As computing technology advances, it has become increasingly clear in recent years that tighter integration between semiconductor and software development is needed. The surge in artificial intelligence (AI) activity in 2023 embodies this. As Nvidia (NASDAQ: NVDA) CEO Jensen Huang has been explaining for years, AI is a full-stack problem -- meaning a successful deployment of AI-powered computing requires deep understanding of chips and the software that runs on it.

Unfortunately for Advanced Micro Devices (NASDAQ: AMD) and other semiconductor competitors, software is sorely lacking from their ecosystem. But AMD has been leaning into its efforts to narrow that gap, and just announced an acquisition to help. Will it be enough as AMD looks to cash in on the AI craze Nvidia ignited?

Just as a reminder before delving into this discussion, AI has actually been around for decades. But more often than not, when folks in the tech world drop the phrase "AI" right now, they're talking about generative AI powered by large language models (LLMs) or something similar. This type of AI requires an algorithm (like an LLM) to be trained with massive amounts of data, using a computing chip accelerator (like a GPU) to train the algorithm and then deploy the finished product for use. 

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Source Fool.com