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.

Google Cloud has collaborated with Y Combinator to offer AI startups $350,000 worth of cloud computing resources, including dedicated GPU/TPU clusters, for a period of two years. This initiative aims to foster AI innovation by prioritizing access to computing resources and facilitating one-on-one discussions with AI experts, helping startups tackle technical challenges and promote their growth. The partnership seeks to nurture future tech giants, with Google aiming to establish long-term relationships through early support. This collaboration not only addresses the computing resource needs of startups.

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.