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Illustration: Eniola Odetunde/Axios

A new general language machine learning model is pushing the boundaries of what AI can do.

Why it matters: OpenAI's GPT-3 system can reasonably make sense of and write human language. It's still a long way from genuine artificial intelligence, but it may be looked back on as the iPhone of AI, opening the door to countless commercial applications — both benign and potentially dangerous.

Driving the news: After announcing GPT-3 in a paper in May, OpenAI recently began offering a select group of people access to the system's API to help the nonprofit explore the AI's full capabilities.

  • The reaction from many who tried GPT-3 was nothing short of ecstatic. "Playing with GPT-3," tweeted developer Arram Sabeti, "feels like seeing the future."

How it works: GPT-3 works the same way as predecessors like OpenAI's GPT-2 and Google's BERT — analyzing huge swathes of the written internet and using that information to predict which words tend to follow after each other.

  • What sets GPT-3 apart is the vast amount of data it was trained on half a trillion words.
  • And the program has 175 billion parameters — the values an AI aims to optimize during training — which is 10 times more than its closest competitor.
  • The result is what Suraj Amonkar of the AI company Fractal Analytics calls "the best language model in the field of AI."

Details: As early testers begin posting about their experiments, what stands out is both GPT-3's range and the eerily human-like quality of some of its responses.

  • Want to write poetry like Walt Whitman? Prompt it with a few lines of "O Captain! My Captain!" and GPT-3 will fill out the rest, generating new poetry in the style of the Bard of Brooklyn.
  • Looking to write workable computer code? GPT-3 is your geek squad.
  • Care to engage in a philosophical debate about the nature of God with an AI? GPT-3 is the stoned freshman-year roommate you never had.

Yes, but: Give it more than a few paragraphs of text prompts and GPT-3 will quickly lose the thread of an argument — sometimes with unintentionally hilarious results, as Kevin Lacker showed when he gave GPT-3 the Turing Test.

  • GPT-3 can use its vast dataset to predict words, but as Amonkar notes, "It most probably does not even have any semantic understanding of the underlying words."

The big picture: Just because GPT-3 lacks real human intelligence doesn't mean that it lacks any intelligence at all, or that it can't be used to produce remarkable applications.

  • Technologist and entrepreneur Azeem Azhar argues that GPT-3 should be seen as a major step forward in knowledge manipulation. Unlike Google's search engine, which organizes the information of the web but still requires you to find the answer, GPT-3 aims to produce direct answers for a query, wrapped in a nice bow.
  • It's still far from perfect, but focusing on those imperfections risks missing GPT-3's true significance. "I'm pretty sure Gutenberg's first press wasn't as good as the modern press," says Azhar.
  • GPT-3 is a "contender for the most spectacularly newsworthy happening of 2020," economist Tyler Cowen writes for Bloomberg. He imagines how it could "generate an entire ecosystem" of spinoffs and services.

Of note: OpenAI has already begun partnering with commercial companies on GPT-3, including Replika and Reddit, though pricing is still undecided.

The catch: As OpenAI itself noted in the introductory paper, "internet-trained models have internet-scale biases." A model trained on the internet like GPT-3 will share the biases of the internet, including stereotypes around gender, race and religion.

  • A system that can generate near-human quality writing could easily be used for misinformation, phishing and other hacking efforts. And while malicious humans already do all of those things, GPT-3 could represent a step change, like going from a pistol to an AK-47.

The bottom line: Humans who assemble letters for a living aren't out of a job — yet. But we may look back upon GPT-3 as the moment when AI began seeping into everything we do.

Go deeper

Bryan Walsh, author of Future
Oct 28, 2020 - Technology

Inequality grows in AI research

Illustration: Aïda Amer/Axios

A new working paper finds that as high-level AI research began to require huge amounts of computing resources, large tech firms and elite universities increasingly dominated the field's most important conferences.

Why it matters: If only the most well-funded researchers are able to drive the direction of AI, the diversity of voices will narrow at the very moment when AI is poised to transform how we live and work.

Miriam Kramer, author of Space
22 mins ago - Science

NASA's Mars helicopter is a test for the future of space exploration

Ingenuity (left) with Perseverance on Mars. Photo: NASA/JPL-Caltech/MSSS

NASA is set to fly the first test flight of its tiny Ingenuity helicopter on Mars Sunday, marking the advent of drones for space exploration.

Why it matters: If successful, this flight will be the first time a human-built aircraft has flown on a world other than Earth, opening the door to new means of exploring planets far from our own.

Bryan Walsh, author of Future
1 hour ago - Politics & Policy

The global future is looking dark and stormy

Illustration: Rae Cook/Axios

A new 20-year-forecast for the world: increasingly fragmented and turbulent.

The big picture: A major report put out this week by the National Intelligence Council reflects a present rocked by the COVID-19 pandemic. How the next two decades will unfold depends largely on whether new technologies will ultimately unite us — or continue to divide us.