CES, held annually in January, is one of the most important trade shows where tech companies go to unveil innovations and showcase bold ideas for the future.
At the 2026 event, Nvidia CEO Jensen Huang offered something that has been just as impactful: his insights about the growing memory needs of artificial intelligence (AI). And based on where the stock prices of Micron Technology (NASDAQ: MU) and Sandisk (NASDAQ: SNDK) have gone since then, his understand of the situation was right on the money.
Missed Nvidia in 2009? This Rare Signal Is Flashing Again. In 2009, a "Double Down" signal flashed for a little-known chipmaker called Nvidia. For the first time in years, that same "Total Conviction" signal is flashing for a company 1/100th the size of Nvidia. Continue »
Large language models are being asked to deliver on requests promptly, but there's also a growing expectation that these tools will preserve users' older requests and conversations as time savers to provide context for the new ones. That requires increasingly higher memory capacity in the data centers that power those AIs, which Huang alluded to in his January CES speech:
We would like this AI to stay with us our entire lives and remember every single conversation we've ever had with it, right? Every single lick of research that I've asked for. Of course, the number of people sharing the supercomputer will continue to grow. And so, this context memory, which started out fitting inside an HBM, is no longer large enough.
At the 2026 event, Nvidia CEO Jensen Huang offered something that has been just as impactful: his insights about the growing memory needs of artificial intelligence (AI). And based on where the stock prices of Micron Technology (NASDAQ: MU) and Sandisk (NASDAQ: SNDK) have gone since then, his understand of the situation was right on the money.
Missed Nvidia in 2009? This Rare Signal Is Flashing Again. In 2009, a "Double Down" signal flashed for a little-known chipmaker called Nvidia. For the first time in years, that same "Total Conviction" signal is flashing for a company 1/100th the size of Nvidia. Continue »
Large language models are being asked to deliver on requests promptly, but there's also a growing expectation that these tools will preserve users' older requests and conversations as time savers to provide context for the new ones. That requires increasingly higher memory capacity in the data centers that power those AIs, which Huang alluded to in his January CES speech:
We would like this AI to stay with us our entire lives and remember every single conversation we've ever had with it, right? Every single lick of research that I've asked for. Of course, the number of people sharing the supercomputer will continue to grow. And so, this context memory, which started out fitting inside an HBM, is no longer large enough.
9 days ago
