Jensen Huang CEO of $NVDA named a few stocks this year.
They all ripped, except this one. It’s actually down since he recommended it.
Might be something to take a look at.
$QCOM
$NVDA CEO JENSEN HUANG SAYS 1 GW DATACENTER GENERATES $300-400 BILLION, COSTS $50 BILLION
This is also what SpaceX $SPCX is demonstrating with its $GOOGL and Anthropic Deals.
If the ROIs are that high, the next 5 years have the potential to be a golden age of technology investing.
The Hyperscalers and Semiconductors profits could be enormous.
Nvidia $NVDA is cheaper than the S&P 500 despite a $4.8 trillion market cap.
Largest company in the world trades at a forward P/E of 19.7x, below the benchmark's 20.4x.
Insane.
If you hold $NVDA and this 15% pullback has you unsure what to do, watch this. 📈
I walk through why my Bull Cycle criteria are still in play, the levels I’m watching, and what would actually tell me it’s time to stop buying this dip.
Wait.
$NVDA CEO Jensen Huang is talking about $3T in annual revenue.
60% margins = $1.8T profit.
Nvidia’s market cap = ~$5T.
That’s less than 3x earnings.
Nvidia is either absurdly cheap today.
Or the entire AI thesis is wrong.
Which is it?
Nvidia $NVDA just posted this
"Nvidia GPUs with Confidential Computing are now used for confidential inference in Apple’s Private Cloud Compute (PCC), as it expands beyond Apple’s data centers to Google Cloud."
"NVIDIA Confidential Computing provides a hardware-based security layer for accelerated AI workloads. The technology protects data while it’s being processed by isolating workloads in trusted execution environments and enabling systems to cryptographically verify that the infrastructure has not been tampered with before any sensitive data is sent to the server."
$NVDA I would love to get this name sub $200’s, preferably closer to $190 for an entry.
Absolutely think we can see fresh ATH’s later this year.
Base case $240
Bull case $275
Ultra FOMO bull case $300
NVIDIA $NVDA AND SK HYNIX JUST ANNOUNCED A MULTIYEAR TECHNOLOGY PARTNERSHIP
SK Hynix will codevelop memory for four specific NVIDIA platforms: Vera Rubin AI supercomputers, Vera CPUs, RTX Spark-powered PCs, and Jetson Thor robotic computing platforms.
SK Hynix will apply AI to semiconductor chip design and manufacturing itself, using NVIDIA's CUDA-X libraries and PhysicsNeMo framework to accelerate chip simulations and engineering workflows.
SK Hynix will build factory digital twins using NVIDIA Omniverse, targeting fully autonomous fab operations.
"AI factories are the engines of the next industrial revolution, and advanced memory is essential to their performance." - Jensen Huang
The hyperscalers are set to spend over $700 billion in capex for 2026.
Here's where that money is flowing:
1. $NVDA - NVIDIA
Q1 revenue $81.6B, up 85% YoY. Data center alone was $75.2B. Total supply commitments surged to $119B as every major hyperscaler scales Blackwell infrastructure. Q2 guided at $91B. The single largest recipient of AI capex on the planet.
$NVDA CEO Jensen on Stock selloff:
“We’re at the beginning of [AI Supercycle], and whatever happened to the stock market, you should be very happy because now you can buy at a discount... Everybody should be very excited
“It is a foregone conclusion that AI will be infrastructure for the world, just like the internet was infrastructure for the world.”
😁Trump just signed an agreement allowing 401k investments in #crypto, and $XRP is going to be included in American pension plans…
My feelings about holding this stock have changed from 'love-hate relationship' to 'finally, this day has come'. How high do you think this wave of institutional funds can push $XRP?
$NVDA CEO Jensen Huang was handing out SK Hynix x 7-Eleven HBM chips to fans in South Korea.
He joked “No HBM for you since I need all the HBM” after saying everyone loves HBM.
A $NVDA Rubin Ultra AI Factory rack contains $123,092 worth of power semiconductors. A Hopper rack from 2023 contained $3,888.
That is a 31x increase in four years. Not from higher prices. From a complete architectural overhaul of how electricity moves inside an AI factory.
The old standard was 54 volt DC. Power supply units in each rack converted AC from the grid, stepped it down to 54V, and distributed it through copper busbars to each GPU. That system worked fine at 40 kilowatts per rack.
Rubin Ultra pulls 600 kilowatts. Feynman hits 1 megawatt. At that scale, 54V distribution requires up to 200 kilograms of copper busbar per rack. A single 1-gigawatt AI factory would need 200,000 kilograms of copper just for busbars.
$NVDA's answer is 800 volt DC. AC from the grid is converted once at the facility perimeter and distributed at 800V through the AI factory. This cuts copper requirements by 45% and enables 85% more power through the same conductor size.
I'm putting together a deep report on my favorite names in this space dropping Monday. So keep an eye out.
This is a really interesting paper about stock performance.
If you bought $AMD at the close every day and sold at the open the next day, over decades you’d have gotten a whopping +4,555,517% return.
But if you bought at the open every day and sold at the close the same day, you’d have lost almost everything – down -99.94%.
This pattern holds across every major market globally. This just reiterates that time IN the market beats anything else.
Other examples:
$MU: overnight +138,330,342% – intraday -99.92%
$NVDA: overnight +221,715% – intraday -99.7%
Same stocks. Completely opposite outcomes depending on when you hold it, overnight risk premium pays, intra day trading doesn’t.
Jensen $NVDA is saying….
WE NEED MORE MEMORY!
Memory = Cheat Code to Wealth in the Next 3-5 years…
Buy:
1) $DRAM
2) Micron $MU
3) Sandisk $SNDK
4) $FLKR
5) $SMH
Even:
6) $QQQM & $XLK is poised for high growth potential …