People granted early access to OpenAI’s latest language model are raving about its way with words — and more.

What’s new: Beta testers of GPT-3 are showing off the model’s ability to write business memos, craft blogs, pen tweets, and even generate computer code. You can apply for access to the API via this link. A paid version is expected in about two months.

Demo explosion: Yaser Martinez Palenzuela, a data scientist at Deutsche Telekom, compiled a list of demos on Github. Here are a few of our favorites.

  • A venture capitalist at Founders Fund used the system to help write an investment memo and declared himself “truly amazed” by its output.
  • It composed a convincing blog post comparing itself to bitcoin, based only on a headline and one-sentence summary provided by an executive at Zeppelin Solutions, which provides blockchain technology.
  • Entrepreneur Sharif Shameem showed that the model, prompted by descriptions of website features, can generate working code.
  • Product designer Jordan Singer built a GPT-3 interface to a graphics program that renders code for plugins based on brief descriptions.
  • A student at Oregon State University asked the model a series of physics questions meant to test its ability to reason. It responded with many correct answers.

Hype alert: OpenAI often has been accused of exaggerating the capabilities of its new technologies. Initially it withheld GPT-2, saying the model was too dangerous to release, and it has threatened to cancel GPT-3 access for anyone who uses the tech maliciously. Yet the company itself warns against overhyping the new model. “It still has serious weaknesses and sometimes makes very silly mistakes,” OpenAI CEO Sam Altman wrote in a tweet.

Bigger is better: GPT-3 owes much of its performance to a gargantuan parameter count of 175 billion, which dwarfs GPT-2’s 1.5 billion and exceeds by an order of magnitude recent models from Google (11 billion) and Microsoft (17 billion).

Why it matters: Large language models based on the transformer architecture have made natural language processing one of the most exciting areas of machine learning. They’re also raising AI’s public profile. GPT-3 is quickly becoming the technology’s foremost spokesbot.

We’re thinking: Sometimes GPT-3 writes like a passable essayist, sometimes like an insightful poet. But after reading the fascinating AI Weirdness blog post in which author Janelle Shane gives the model a question-and-answer workout, it seems a lot like some public figures who pontificate confidently on topics they know little about.


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