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Hugging Face is sharing $10 million worth of compute to help beat the big AI companies

May 22, 2024 - theverge.com
Hugging Face, a leading machine learning company, is investing $10 million in free shared GPUs to support developers, academics, and startups in creating new AI technologies. The initiative, called ZeroGPU, aims to counter the centralization of AI advancements by making state-of-the-art AI technologies accessible to everyone, not just tech giants. The shared GPUs will be available through Hugging Face’s hosting platform, Spaces, and will be allocated based on usage, making them cost-effective and ideal for community-wide utilization.

The company's CEO, Clem Delangue, expressed concern about the ability of AI startups to compete with tech giants, who often keep significant advancements in AI proprietary and have vast resources for computational resources. Delangue believes in a more decentralized approach to AI, where most organizations can participate without too much concentration of power. The investment is possible due to Hugging Face's profitability and recent funding of $235 million, which valued the company at $4.5 billion.

Key takeaways:

  • Hugging Face, a major player in machine learning, is committing $10 million in free shared GPUs to support developers, academics, and startups in creating new AI technologies, aiming to counter the centralization of AI advancements.
  • The company's CEO, Clem Delangue, believes that the open-source approach to AI is a more decentralized and equitable way forward, as opposed to the proprietary models of major tech companies.
  • Hugging Face is launching a new program called ZeroGPU, which will provide shared GPU access to the community through its hosting platform, Spaces. The shared GPUs can be used by multiple users or applications concurrently, making them cost-effective and energy-efficient.
  • Delangue also expressed concern about the difficulties smaller companies and developers face in securing enough GPUs from main cloud providers, as they often require committing to large numbers for long periods. He believes this creates a high barrier to entry and disadvantages those who build on a smaller scale.
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