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“Over 80 technical papers published since January 2022,” LeCun responded. “What about you?”

To which Musk posted: “That’s nothing, you’re going soft. Try harder!

At stake are the hearts and minds of AI experts—academic and otherwise—needed to usher in the technology

“Join xAI,” LeCun wrote, “if you can stand a boss who:– claims that what you are working on will be solved next year (no pressure).– claims that what you are working on will kill everyone and must be stopped or paused (yay, vacation for 6 months!).– claims to want a ‘maximally rigorous pursuit of the truth’ but spews crazy-ass conspiracy theories on his own social platform.”

Some read Musk’s “science” dig as dismissing the role research has played for a generation of AI experts. For years, the Metas and Googles of the world have hired the top minds in AI from universities, indulging their desires to keep a foot in both worlds by allowing them to release their research publicly, while also trying to deploy products. 

For an academic such as LeCun, published research, whether peer-reviewed or not, allowed ideas to flourish and reputations to be built, which in turn helped build stars in the system.

LeCun has been at Meta since 2013 while serving as an NYU professor since 2003. His tweets suggest he subscribes to the philosophy that one’s work needs to be published—put through the rigors of being shown to be correct and reproducible—to really be considered science. 

“If you do research and don’t publish, it’s not Science,” he posted in a lengthy tweet Tuesday rebutting Musk. “If you never published your research but somehow developed it into a product, you might die rich,” he concluded. “But you’ll still be a bit bitter and largely forgotten.” 

After pushback, he later clarified in another post: “What I *AM* saying is that science progresses through the collision of ideas, verification, analysis, reproduction, and improvements. If you don’t publish your research *in some way* your research will likely have no impact.”

The spat inspired debate throughout the scientific community. “What is science?” Nature, a scientific journal, asked in a headline about the dust-up.

Others, such as Palmer Luckey, a former Facebook executive and founder of Anduril Industries, a defense startup, took issue with LeCun’s definition of science. “The extreme arrogance and elitism is what people have a problem with,” he tweeted.

For Musk, who prides himself on his physics-based viewpoint and likes to tout how he once aspired to work at a particle accelerator in pursuit of the universe’s big questions, LeCun’s definition of science might sound too ivory-tower. 

Musk has blamed universities for helping promote what he sees as overly liberal thinking and other symptoms of what he calls the Woke Mind Virus. 

Over the years, an appeal of working for Musk has been the impression that his companies move quickly, filled with engineers attracted to tackling hard problems and seeing their ideas put into practice.

“I’ve teamed up with Elon to see if we can actually apply these new technologies to really make a dent in our understanding of the universe,” Igor Babuschkin, an AI expert who worked at OpenAI and Google’s DeepMind, said last year as part of announcing xAI’s mission. 

The creation of xAI quickly sent ripples through the AI labor market, with one rival complaining it was hard to compete for potential candidates attracted to Musk and his reputation for creating value

that was before xAI’s latest round raised billions of dollars, putting its valuation at $24 billion, kicking off a new recruiting drive. 

It was already a seller’s market for AI talent, with estimates that there might be only a couple hundred people out there qualified to deal with certain pressing challenges in the industry and that top candidates can easily earn compensation packages worth $1 million or more

Since the launch, Musk has been quick to criticize competitors for what he perceived as liberal biases in rival AI chatbots. His pitch of xAI being the anti-woke bastion seems to have worked to attract some like-minded engineers.

As for Musk’s final response to LeCun’s defense of research, he posted a meme featuring Pepé Le Pew that read: “my honest reaction.”

A closer look, however, would have revealed that individual journalists at BNN published lengthy stories as often as multiple times a minute, writing in generic prose familiar to anyone who has tinkered with the A.I. chatbot ChatGPT.

How easily the site and its mistakes entered the ecosystem for legitimate news highlights a growing concern: A.I.-generated content is upending, and often poisoning, the online information supply.

The websites, which seem to operate with little to no human supervision, often have generic names — such as iBusiness Day and Ireland Top News — that are modeled after actual news outlets. They crank out material in more than a dozen languages, much of which is not clearly disclosed as being artificially generated, but could easily be mistaken as being created by human writers.

Now, experts say, A.I. could turbocharge the threat, easily ripping off the work of journalists and enabling error-ridden counterfeits to circulate even more widely — as has already happened with travel guidebooks, celebrity biographies and obituaries.

The result is a machine-powered ouroboros that could squeeze out sustainable, trustworthy journalism. Even though A.I.-generated stories are often poorly constructed, they can still outrank their source material on search engines and social platforms, which often use A.I. to help position content. The artificially elevated stories can then divert advertising spending, which is increasingly assigned by automated auctions without human oversight.

NewsGuard, a company that monitors online misinformation, identified more than 800 websites that use A.I. to produce unreliable news content.

Low-paid freelancers and algorithms have churned out much of the faux-news content, prizing speed and volume over accuracy.

Former employees said they thought they were joining a legitimate news operation; one had mistaken it for BNN Bloomberg, a Canadian business news channel. BNN’s website insisted that “accuracy is nonnegotiable” and that “every piece of information underwent rigorous checks, ensuring our news remains an undeniable source of truth.”

this was not a traditional journalism outlet. While the journalists could occasionally report and write original articles, they were asked to primarily use a generative A.I. tool to compose stories, said Ms. Chakraborty and Hemin Bakir, a journalist based in Iraq who worked for BNN for almost a year. They said they had uploaded articles from other news outlets to the generative A.I. tool to create paraphrased versions for BNN to publish.

Mr. Chahal’s evangelism carried weight with his employees because of his wealth and seemingly impressive track record, they said. Born in India and raised in Northern California, Mr. Chahal made millions in the online advertising business in the early 2000s and wrote a how-to book about his rags-to-riches story that landed him an interview with Oprah Winfrey.

Mr. Chahal told Mr. Bakir to focus on checking stories that had a significant number of readers, such as those republished by MSN.com.Employees did not want their bylines on stories generated purely by A.I., but Mr. Chahal insisted on this. Soon, the tool randomly assigned their names to stories.

This crossed a line for some BNN employees, according to screenshots of WhatsApp conversations reviewed by The Times, in which they told Mr. Chahal that they were receiving complaints about stories they didn’t realize had been published under their names.

According to three journalists who worked at BNN and screenshots of WhatsApp conversations reviewed by The Times, Mr. Chahal regularly directed profanities at employees and called them idiots and morons. When employees said purely A.I.-generated news, such as the Fanning story, should be published under the generic “BNN Newsroom” byline, Mr. Chahal was dismissive.“When I do this, I won’t have a need for any of you,” he wrote on WhatsApp.Mr. Bakir replied to Mr. Chahal that assigning journalists’ bylines to A.I.-generated stories was putting their integrity and careers in “jeopardy.”

This was a strategy that Mr. Chahal favored, according to former BNN employees. He used his news service to exercise grudges, publishing slanted stories about a politician from San Francisco he disliked, Wikipedia after it published a negative entry about BNN Breaking and Elon Musk after accounts belonging to Mr. Chahal, his wife and his companies were suspended o

The increasing popularity of programmatic advertising — which uses algorithms to automatically place ads across the internet — allows A.I.-powered news sites to generate revenue by mass-producing low-quality clickbait content

Experts are nervous about how A.I.-fueled news could overwhelm accurate reporting with a deluge of junk content distorted by machine-powered repetition. A particular worry is that A.I. aggregators could chip away even further at the viability of local journalism, siphoning away its revenue and damaging its credibility by contaminating the information ecosystem.