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Introduced in May of 2020, we’ve been waiting on edge for the release of GPT-3 for mass use. In the nearly ten months since its initial release, we are starting to see more startups with access to this groundbreaking technology. 

We’ve covered natural language processing through our BERT series, so it’s all-the-more fitting that we tap into GPT-3. Who knows, maybe this will be part of our AI-writing series.

But for now, here’s the low-down on GPT-3 and when we expect it’ll be ready for mass use. 

What is GPT-3?

According to the MIT Technology Review, GPT-3 is a powerful language model and one of the largest artificial neural networks ever created.

Believed to be one of the most revolutionary forms of AI, GPT-3 stands for Generative Pretrained Transformer 3 and is OpenAI’s unreleased, third-generation language generator. 

All in all, GPT-3 is a fancy name for a machine-learning algorithm that can read data and spit out text that sounds like a human wrote it! From the perspective of content marketing, it’s fascinating, and we expect to see the GPT-3 algorithm soon implemented for private use. 

What’s significant about GPT-3 is its ability to combine data learning processes and machine learning processes. AI data learning is helpful in business automation and things like search engine optimization (SEO). We also see machine learning applications in the most recent BERT update, Google’s search engine algorithm. 

GPT-3 is offering a unique combination of both those tools for a very distinct purpose.

How Does it Work?

The machine learning algorithm behind GPT-3 was fed approximately 570GB of text crawled from the internet (explicitly using Wikipedia, random sources selected by OpenAI, and text in the publicly available dataset CommonCrawl). By feeding GPT-3, the researchers at OpenAI trained it to learn the language structure. 

OpenAI’s GPT-3 is technically known as a language prediction model, which means that it can use text input and transform it into an appropriate and recognizable output that is in the language of the user. Since it capitalizes on the newest machine learning technology, the algorithm can learn the language within context and associate appropriate response styles. For example, if given a question, it knows that it needs to provide an answer in response. 

By reading hundreds of thousands of text options, GPT-3 can begin to differentiate between memos, long texts, essays, and translations, and then it can create something for you. If you give GPT-3 a prompt, the algorithm might come back with an answer. 

It has shown that it can write essays, summarize long texts, and even write computer code. In this video, GPT-3 is given the prompt to build a photo app, and, well, GPT-3 is successful.

The Potential of GPT-3

Now, for us is in the content marketing industry, we have been told that GPT-3 can virtually replace human writers and change content production. 


However, upon examining the potentials of GPT-3, it’s clear that this technology is much bigger than something designed to shake up content marketing. 

The implementation of GPT-3 for common use will change how we interact with each other and with technology, and it is destined to shake up more than digital marketing. Much like how programming frameworks made designing, testing, and modding software code much more manageable, so will GPT-3 make creating written text and solving complex problems far easier. 

We see the potential of GPT-3 in several ways:

  • Automation in AI SEO services
  • Providing concise summaries of complex problems for educating mass audiences
  • Automation in business (such as in memo writing)
  • The dynamics between AI writing and human writing will change, and most likely far more drastically in the publishing industry
  • Increasing the feasibility of automation for grammar checks, fact-checking, basic word processing features, basic administrative tasks, mundane tasks, and minimizing human error in basic tasks

It’s also important to step away from the narrative that GPT-3 will replace writing altogether. In the first place, it’s doubtful that we will have access to this technology in its full capacity any time soon or for an affordable price. It will be useful for creating content in the same way that social media marketing has evolved. Social media marketing is predicated on scheduling tools, fake social media personas, and editing tools. 

So, when you come across a marketed social media page and a real one, well, it’s still kind of obvious. Sure, we should see more GPT-3 writing in terms of content marketing for blogs and copy. But it’ll be more useful in technical writing, whitepapers, press releases, and perhaps academic writing (for example, summarizing literature reviews). 

It will still be implemented in content marketing, but good content marketers will be able to tell the difference between machine-written and human. This is because the machine-written text will still lack colloquial language, personality, character, expert insights, and the ability to make inferences. It will be more focused on regurgitation and related language than creating new knowledge. Therefore, companies who want to fill their page with SEO-related key terms may eventually get pegged for having too much machine-written content as it does not provide the value readers are looking for. 

Remember, there will still need to be human input to edit the work as well. Much like how people thought that the advent of the digital space will eliminate snail mail or the publishing industry, we’re, in fact seeing the opposite, and instead, analog communication channels are supporting digital ones. The same will go for GPT-3. Human forms of communication will need to support the AI ones. 

When Will GPT-3 Be Ready For Mass Use, If Ever?

So when will GPT-3 be ready for mass use? And will it ever? 

Since no one outside of OpenAI’s bubble really knows this question, what we can give you is a guess: GPT-3 will absolutely be available to mass use because Elon Musk is behind the project, and Musk has always been a proponent of putting outstanding technology in the hands of regular people (like he did with Starlink). 

It will most likely be scaled down based on, honest to goodness, tier pricing, but it will be available. There are doubts that it will be available for content marketing agencies like okwrite to get their hands on it this year; however, with partner connections, there is the chance that AI content optimization companies like MarketMuse will begin to roll out their version of the product. So expect to see a rise in GPT-3 related technology provided through partners.

If released open-source, AI optimization tools like MarketMuse’s Final Draft might also be able to improve their functionality, therefore offering benefits to more companies without having to shift completely to the GPT-3 model. 


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