100,000-strong GPU clusters are next
LLMs show no sign of plateauing, says OpenAI's CTO Mira Murati.
LLMs show no sign of plateauing, says OpenAI's CTO Mira Murati - so we can expect ever-larger AI models.
Mira spoke at a fireside chat at Qualtrics X4 which I attended in May, and recent developments show that we are indeed on the trajectory she painted.
Here are some comments she made that caught my interest:
- Expect another leap in performance
Even the researchers at OpenAI were astounded by the new capabilities that GPT-3, then GPT-4 delivered. She expects GPT-5 to offer yet another "step change" in new capabilities.
- How you are helping train AI
As observers have long pointed out, OpenAI isn't offering a free version of ChatGPT for purely altruistic reasons. By Mira's admission, inputs from users are used for reinforcement learning, helping make AI more steerable and useful".
- 100,000 GPU AI models coming soon
Mira says there is no sign that the scaling paradigm - which posits that AI models will become more powerful with more compute and data - will taper off soon.
- To add to point 3, we know that LLama 3 was trained on 24,000 GPU clusters and that Meta is currently working to build GPU clusters in the "hundreds of thousands".
- Elon Musk has separately told investors he wants to deploy a 100,000 H100 GPU data centre for his xAI startup, which recently closed a US$6 billion fundraising round.
The next generation of AI models will be trained on supercomputers with GPUs numbering in the 100,000s - likely leaving the supercomputers of just a few years ago in the dust.
Where will the AI race end? Or should I ask instead: How will the AI race end?
Read my full article here.