Commercial Applications of GPT-3

GPT-3 is a language model that uses deep learning to generate human-like text on demand.

GPT-3 is Open AI’s latest natural language prediction model. With the emergence of Artificial Intelligence (AI) in the business landscape, this is one of the tools that will quickly increase in popularity. The Generative Pre-trained Transformer 3 offers limitless access to computing on top of its cloud infrastructure, promoting scalability. Nevertheless, GPT-3 should be the next big thing in tech. Following the rise of deep learning, advanced technology will transform how business gets conducted globally.

What is GPT-3?

The Generative Pre-trained Transformer 3, also known as GPT-3, is developed by OpenAI, a San Francisco startup founded by Elon Musk. The GPT-3 is an extensive neural network formed from the deep learning segment of machine learning technology.

Machine learning is the extension of artificial intelligence (AI), which uses computer algorithms to automate specific actions.

The latest version of GPT offers advanced features that produce lines of text that come off as something created by humans. Imitating human-like actions, this provides a personalized approach to transactions and crucial business decisions.

As a result, a growing number of commercial industries found the potential of leveraging GPT-3 to automate mundane tasks. GPT-3 prompts a generated response to any text that the person enters into the computer. It creates a reaction following the information presented.

For instance, typing a string of statements into the search box can respond within the given statement’s context. GPT-3 has the potential to amplify human effort in a variety of situations. It can be applied in different business processes such as customer service, documentation, and producing various content.

Understanding GPT-3

GPT-3 (Generative Pre-trained Transformer 3) is a language model that was developed by the AI research laboratory OpenAI.

GPT-3 was launched in mid-2020 and returns natural language text completion for any text prompt such as a sentence or phrase. 

Note that the GPT-3 algorithms have been pre-trained. Each draws from around 570 GB of text-based information that was sourced from crawling the internet.

The model can generate text of up to 50,000 characters unsupervised and in addition to simple fact-based writing, can also produce code, stories, press releases, technical manuals, and even Shakespeare-esque content.

GPT-3 marks the first instance of a model that can produce text which is virtually indistinguishable from that produced by a person.

Just nine months after it was launched, more than 300 applications were already using GPT-3 to churn out 4.5 billion words per day

Considered the world’s most powerful language model with over 175 billion trainable machine learning parameters, it has been used in everything from creativity and games to education and productivity.

How does GPT-3 work?

Central to the functioning of GPT-3 are transformers which were released by Google researchers in 2017.

Transformers are machine learning models that are semi-supervised and primarily used with text data.

These models, which have replaced the role of neural networks in natural language processing, take input sequence data and then generate an output sequence one element at a time.

Take a transformer that translates a sentence from English to Spanish. The sentence is essentially treated as a sequence with the words in that sentence serving as its elements.

Transformers have two primary segments.

The first is an encoder that operates on the input sequence while the other segment, the decoder, operates on the output sequence during training and predicts what the next item will be.

Returning to our example, the transformer model may analyze the sequence of words in English and iteratively predict the next Spanish word until the sentence has been accurately translated.

For the sake of accuracy, the model works through the sentence one word at a time whilst respecting the grammar rules inherent to the Spanish language.

What makes GPT-3 special?

Parameters and data

The feature that stands out most about GPT-3 is the 175 billion trainable parameters. 

To put this number into perspective, consider that GPT-3 has ten times more parameters than any of its predecessors.

This necessitated that the model was trained with 45 TB of data from numerous sources which include books, web text, all outbound links from Reddit, and the entire Wikipedia content library.

While GPT-3 can perform reading and writing tasks at a level compared to humans, the real power of the model lies in the fact that it has “processed” more information than a person would ever be capable of reading in their lifetime.


The versatility of GPT-3 was touched on briefly in the previous section, but to explain this point further, we’d like to mention a blog post by artist Mario Klingemann who used GPT-3 to generate all kinds of interesting output. 

Content included songs about Harry Potter by Taylor Swift and Lil Wayne, a user manual for the flux capacitor from Back to the Future, and a post espousing the value of free speech and civility in a democratic society.

GPT-3 commercial applications

Here are a few recent commercial applications of GPT-3. is an AI software tool that automates customer support and sales conversations. It uses natural language processing (NLP) and machine learning (ML) to understand customer inquiries and provide accurate responses in real time. can be integrated with popular messaging and chat platforms such as Facebook Messenger, WhatsApp, and Slack, as well as with websites and mobile apps. It can also be customized to match the branding and tone of voice of the business it represents. is best suited to repetitive or common customer inquiries that free up human support staff to focus on those that are more complex or sensitive. The tool can also provide data insights to businesses on customer interactions, sentiment analysis, and performance metrics.

The company offers one plan that encompasses all its services, with prices based on the number of business locations the client wants to monitor. The cost for Replier’s Base Plan is $10 per location per month.

Features include:

  • Auto-generated review responses – the AI can output custom review responses for client use.
  • Reply analysis – the client can also analyze how their response rates improve over time and the impact it has on their business.
  • Marketing content – clients can generate marketing content for their reviews and share it on social media as part of brand promotion.
  • Support for over 20 languages – this includes English, Spanish, Portuguese, German, French, and Italian.
  • API integration, and
  • White labeling for agencies. is a software tool that utilizes AI to automate the process of A/B testing, a widely used method for increasing website and app performance. 

A/B testing involves comparing two versions of a web page or app to determine which performs better based on user behavior and engagement metrics.

This is how a company can run its first A/B test based on GPT-3:

  1. Create variations – to start, the user enters the URL and provides several variations of the title, copy, and CTA. The AI then recognizes these, suggests further variations, and will track any subsequent conversion events.
  2. Integrate – the user then adds a small JavaScript snippet to their site or installs a proprietary app for Wix or WordPress.
  3. Experiment – an experiment is then run with some of the variations using the multi-armed bandit approach. This is a classic ML technique that seeks to minimize the exploration/exploitation trade-off dilemma. As the experiment is conducted, the algorithm shows successful variations more often. 
  4. Find the best combination – when the experiment achieves statistical significance, the most successful variations are incorporated into a so-called “evolutionary” algorithm which mixes and mutates them before the next batch is run. This enables the algorithm to quickly find the best variation via refinement and avoids the need to separately test every possible combination.
  5. Repeat – the company then repeats the process with a new experiment until the combination yielding the highest conversion rate is discovered.

The company offers four plans based on the number of website visitors, experiments, and AI-generated variations. The $19 per month starter plan, for example, is suitable for up to 8,000 unique visitors and 30 AI-generated variations per month. 

For more trafficked websites, the business plan can accommodate up to 150,000 unique monthly visitors and comes with GA integration, premium support, API access, and a team-sharing feature.

Key takeaways:

  • GPT-3 is a language model that uses deep learning to generate human-like text on demand.
  • Central to the functioning of GPT-3 are transformers, which are machine learning models that are semi-supervised and primarily used with text data.
  • The ability of GPT-3 to produce text comparable to humans is impressive, but so too is the 45 TB of information the model can access. With access to so much information, the model can produce a diverse variety of texts such as poems, essays, songs, technical manuals, and music lyrics.

Interesting Ways GPT-3 Is Used in Commercial Applications

GPT-3 can help businesses accomplish mundane, repetitive tasks. For instance, developers can build a tool that generates various layouts for the design required in different situations. It can also simplify programming by translating natural language into SQL queries. Formulating complex spreadsheets, building complex CSS, or even deploying Amazon Web Services (AWS) instances, GPT-3 can get applied in almost any business process.

The novel applications mentioned above can automate simple tasks helping employees focus on value-adding projects.

However, the commercial applications that businesses can take advantage of using GPT-3 are even greater.

Let’s take a look at some of them below:

Automate Translation of Various Documents

The automated translation of large volumes of documents from various languages can bring many opportunities to businesses. Apart from streamlining the delivery of services, they can increase their capacity outside the country. GPT-3 can learn over 499 billion words of different languages to produce translations at a given time seamlessly.

As we all know, some statements can get lost in translation even when every word gets translated correctly. Each language has sayings and context that controls the conversation. With GPT-3, that context is taken into consideration to understand further what the statement means.

Priming AI to Deal with Data

One of the applications of GPT-3 that businesses find exceptionally fascinating is priming AI to respond to English inputs with structured data output like JSON or XML. Through this feature, developers can take advantage of its machine learning capabilities to comprehend the theorems and their underlying structure. While it can produce answers to mathematical questions with the highest accuracy, it also considers those values’ context. This consideration provides better results and can help the advancement of the research promptly.

Programming Without the Use of Code

Without the need for manual intervention, GPT-3 generates structured data for developing specialized programs and software. Eliminating the need for writing algorithms using traditional programming languages allows some developers to embrace natural languages. Adopting natural languages becomes vital to prime the AI. Although it does not require expert skills in coding, this opens up new opportunities needing unique skills to expand software development jobs.

Generate Automated Regex

Composed of a sequence of characters that define the search pattern, Regex is vital in creating string-searching algorithms. Through GPT-3, developers can acquire Regex for various use-cases. All you need to do is type the Regular expression that you wish to generate in plain English. You have to enter an example string to help GPT-3 develop relevant Regex in a matter of seconds.

Create a Clone of a Website

GPT-3 works with the UI and UX designer application called Figma to create clones of a website. Cloning websites is necessary to test the updates and the compatibility of certain features safely. This breakthrough in designing websites and generating robust tools can boost their functionalities. All you need to do is to input the URL of the website to produce its clone.

Produce Quizzes and Tests

Now that most of the classes became online, most teachers and students find it challenging to manage their time in the middle of the pandemic. A quiz generator powered by GPT-3 can ease their burden and also improve learning. It produces test questions of different topics and subject matter for students to answer. It also contains a thorough explanation of the answers to help students understand how they find the result.

Formulate Unique Animations

Among many other things you can create from GPT-3, production companies leverage this tool to automate animations. GPT-3 combined with a Figma plugin can produce frame-by-frame animations and a text prompt. It can also formulate 3D scenes with the help of the three.js Javascript API. All you need to do is enter the details of the location that you desire to create and take care of the rest.

Automate Documentation

Even though you don’t have prior accounting knowledge, it is possible to generate financial statements using GPT-3. This tool transforms natural language into Python code to automate balance sheets.

The Future of GPT-3

Everything that involves a particular language structure can get automated through GPT-3. From answering queries, producing content, summarizing a long string of texts, translating languages, to programming code, there are multiple ways for businesses to leverage this tool.

Overall, GPT-3 helps businesses get a few steps ahead into providing a future that makes business data and communication much more manageable. After all, communicating effectively is one of the best business tools, and GPT-3 makes that communication more accessible.

Read Next: History of OpenAI, AI Business Models, AI Economy.

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OpenAI Organizational Structure

OpenAI is an artificial intelligence research laboratory that transitioned into a for-profit organization in 2019. The corporate structure is organized around two entities: OpenAI, Inc., which is a single-member Delaware LLC controlled by OpenAI non-profit, And OpenAI LP, which is a capped, for-profit organization. The OpenAI LP is governed by the board of OpenAI, Inc (the foundation), which acts as a General Partner. At the same time, Limited Partners comprise employees of the LP, some of the board members, and other investors like Reid Hoffman’s charitable foundation, Khosla Ventures, and Microsoft, the leading investor in the LP.

OpenAI Business Model

OpenAI has built the foundational layer of the AI industry. With large generative models like GPT-3 and DALL-E, OpenAI offers API access to businesses that want to develop applications on top of its foundational models while being able to plug these models into their products and customize these models with proprietary data and additional AI features. On the other hand, OpenAI also released ChatGPT, developing around a freemium model. Microsoft also commercializes opener products through its commercial partnership.


OpenAI and Microsoft partnered up from a commercial standpoint. The history of the partnership started in 2016 and consolidated in 2019, with Microsoft investing a billion dollars into the partnership. It’s now taking a leap forward, with Microsoft in talks to put $10 billion into this partnership. Microsoft, through OpenAI, is developing its Azure AI Supercomputer while enhancing its Azure Enterprise Platform and integrating OpenAI’s models into its business and consumer products (GitHub, Office, Bing).

Stability AI Business Model

Stability AI is the entity behind Stable Diffusion. Stability makes money from our AI products and from providing AI consulting services to businesses. Stability AI monetizes Stable Diffusion via DreamStudio’s APIs. While it also releases it open-source for anyone to download and use. Stability AI also makes money via enterprise services, where its core development team offers the chance to enterprise customers to service, scale, and customize Stable Diffusion or other large generative models to their needs.

Stability AI Ecosystem


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