Respond to prefers-color-scheme dark in app web views

Follow section front redirects in Spectrum

Enable NLP source in PCS for load testing

Switch off the News Alerts Survey Widget when we have enough responses

Poll to determine if new LUF updates are available

Allows the winning A/B test variant to be turned on without Spectrum deployment

Show infinite scrolling sections in Assembler MultiView

Show option for NLP article summaries in Action Bar

Show NLP summaries collection recirc on article pages

A general feature flag for Recipe Features that aren't yet released

Feature flag for media team features that aren't yet released

Use new Orca video player for preroll plugin in Spectrum

Show the snow tracker (instead of the heat tracker) on Spectrum

Defense think tank MITRE to build AI supercomputer with Nvidia 

After big weekend in Palm Beach, Trump returns to N.Y. courtroom

Improper ‘shadow’ ads thriving on Facebook during India’s election

Triumphal Putin is inaugurated for fifth term as Russian president 

Middle East conflict live updates: IDF takes control of Rafah border crossing; aid flow halted, official says

Eurovision 2024 is as garish and controversial as ever. Here’s what to know.

Miss Manners: Greeting a non-parent on Mother’s or Father’s Day 

Carolyn Hax: Husband admits to one-night stand, wants spouse to ‘let it go’

Ask Amy: I’ve lied about being a Vietnam War veteran for 50 years

Strangers help Sesame Street puppeteer after heirloom necklace was stolen

Teen grabs wheel when driver passes out and school bus veers into traffic

Cat climbed into Amazon return box, found alive 630 miles away

Baseball can crush rookies. Why hasn’t it crushed Trey Lipscomb?

Eddie Rosario and Co. lead the Nats to an MLB-best 12th comeback win

CJ Abrams keeps getting better. It’s time to think about an extension.

The next global crisis could come from the sun. We should prepare now.

Under Putin, a militarized new Russia rises to challenge U.S. and the West 

How did we end up with a Biden-Trump matchup again?

Book excerpt: The admiral who had a mental breakdown over Fat Leonard

A guide to the 2024 Alexandria Democratic primary election 

Kristi Noem’s increasingly bizarre Kim Jong Un story

Trump mocks Sen. Tester’s weight, hints at a Mont. campaign appearance

Read the Pulitzer Prize-winning ‘Annals of Autocracy’ editorial series

Russia is using toxic chemical weapons, wrecking a ban it helped create

Don’t be a jerk at the airport: A guide for headphones

The new cure-all for vacation excess: the IV drip 

You asked: Do I need a passport for my cruise?

President Joe Biden White House Cinco de Mayo Reception

Big Tech news and how to take control of your data and devices

See more coverage in your recommendations

Technology

Tips delivered to your inbox twice weekly

The Tech Friend newsletter

Business and Tech alerts

San Francisco Chronicle/Hearst Newspapers via Getty Images

Fei-Fei Li, the “godmother of artificial intelligence,” delivered an urgent plea to <a href="https://www.washingtonpost.com/elections/candidates/joe-biden-2024/" target="_blank" class="contextual_link">President Biden</a> in the glittering ballroom of San Francisco’s Fairmont Hotel in June.

The Stanford professor asked Biden to fund a national warehouse of computing power and data sets — part of a “moonshot investment” allowing the country’s top AI researchers to keep up with tech giants.

She elevated the ask Thursday at Biden’s State of the Union address, which Li attended as a guest of Rep. Anna G. Eshoo (D-Calif.) to promote a bill to fund a national AI repository.

Li is at the forefront of a growing chorus of academics, policymakers and former employees who argue that the sky-high cost of working with AI models is boxing researchers out of the field, compromising independent study of the burgeoning technology.

As such tech behemoths as Meta, Google and Microsoft funnel billions of dollars into AI, a massive resources gap is building with even the country’s richest universities. Meta aims to procure 350,000 of the <a href="https://www.washingtonpost.com/technology/2024/02/21/nvidia-stock-earnings-revenue-ai/" target=_blank>specialized computer chips</a> — called GPUs — that are essential to run the gargantuan calculations needed for AI models. In contrast, Stanford’s Natural Language Processing Group has 68 GPUs for all of its work.

To obtain the expensive computing power and data required to research AI systems, scholars frequently partner with tech employees. Meanwhile, tech firms’ eye-popping salaries are draining academia of star talent.

Big tech companies now dominate breakthroughs in the field. In 2022, the tech industry created 32 significant machine learning models, while academics produced three, a significant reversal from 2014, when the majority of AI breakthroughs originated in universities, according to a Stanford <a href="https://aiindex.stanford.edu/wp-content/uploads/2023/04/HAI_AI-Index-Report_2023.pdf" target=_blank>report</a>.

Researchers say this lopsided power dynamic is shaping the field in subtle ways, pushing AI scholars to tailor their research for commercial use. Last month, Meta CEO Mark Zuckerberg announced that the company’s independent AI research lab would move closer to its product team, ensuring “some level of alignment” between the groups, he said.

“The public sector is now significantly lagging in resources and talent compared to that of industry,” said Li, a former Google employee and the co-director of the Stanford Institute for Human-Centered AI. “This will have profound consequences because industry is focused on developing technology that is profit-driven, whereas public-sector AI goals are focused on creating public goods.”

Kori Suzuki

 This agency is tasked with keeping AI safe. Its offices are crumbling.

Some are pushing for new sources of funding. Li has been making the rounds in Washington, huddling with White House Office of Science and Technology Policy Director Arati Prabhakar, dining with the political press at a swanky seafood and steak restaurant and visiting Capitol Hill for meetings with lawmakers working on AI, including Sens. Martin Heinrich (D-N.M.), Mike Rounds (R-S.D.) and Todd Young (R-Ind.).

Large tech companies have contributed computing resources to the National AI Research Resource, the national warehouse project, including a $20 million donation in computing credits from Microsoft.

“We have long embraced the importance of sharing knowledge and compute resources with our colleagues within academia,” Microsoft Chief Scientific Officer Eric Horvitz said in a statement.

Policymakers are taking some steps to address the funding gaps. Last year, the National Science Foundation <a href="https://new.nsf.gov/news/nsf-announces-7-new-national-artificial" target=_blank>announced</a> a $140 million investment to launch seven university-led National AI Research Institutes to examine how AI could mitigate the effects of climate change and improve education, among other topics.

Eshoo said she hopes to pass the Create AI Act, which has bipartisan backing in the House and the Senate, by the end of the year, when she is scheduled to retire. The legislation “essentially democratizes AI,” Eshoo said.

But scholars say this infusion may not come quickly enough.

As Silicon Valley races to build chatbots and image generators, it is drawing would-be computer science professors with high salaries and the chance to work on interesting AI problems. Nearly 70 percent of people with PhDs in AI end up in private industry compared with 21 percent of graduates two decades ago, according to a <a href="https://ide.mit.edu/wp-content/uploads/2023/03/0303PolicyForum_Ai_FF-2.pdf" target=_blank>2023 report</a>.

Bloomberg

Amid explosive demand, America is running out of power

Big Tech’s AI boom has pushed the salaries for the best researchers to new heights. Median compensation packages for AI research scientists at Meta climbed from $256,000 in 2020 to $335,250 in 2023, according to <a href="http://levels.fyi/" target=_blank>Levels.fyi</a>, a salary-tracking website. True stars can attract even more cash: AI engineers with a PhD and several years of experience building AI models can command compensation as high as $20 million over four years, said Ali Ghodsi, who as CEO of AI start-up Databricks is regularly competing to hire AI talent.

“The compensation is through the roof. It’s ridiculous,” he said. “It’s not an uncommon number to hear, roughly.”

University academics often have little choice <a href="https://www.washingtonpost.com/technology/2023/12/06/academic-research-meta-google-university-influence/" target=_blank>but to work with industry researchers</a>, with the companies footing the bill for computing power and offering data. Nearly 40 percent of papers presented at leading AI conferences in 2020 had at least one tech employee author, according to the 2023 <a href="https://ide.mit.edu/wp-content/uploads/2023/03/0303PolicyForum_Ai_FF-2.pdf" target=_blank>report</a>. And industry grants often fund PhD students to perform research, said Mohamed Abdalla, a scientist at the Canada-based Institute for Better Health at Trillium Health Partners and incoming assistant professor at the University of Alberta, who has conducted research on the effect of industry on academics’ AI research.

“It was like a running joke that, like, everyone is getting hired by them,” Abdalla said. “And the people that were remaining, they were funded by them — so, in a way, hired by them.”

Google believes private companies and universities should work together to develop the science behind AI, said Jane Park, a spokesperson for the company. Google still routinely publishes its research publicly to benefit the broader AI community, Park said.

David Harris, a former research manager for Meta’s responsible AI team, said corporate labs may not censor the outcome of research but may influence which projects get tackled.

“Anytime you see a mix of authors who are employed by a company and authors who work at a university, you should really scrutinize the motives of the company for contributing to that work,” said Harris, who is now a chancellor’s public scholar at the University of California at Berkeley. “We used to look at people employed in academia to be neutral scholars, motivated only by the pursuit of truth and the interest of society.”

These fake images reveal how AI amplifies our worst stereotypes

Tech giants procure huge amounts of<a href="https://www.washingtonpost.com/technology/2023/09/30/anthropic-amazon-artificial-intelligence/" target=_blank> computing power </a>through data centers and have access to GPUs. These resources are expensive: A recent report from Stanford University researchers <a href="https://aiindex.stanford.edu/wp-content/uploads/2023/04/HAI_AI-Index-Report_2023.pdf" target=_blank>estimated </a>that Google DeepMind’s large language model, Chinchilla, cost $2.1 million to develop. More than 100 top artificial intelligence researchers on Tuesday <a href="https://www.washingtonpost.com/technology/2024/03/05/ai-research-letter-openai-meta-midjourney/" target=_blank>urged generative AI companies</a> to offer a legal and technical safe harbor to researchers so they can scrutinize their products without the fear that internet platforms will suspend their accounts or threaten legal action.

Joel Saget

The necessity for advanced computing power is likely to only grow as AI scientists crunch more data to improve the performance of their models, said Neil Thompson, director of the FutureTech research project at MIT’s Computer Science and Artificial Intelligence Laboratory, which studies progress in computing.

“To keep getting better, [what] you expect to need is more and more money, more and more computers, more and more data,” Thompson said. “What that’s going to mean is that people who do not have as much compute [and] who do not have as many resources are going to stop being able to participate.”

Tech companies, including Meta and Google, have historically run their AI research labs to resemble universities where scientists decide what projects to pursue to advance the state of research, according to people familiar with the subject who spoke on the condition of anonymity to discuss private company matters.

Those workers were largely isolated from teams focused on building products or generating revenue, the people said. They were judged on influential papers they published or notable breakthroughs — similar to metrics used for their university peers, the people said. Top AI Meta scientists Yann LeCun and Joelle Pineau hold dual appointments at New York University and McGill University, blurring the lines between industry and academia.

Top AI researchers say OpenAI, Meta and more hinder independent evaluations

In an increasingly<a href="https://www.washingtonpost.com/technology/2023/06/05/chatgpt-hidden-cost-gpu-compute/" target="_blank"> competitive market for generative AI products</a>, research freedom inside companies could wane. In April, Google announced it was merging two of its AI research groups — DeepMind, which it acquired in 2014, and the Brain team from Google Research — into one department called Google DeepMind. Last year, Google started to take more advantage of its own AI discoveries, sharing research papers only after the lab work had been turned into products, The Washington Post has <a href="https://www.washingtonpost.com/technology/2023/05/04/google-ai-stop-sharing-research/" target="_blank">reported</a>.

Meta has also reshuffled its research teams. The company placed its Fundamental AI Research team, known as FAIR, under the helm of its virtual-reality division, Reality Labs, in 2022 and last year reassigned some of the group’s researchers to a new generative AI product team. Last month, Zuckerberg told investors that FAIR would work “closer together” with the generative AI product team, arguing that while the two groups would still conduct research on “different time horizons,” it was helpful to the company “to have some level of alignment” between them.

“In a lot of tech companies right now, they hired research scientists that knew something about AI and maybe set certain expectations about how much freedom they would have to set their own schedule and set their own research agenda,” Harris said. “That’s changing, especially for the companies that are moving frantically right now to ship these products.”

A previous version of this article incorrectly said that Google acquired DeepMind in 2010. Google acquired the AI start-up in 2014. The article has been corrected.

Princeton University, BA in sociology

Naomi Nix is a staff writer for The Washington Post, covering Meta and other social media companies. Before joining The Post in 2022, she was a reporter for Bloomberg News and the Chicago Tribune.

Naomi Nix

Northwestern University, BS in journalism

Cat Zakrzewski is a national technology policy reporter, tracking global efforts to regulate the tech industry. She focuses on AI policy and the battles over free speech online.

Cat Zakrzewski

Carleton University, BA in Journalism and Global Politics

Gerrit De Vynck is a tech reporter for The Washington Post. He writes about Google, artificial intelligence and the algorithms that increasingly shape society. He previously covered tech for seven years at Bloomberg News.

Gerrit De Vynck

washpost

Silicon Valley is pricing academics out of AI research

the-washington-post

Fei-Fei Li, chief AI scientist for Google Cloud, speaks during the keynote address at the Google Cloud Next '17 conference at the Moscone Convention Center in San Francisco, Calif. on Wednesday, March 8, 2017

Contributor

San Francisco Chronicle via Getty Images

Help Desk

Artificial Intelligence

Internet Culture

Space

Tech Policy

Tech

prism://prism.query/two-sites,/technology,/politics/powerpost/the-technology-202?limit=20