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 … – Yahoo News

3 minutes, 1 second Read
  • It’s only getting harder to hire workers with AI skills.

  • The CEO of an AI startup said he couldn’t poach a Meta employee because it didn’t have enough GPUs.

  • “Amazing incentives” are needed to attract AI talent, he said on the podcast “Invest Like The Best.”

Recruiting AI talent appears to 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 reflects just 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 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 5 to 10 years to get from Nvidia,” Srinivas said.

Limited funds — combined with a chip shortage — may be one reason 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.

“People don’t want to leave because when you don’t have anything when they have peers to work with, and when they already have a great experimentation stack and existing models to bootstrap from, for somebody to leave, it’s a lot of work,” the CEO said. “You have to offer such amazing incentives and immediate availability of compute. And we’re not talking of small compute clusters here.”

The CEO added that even if smaller firms like Perplexity are finally able to get Nvidia’s chips, they’ll continue to fall behind because of AI’s rapid speed of development.

That could make it even harder to secure AI talent in the future.

“By the time you waited and got the money and booked the cluster and got it, the guys working here will have already made the next-generation model,” Srinivas said, referring to AI talent at major tech companies.

“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 Business Insider’s request for comment before publication.

There has 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.

While Big Tech companies may employ workers who can create AI models that generate desirable outputs, Srinivas believes that skillset alone isn’t enough to make AI tools useful.

“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 industries like crypto or e-commerce can quickly learn, Srinivas said.

Leaning into that skillset, the CEO 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.”

Read the original article on Business Insider

This post was originally published on this site

Similar Posts