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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.

FDA limits use of Regeneron and Lilly COVID antibody treatments

A coldbox containing monoclonal antibody treatments at a Regeneron clinic in Pembroke Pines, Florida, in August. Photo: Eva Marie Uzcategui/Bloomberg via Getty Images

The FDA said Monday it's limiting the use of two monoclonal antibody therapies as COVID-19 treatments because data indicates they're "highly unlikely" to be effective against the dominant Omicron variant.

Driving the news: The FDA revised the authorizations for Regeneron and Eli Lilly "to limit their use to only when the patient is likely to have been infected with or exposed to a variant that is susceptible to these treatments," per a statement from the agency.

Updated 3 hours ago - World

Pentagon: 8,500 troops on high alert for possible deployment to eastern Europe

Photo: Anna Moneymaker/Getty Images

Defense Secretary Lloyd Austin has placed 8,500 U.S. troops on "heightened preparedness to deploy" to eastern Europe in case NATO activates its rapid-response force over tensions with Russia, the Pentagon announced Monday.

Why it matters: No decisions have been made to actually deploy U.S. forces, but the heightened alert level will allow the military to rapidly shore up NATO's eastern flank in the event that Russia invades Ukraine. The Pentagon warned that Russia has shown "no signs of de-escalating," and continues to amass troops on Ukraine's borders.