英伟达史上最大的一次收购，也可能是最招骂的一次

Core Viewpoint - NVIDIA has made a significant acquisition of Groq, a chip manufacturer with a different technological approach, for $20 billion, which has sparked discussions about market monopolization and competitive dynamics in the AI chip sector [1][19]. Group 1: Acquisition Details - NVIDIA's acquisition of Groq is its largest to date, aimed at eliminating a potential competitor in the AI chip market [1]. - Groq, founded in 2016, has a valuation exceeding $7 billion and was co-founded by Jonathan Ross, a designer of Google's first-generation TPU [3]. - The acquisition is structured as a "shell acquisition," where NVIDIA has not fully acquired Groq but has signed a non-exclusive licensing agreement to use Groq's inference technology [22]. Group 2: Technology Insights - Groq's core product is the Language Processing Unit (LPU), designed specifically for accelerating AI computations, similar to Google's TPU but without the use of high-bandwidth memory (HBM) [5][12]. - The LPU utilizes SRAM for storage, allowing for faster data access compared to traditional GPU architectures, achieving data retrieval speeds over 20 times faster than GPUs [12][24]. - Groq's LPU has demonstrated a model inference speed that is reportedly 10 times faster than NVIDIA's GPUs, indicating its potential to disrupt the market [14]. Group 3: Market Implications - The acquisition reflects a broader trend in the AI industry where the demand for model inference is expected to surpass that for model training, as indicated by a Bloomberg report projecting a decrease in training costs from 60% to around 20% of data center expenditures by 2032 [25]. - NVIDIA's move to acquire Groq's technology suggests a strategic effort to enhance its capabilities in both model training and inference, ensuring it remains a dominant player in the AI computing landscape [24][25].