Click on the arrow above to listen to this article By Dr. Patrice Caire In June of 2020, the US research lab OpenAI, which is backed up by Elon Musk, among others, launched its breakthrough language model: GPT-3—Generative Pre-trained Transformer 3. Why was it such a big event? Because GPT-3 may just change the way we work: we’re talking about a tool that can summarize mails and news articles, generate tweets and create chatbots, and yes…translate language. GPT-3 versus Other Language-prediction Programs As a language-prediction program created with neural networks, GPT-3 is by far the most powerful language model ever created. It is an artificial-intelligence system trained on a gigantic corpus of text: thousands of digital books, the entire Wikipedia, and roughly a trillion words from blogs, social media, and the internet at large. Given enough text—and enough processing—the machine learns probabilistic connections between words. In a nutshell: GPT-3 can read and write. In fact, GPT-3 can process text far better than its predecessor, GPT-2 (2019). GPT-3 is also distinguished by its sheer size: it boasts 100+ times more parameters than its previous version. GPT-3 uses 175 billion parameters, compared with the 17 billion of its closest competitor, Microsoft’s Turing NLG—making it the largest neural-network ever built. GPT-3: The Power and the Glory Get this: GPT-3 can correct English. It can write poetry. It can write like Faulkner, Proust, or Goethe. Any author you “feed” it—really. Even more relevant to our industry, GPT-3 can also: translate legal text into plain language—and generate legal text from simple “instructions”; write the code to create a website, based on your directions; generate well-formatted charts and infographics—from your summary; and fill in the missing parts of a spreadsheet, by computing formula on its own. What We Love about GPT-3 First, using easily understood natural language, GPT-3 can answer questions on any topic, while retaining the context of previously-asked questions. GPT-3 can also translate from spoken languages and programming languages—Python, JavaScript, and CSS (very useful for websites!), for example. GPT-3 can also generate questions and answers for UX, due diligence document search, and report generation. GPT-3: Dealbreakers At first, GPT-3’s generated text can be impressive. But longer texts tend to dissolve into meaninglessness. Another problem: like many chatbots, for example, the program amplifies biases inherent in the data—including racism and sexism. Then there’s the ginormous amount of processing power that GPT-3 sucks up: the program is miles more “compute-hungry” than even bitcoin. Finally, there’s cost: conservative estimates place a GPT-3 training run at a staggering $4.6 million—well beyond the reach of most companies. GPT-3 and You Right now, GPT-3 isn’t ready to replace the leading conversational interfaces on the market—Amazon’s Echo and Apple’s Siri, for example—but it can be used as a powerful tool to improve them. For now, GPT-3 is a crucial steppingstone to building language models of the future. So, How Can GPT-3 Be Used Effectively? It’s unclear. After all, if GPT-3 is eventually shown to generate the right text only half of the time, will it satisfy professionals? Be of use as more than a steppingstone? Let’s see!