How to navigate today’s generative landscape of text and conversational AI

OpenAI’s revolutionary ChatGPT chatbot has been all over the news in recent months, prompting tech giants like Google and Baidu to accelerate their AI roadmaps.

ChatGPT is based on the OpenAI GPT language model and provides a variety of features such as participating in conversations, answering questions, generating typed text, debugging code, performing sentiment analysis, translating languages, and much more.

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

How should business leaders react to this? We thought that by looking under the hood of ChatGPT and breaking the app down to its individual capabilities, we could demystify the product and allow any sufficiently innovative company to identify the most appropriate elements for its strategic relevance. This is how this analysis and research was born.

We looked at the various roles that ChatGPT provided and created an industry landscape map of companies that serve one or more of these roles. You can think of this as dissecting ChatGPT into its various anatomical parts and finding possible alternatives for each feature with its own unique and specific capabilities. The resulting text conversational and generative AI landscape is shown below and consists of ten functional categories with a sample of representative companies for each category.

Breaking down the text conversational and generative AI landscape

Generative AI is an increasingly popular term with ChatGPT. It refers to artificial intelligence technology that can create original content such as text, image, video, audio, and code. Our overview focuses on the area of ​​text generative AI because that is the predominant feature of ChatGPT.

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

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

Text summarization companies use AI to summarize written text into extracts 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 picture, we’ve grouped the categories of virtual assistants, chatbot building platforms, chatbot frameworks, and NLP engines into the general category of conversational AI. This encompasses technologies that interact with people through human-like written and verbal communication.

Virtual assistant software is responsive 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 core components of NLP. Companies in this category include Cognigy, Yellow AI, and Kore AI.

To the right of the landscape, we have the categories of writers, coders, and search. Writers use AI to create original written content and edit existing written content to improve 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 comprises AI-based 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

• Text summary: These companies use AI to identify the most important information from long texts and summarize them in short, digestible extracts. 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 the 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-enabled assistants that help the user with a variety of 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 create and deploy chatbots without the need to write code. They usually include a visual builder to designate 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 component of natural language processing that converts human language into machine input.
• Writers: These companies use AI to generate written text for 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 your code edits.
• Look for: These companies use AI to search the web for answers to general knowledge questions, as well as companies creating custom search solutions for a company’s own internal knowledge base.
• Language models: These models learn from a large number of human written and spoken texts, and predict the probability of the next word in a specified sequence of words. They form the building blocks of NLP used for text conversational and generative AI.

Big picture, evolving challenges

As you can see, the landscape of features similar to ChatGPT is vast, with a growing number of companies competing in each feature. This infographic shows just a fraction of the 700+ companies we’ve discovered in the space, with more products and companies launching daily. Like other major technological shifts we’ve seen with the internet, mobile devices, and more recently cryptocurrency, this early spring tide of market buildup is an explosion of activity that will continue to accelerate before shaking off and consolidating for years to come. coming.

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

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

Dong Liu and Nader Ghaffari are co-founders of sunrise prospects.

A special thanks to Arte Merritt for her review and comments.