ASICs won’t replace GPUs

ASICs are cost-effective at scale, but rigid because they are hardwired for highly specific functions, such as machine learning workloads. That said, the software stack remains flexible, which is why Google and AWS have been discussing selling their custom chips to select third parties for similar AI training and inference tasks.

For Meta, using ASICs for a high-volume, repetitive inferencing task like its content recommendation algorithms for Instagram and Facebook makes perfect sense because it leverages what it has learned previously and applies it to new inputs without needing to be retrained.

Nvidia’s GPUs, particularly when paired with its CUDA software platform, can be easily reprogrammed to handle changing needs. As such, GPUs are more suitable for customers where innovation and flexibility are required, such as those in high-performance computing, regulatory-heavy industries, cybersecurity, and healthcare.

In other words, GPUs will always be needed at the frontier of AI for evolving workloads, whereas ASICs are useful for maximizing efficiency for fixed workloads.

A top AI inferencing play

Even with the stock trading near its all-time high and carrying a premium valuation, Broadcom remains a generational buying opportunity for long-term investors because it has a diversified business model across non-AI semiconductors and infrastructure software, plus a clear runway for AI-driven growth.

As AI use cases and adoption become more widespread, many simple, straightforward, inference-heavy tasks that do not require retraining will benefit from ASICs. Investors who believe AI will be increasingly used to automate stable, repetitive workloads should take a closer look at buying Broadcom in June.

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Daniel Foelber has positions in Nvidia. The Motley Fool has positions in and recommends Alphabet, Amazon, Broadcom, Goldman Sachs Group, Meta Platforms, and Nvidia. The Motley Fool has a disclosure policy.

Does the Surge in Demand for ASICs Make Broadcom a No-Brainer Buy Before June 3? was originally published by The Motley Fool