🔥🚀 Jensen Huang is playing a bigger game: $NVDA isn't just about selling computing power, but rather 'deciding who gets to use that computing power'
In the past, $NVDA was always seen as 'the one selling shovels'.
But in the last six months, I've started to realize that this assessment is outdated.
The real change is — Jensen Huang is no longer just providing GPUs; he's using capital to redesign the entire power structure of the AI industry.
Over the past six months, nearly $19 billion in investments haven’t been simple financial maneuvers, but rather resemble a complete 'ecosystem control system'.
When you break it down, the logic becomes very clear: it’s not about scattered bets but making systematic moves around two core issues — 'how demand for computing power can be amplified' and 'who will consume that computing power.'
The first layer, which I think is the most critical, is control over foundational bottlenecks.
$SNPS
$INTC
As AI enters the era of clusters with hundreds of thousands of cards, the real limitation is no longer the performance of a single GPU but design efficiency, packaging capability, and data transmission.
Investing in EDA ($SNPS) essentially accelerates the 'speed at which the next generation of GPUs will be born.'
Investing in $INTC, on the other hand, serves as a strategic backup for advanced packaging and foundry work, reducing reliance on a single supply chain.
Looking further, the optical communication sector is more directly relevant.
$LITE
$COHR
Without 800G or 1.6T transmission capabilities, even the most powerful GPUs will be isolated islands.
The logic here is very simple...