This might be the most underrated AI story of today. According to CNBC, TikTok's US business is looking to secure multiple gigawatts of computing capacity, with one source suggesting the company is targeting 4 GW by the early 2030s. I don't think people understand how significant this is. We're talking about a social media platform potentially looking to secure enough power and computing infrastructure to rival some of the largest AI data center developments in the country. For perspective, Meta's massive Hyperion data center campus in Louisiana is targeting around 5 GW of capacity. TikTok already relies primarily on Oracle Cloud Infrastructure, and the company has confirmed that $ORCL will remain its primary cloud provider in the United States. On top of that, TikTok is retraining its recommendation algorithm using American user data and is developing AI products focused on large model inference and creative automation. In other words, this isn't necessarily just about supporting people scrolling through videos anymore. TikTok could be preparing for significantly more AI workloads which would require enormous amounts of computing power. Now connect this to everything else we've been discussing. Microsoft, Amazon, Google, Meta, OpenAI, and xAI are already competing to secure power, GPUs, land, and data center capacity. Now we're seeing another major technology platform potentially entering that same competition at the gigawatt scale. And remember, these companies cannot simply decide they want another gigawatt of computing capacity and have it available tomorrow. They need electricity, substations, cooling infrastructure, networking equipment, GPUs, memory, and facilities capable of supporting all of it. This is exactly why I remain so bullish on the companies supplying the infrastructure behind AI. Whether we're talking about $NVDA, $MU, $ORCL, $BE, or the broader networking and power ecosystem, the number of potential customers competing for limited resources continues to grow. What's particularly interesting is that this demand is increasingly coming from companies outside the handful of frontier AI labs everyone focuses on. I think we're still underestimating just how much infrastructure the AI economy is going to need over the next decade.