.

Looking at the technologies of this moment in time, nothing seems to be as crucial to the future of humanity as Generative AI. The idea of ​​expanding the creation of intelligence through machines will touch everything around us, and the momentum in the AI ​​generative space created by the sudden rise of ChatGPT is inspiring.

How should business leaders react to this? We believed that by looking under the hood of ChatGPT and disassembling the application to its individual capabilities, we could demystify the product and allow any sufficiently innovative company to identify the most appropriate elements for their strategic relevance. Thus was born this analysis and this research.

We have analyzed the different functions that ChatGPT provided and created an industrial landscape map of companies that perform one or more of these functions. You can think of it as dissecting ChatGPT into its various anatomical parts and finding potential alternatives for each feature with its own unique and targeted capabilities. The generative and conversational AI landscape resulting from the text is shown below and consists of ten functional categories with a sample of representative companies for each category.

Breaking down the generative text and conversational AI landscape

Generative AI is a term that is gaining popularity with ChatGPT. It refers to AI technology that can create original content such as text, images, video, audio, and code. Our landscape focuses on the field of generative text AI as it is the predominant function of ChatGPT.

As you can see, language models are at the bottom of the landscape because they form the building blocks of natural language processing (NLP) used for all other functions. The sample language models shown here include OpenAI’s GPT, Google’s LaMDA, and BigScience’s BLOOM.

To the left of the landscape, we’ve grouped the categories of text summarization, sentiment analysis, and text translation into the overall category of text analytics, which refers to the process of using AI to analyze unstructured text data looking for patterns, ideas and intentions.

Text summarization companies use AI to summarize written texts into snippets of the most important points. Companies in this category include QuillBot, Upword, and spaCy. Sentiment analysis companies use AI to determine the emotions, opinions, and tones inherent in written texts. Companies in this category include MonkeyLearn, Repustate, and Cohere. Text translation companies use AI to translate written texts from one language to another. Companies in this category include ModernMT, TextUnited, and Phrase.

Human-like interaction; code, text and search capabilities

In the middle of the landscape, we have grouped the categories of virtual assistants, chatbot creation platforms, chatbot frameworks and NLP Engines in the global Conversational AI category. This encompasses technologies that interact with people using human-like written and verbal communication.

Virtual assistant software responds to human language and helps the user with a variety of tasks and queries. Companies in this category include Augment, Replika, and SoundHound. Chatbot building platforms allow non-technical users to build and deploy chatbots without writing code.

Companies in this category include Amelia, Avaamo, and Boost AI. Chatbot frameworks and NLP engines allow developers to create chatbots using code, and also build the basic components of NLP. Companies in this category include Cognigy, Yellow AI, and Kore AI.

To the right of the landscape, we have the Writers, Coders, and Research categories. Writers use AI to create original written content and edit existing written content for grammar and clarity. Companies in this category include Jasper, Writesonic, and Grammarly.

Coders use AI to generate code from natural language input and debug existing code. Companies in this category include Tabnine, Replit, and Mutable AI.

Finally, search includes AI-powered search engines for the entire web or for a company’s internal knowledge base. Companies in this category include Neeva, Perplexity AI, and You.com.

The ten categories

• Summary of text : These companies use AI to identify the most important information from long texts and summarize them into short, digestible snippets. Other functions of these companies include keyword extraction, text classification, and named entity recognition.
• Sentiment analysis: These companies use AI to determine the sentiment of text as positive, negative, or neural, as well as the tone, emotion, and intent behind the text. Sentiment analysis is often used to analyze customer feedback and brand attitudes.
• Text translation: These companies use AI to translate text from one language to another, primarily for written text but also for voice and video recordings.
• Virtual Assistants: These companies create voice or text-based assistants that help the user with various tasks such as taking notes, scheduling appointments, recommending products, and providing mental health therapy.
• Chatbot creation platforms: These companies provide an interface for non-technical users to build and deploy chatbots without having to write code. They usually include a visual constructor to denote the flow of interaction with the chatbot.
• Chatbot frameworks and NLP engines: These companies provide an environment for developers to build and deploy chatbots using code, as well as companies that create the core natural language processing component that converts human language into machine input.
• Writers: These companies use AI to generate written text on given topics such as essays, poems, blog posts, and sales copy. They also help edit and paraphrase written text for grammar, tone, clarity, and style.
• Encoders: These companies use AI to help developers generate code from natural language descriptions. They also help debug existing code and explain the reasoning behind their code changes.
• Research: These companies use AI to search the web for answers to general knowledge questions, as well as companies that create custom search solutions for a company’s own internal knowledge base.
• Language models: These models learn from an abundance of written and spoken human texts and predict the probability of the next word in a specific word sequence. They form the fundamental building blocks of NLP used for generative text and conversational AI.

A vast landscape, ever-changing challenges

As you can see, the landscape of functions similar to ChatGPT is vast, with an increasing number of companies competing in each function. This infographic shows just a fraction of the more than 700 companies we discovered in the space, with more products and companies launching daily. Similar to other major technology shifts we’ve seen with the internet, mobile, and more recently crypto, this spring wave of market development is a burst of activity that will continue to pick up speed before fading and to consolidate in the years to come.

The obvious challenge for business leaders in this phase of market evolution will be to navigate the landscape and identify the real signals. What are the opportunities that can accelerate their business, bring new value to their customers, or keep them competitive in a rapidly changing market?

Faced with the plethora of competing generative AI products, business leaders need clear criteria to weigh and select the right ones for their creative and intellectual workforce. It may turn out that a portfolio of solutions would work better, and the role of knowledge and creative workers evolves from creating original content to comparing, assembling and editing the best creative results from the multitude of tools of generative AI. One thing is sure; every business should have a generative AI plan.

Dong Liu and Nader Ghaffari are co-founders of Glimpse of dawn.

Special thanks to Arte Merritt for his review and comments.