Thoughts on AI compute demand & NVDA's next leg

Been following the AI space closely, and it's clear the compute arms race is far from over. We've seen incredible runs in companies like NVDA, and a lot of that is priced in based on current demand. However, I'm starting to think about the next wave of demand, specifically from smaller, specialized AI models and the increasing need for on-device inference for edge computing.

My take is there's a 65-70% chance we see a significant push towards more distributed and energy-efficient AI hardware solutions by late Q3/early Q4. This isn't necessarily about a new type of chip altogether, but more about optimization and broader adoption across various industries beyond just hyperscalers. If this trend solidifies, it could open up a whole new TAM for companies that can adapt. It's a different kind of growth driver than just building bigger data centers, and it could be the catalyst for the next leg up for the broader AI hardware sector, even if $RBLX is having a rough day and $DOGE is just doing its thing.