Zuckerberg Under Fire After Ex-Employee Warns of Looming Meta Losses

Yann LeCun, Meta’s longtime chief artificial intelligence scientist, said last November that he planned to leave the company after more than a decade.

LeCun joined Meta in 2013, when the company prioritized open-ended research over rapid product launches. (Photo: Yann LeCun Facebook) 

In later interviews, including one referenced by Futurism, he openly criticized Meta’s approach to AI and the direction the company was taking, Nicole Westhoff reported for The Cool Down.

LeCun joined Meta in 2013, when the company prioritized open-ended research over rapid product launches.

For years, he had unusual freedom to explore ideas without pressure to turn them into revenue.

As he later told the Financial Times, “Money was clearly not going to be a problem.”

That changed after the release of ChatGPT in late 2022. The surge in competition pushed Meta — along with Google and OpenAI — toward faster development, tighter secrecy and large-scale commercial deployment.

LeCun has warned that this shift favors speed over caution, increasing the risk of unreliable systems, misuse, and unintended consequences.

While much of the debate around AI focuses on ethics and jobs, LeCun’s exit also highlights something more tangible: AI’s growing physical footprint.

Tech companies use enormous amounts of electricity and water to train and operate large models.

That demand often concentrates in data centers drawing power from local grids, creating added strain that can ripple out to nearby communities through higher costs or infrastructure pressure.

At the same time, AI can help energy systems operate more efficiently, such as by analyzing long-term weather patterns to improve solar-output forecasting and reduce waste.

Whether AI becomes a burden or a benefit depends less on the technology itself and more on how deliberately companies choose to deploy it.