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4 ways startups will drive GPT-3 adoption in 2021

The introduction of GPT-3 in 2020 was a tipping point for artificial intelligence. In 2021, this technology will power the launch of a thousand new startups and applications. GPT-3 and similar models have brought the power of AI into the hands of those looking to experiment — and the results have been extraordinary.

Trained on trillions of words, GPT-3 is a 175-billion parameter transformer model — the third of such models released by OpenAI. GPT-3 is remarkable in its ability to generate human-like text and responses — in some respects, it’s eerie. When prompted by a user with text, GPT-3 can return coherent and topical emails, tweets, trivia and much more.

In 2021, this technology will power the launch of a thousand new startups and applications.

Suddenly, authoring emails, customer interactions, social media exchanges and even news stories can be automated — at least in part. While large companies are pondering the pitfalls and risks of generating text (remember Microsoft’s disastrous Tay bot?), startups have already begun sweeping in with novel applications — and they will continue to lead the charge in transformer-based innovation.

OpenAI researchers first released the paper introducing GPT-3 in May 2020, and what started out as some nifty use cases on Twitter has quickly become a hotbed of startup activity. Companies have been formed on top of GPT-3, using the model to generate emails and marketing copy, to create an interactive nutrition tracker or chatbot, and more. Let OthersideAI take a first pass at writing your emails, or try out Broca or Snazzy for your ad copy and campaign content, for instance.

Other young companies are harnessing the API to accelerate their existing efforts, augmenting their technical teams’ capabilities with the power of 175 billion parameters and quickly bringing otherwise difficult products to market with much greater speed and data than previously possible. With some clever prompt engineering (a combination of an instruction to the model with a sample output to help guide the model), these companies leverage the underlying GPT-3 system to improve or extend an existing application’s capabilities.

Sure, a text expander can be a useful tool for shorthand notation — but powered by GPT-3, that shorthand can be transformed into a product that generates contextually aware emails in your own style of writing.

As early-stage technology investors, we are inspired to see AI broadly, and natural language processing specifically, become more accessible via the next generation of large-scale transformer models like GPT-3. We expect they will unlock new use cases and capabilities we have yet to even contemplate.

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