Social media giant Meta is facing unprecedented AI infrastructure costs, with projected AI-related spending soaring to a staggering $65 billion, potentially contributing to a total annual expenditure of $119 billion! Faced with this astronomical bill, the tech giant has decided to develop its own AI chips, and has already made significant progress. Recent reports indicate that Meta is about to begin a small-scale deployment of its custom chips, signaling a gradual move away from Nvidia and its reliance on their GPUs.

Recently, Musk officially launched the brand new chatbot Grok 3 in a live stream and disclosed the astonishing cost of training the model. Grok 3 is currently available to Premium + subscribers and has shown outstanding performance in various evaluation areas, even surpassing other competitors in the market, such as Gemini, DeepSeek, and ChatGPT. During the live stream, Musk mentioned that the training process for Grok 3 consumed a total of 200,000 NVIDIA GPUs, a figure that is truly shocking.

Social media giant Meta plans to deploy a custom second-generation AI chip, codenamed Artemis, in its data centers this year. The new chip will be used for running AI model 'inference' and aims to reduce dependency on chips and control the costs of AI workloads. Meta CEO Mark Zuckerberg announced plans to use 340,000 Nvidia H100 GPUs, totaling around 600,000 GPUs, for running and training AI systems. Meta hopes to lower its dependence on Nvidia chips through the deployment of its own AI chips.