October 16, 2023 · 1 min read
GPT-4, PaLM, Claude, Bard, LaMDA, LLaMA, Chinchilla, Sparrow – the list of large-language models on the market continues to grow. But behind their remarkable capabilities, users are discovering substantial costs. While LLMs offer tremendous potential, understanding their economic implications is crucial for businesses and individuals considering their adoption.
Multiverse Computing
OpenAI itself says that the amount of compute used in the largest AI training runs has been increasing exponentially, doubling every few months.
Sam Mugel, Chief Technology Officer of Multiverse, which uses tensor networks and quantum computing to bring down costs, estimates that training the next generation of large language models will pass $1 billion within a few years.
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