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Illustration: Eniola Odetunde/Axios

Microsoft announced a deal Tuesday that will give it the exclusive license to OpenAI's GPT-3 language model, a tool that uses machine learning to generate remarkably human sounding text.

Why it matters: The deal provides a way for many companies to have access to the technology while seemingly allowing Microsoft to establish guardrails and parameters for how the technology can be used.

The big picture: GPT-3, which was trained on half a trillion words to optimize for a staggering 175 billion parameters, has generated all kinds of buzz in recent months, with MIT Technology Review declaring it "shockingly good."

Between the lines: While the algorithm doesn't actually "know" much of anything as factual, it's capable of writing surprisingly clearly text on just about anything, by analyzing huge swathes of the written internet and using that information to predict which words tend to follow after each other.

Flashback: Microsoft said in May it was building a supercomputer within its Azure cloud specifically for OpenAI and has also invested $1 billion in the San Francisco-based company.

Go deeper: Meet the AI that can write

Go deeper

The Microsoft case's long shadow over Google

Illustration: Sarah Grillo/Axios

Microsoft's epic battle with the U.S. government from 1997-2002, the last major federal antitrust action in tech, casts a long shadow over today's Department of Justice lawsuit against Google — but the industry landscape today is profoundly different.

The big picture: Microsoft's legal ordeal came at a moment when its old competitors, like Apple, were on the ropes, and new competitors, like Google, were just launching. The antitrust case preoccupied Bill Gates and the rest of Microsoft's leadership for years and arguably gave all those competitors the breathing room to grow toward their current success.

Oct 20, 2020 - Technology

When robots are recruiters

Illustration: Sarah Grillo/Axios

One of the fastest-growing workplace applications of artificial intelligence is in hiring, but imperfect algorithms leave qualified women and candidates of color out — and can ultimately build weaker teams.

Why it matters: Algorithms are most often used to make the initial applicant screening process — the resume review — more efficient. But their role cannot be underestimated, as around 95% of all job applicants are rejected based on resumes.

The hard math behind America's labor shortage

Data: Bureau of Labor Statistics, Congressional Budget Office; Chart: Axios Visuals

Yes, the pandemic has created unusual temporary labor market dynamics. But in the bigger picture, the 2010s were a golden age for companies seeking cheap labor. The 2020s are not.

The big picture: In the 2010s, the massive millennial generation was entering the workforce, the massive baby bo0m generation was still hard at work, and there was a multi-year hangover from the deep recession caused by the global financial crisis.