CEO Says He Tried to Hire an AI Researcher from Meta and Was Told to 'Come Back to Me When You Have 10,000 H100 GPUs'


This article originally appeared on Business Insider.

Recruiting AI talent can be a tough feat for some companies.

Aravind Srinivas, the founder and CEO of Perplexity, an AI-powered question-and-answer engine, described his interaction with a job candidate that shows how hard it can be to hire people with generative AI skills.

“I tried to hire a very senior researcher from Meta, and you know what they said? Come back to me when you have 10,000 H100 GPUs,'” Srinivas said on a recent episode of the business advice podcast “Invest Like the Best.

H100 GPUs refer to Nvidia’s highly coveted graphic-processing units that tech giants like Meta, OpenAI, and Google use in their data centers to power and train their AI chatbots.

“That would cost billions and take five to 10 years to get from Nvidia,” Srinivas said.

Limited funds, combined with a chip shortage, means Perplexity, which powers its Q&A engine using GPT-4, has found it tough to find the talent required to create a large language model, Srinivas said.

Srinivas said it’s difficult to get employees to leave a company where they “have a great experimentation stack and existing models to bootstrap from.”

“You have to offer such amazing incentives and immediate availability of computing. And we’re not talking of small compute clusters here,” he said.

The CEO added that even if smaller firms like Perplexity are able to get Nvidia’s chips, they’ll continue to fall behind because AI is developing so quickly.

Srinivas said AI talent at major tech companies “will have already made the next-generation model.”

“They’re like, ‘Look, the world has changed, I’m already in the next generation,'” he added. “‘I’ll come when the next version of the model is finished training. This time, you come back to me when you have 20,000 H100s.'”

Srinivas and Meta didn’t immediately respond to a request for comment from Business Insider before publication.

There’s been a rapid uptick in interest in AI skills like machine learning and data engineering since OpenAI launched ChatGPT in November 2022. Companies like Amazon, Netflix, and Meta have offered salaries as high as $900,000 a year to attract generative AI talent, and non-tech companies across the education, healthcare, and legal sectors have been looking to fill roles with workers who know how to use AI.

Srinivas believes that workers need skills beyond the ability to create AI models that generate desirable outputs.

“You have to post-train them and address the long tail of issues you get on serving a product,” the CEO said.

Post-training expertise, like knowing how to reduce a chatbot’s factual inaccuracies, is an important skill that employees from a wide range of digital industries can learn quickly, Srinivas said.

Leaning into that skill set, he said, will help AI companies like Perplexity stand out in a sector dominated by Big Tech.

“You have tremendous advantage to create a lot of value,” he said about post-training skills. “And we are focused on that.”



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