Does the Surge in Demand for ASICs Make Broadcom a No-Brainer Buy Before June 3?

The initial boom in artificial intelligence (AI) data center investment centered around hardware for training AI models -- workloads that demand massive parallel-processing capabilities. Graphics processing units (GPUs) are powerful and flexible parallel processors, and that property propelled the rise of GPU specialist Nvidia (NASDAQ: NVDA) from an ordinary large cap worth around $350 billion at the start of 2023 to its current position as the world's most valuable company. Today, it's worth more than $5 trillion.But data centers are growing in size, creating cost constraints and an AI energy bottleneck. What's more, hyperscalers' needs are evolving as AI inference becomes a growing part of the overall workload. While training is needed to build a model's intelligence, inference applies that intelligence in real-world applications, such as through AI chatbots, AI agents, robotics, and self-driving cars.Application-specific integrated circuits (ASICs) aren't nearly as flexible as GPUs, but they can be highly cost-effective at scale. This is why investment bank Goldman Sachs forecasts that demand for ASICs will surpass GPU demand in the coming years.Continue readingWeiter zum vollständigen Artikel bei MotleyFool Weiter zum vollständigen Artikel bei MotleyFool