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Jensen Huang: “We need memory for… HBM memory for performance. We need LPDDR for low-power memory.” Reporter: Is memory constraint an issue for NVIDIA this year? Jensen Huang: “The entire supply chain is challenging this year because demand is so much more. Supply has been growing 100% every year,... show more

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NVIDIA $NVDA CEO JENSEN HUANG JUST SAID: "We need many many TRILLIONS OF DOLLARS OF CAPACITY...We work with EVERY MEMORY VENDOR, BECAUSE WE USE SO MUCH MEMORY. We are going to work with every connector vendor, EVERY SINGLE SILICON PHOTONICS COMPANY." $AAOI $COHR $LITE $CIEN $FN $MU $SNDK $EWY

NVIDIA $NVDA CEO JENSEN HUANG JUST SAID: "We need many many TRILLIONS OF DOLLARS OF CAPACITY...We work with EVERY MEMORY VENDOR, BECAUSE WE USE SO MUCH MEMORY. We are going to work with every connector vendor, EVERY SINGLE SILICON PHOTONICS COMPANY." $AAOI $COHR $LITE $CIEN $FN $MU $SNDK $EWY

KawzInvests 🦑

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Look at the expression on Jensen’s face when a reporter asks if TSMC is going to make enough wafers for Nvidia this year. I'm not a CIA body language expert, but GOOD LUCK to da bears. $NVDA Reporter: "Jensen will TSMC be supplying enough for you guys this year?" Nvidia CEO Jensen Huang: "TSMC needs to work very hard this year because I need a lot of wafers and CoWoS this year. ... So TSMC is doing an incredible job and they're working very, very hard. We have a lot of demand this year."

Look at the expression on Jensen’s face when a reporter asks if TSMC is going to make enough wafers for Nvidia this year. I'm not a CIA body language expert, but GOOD LUCK to da bears. $NVDA Reporter: "Jensen will TSMC be supplying enough for you guys this year?" Nvidia CEO Jensen Huang: "TSMC needs to work very hard this year because I need a lot of wafers and CoWoS this year. ... So TSMC is doing an incredible job and they're working very, very hard. We have a lot of demand this year."

tae kim

403,365 görüntüleme • 5 ay önce

Jensen Huang and Michael Dell discussed the supply bottleneck: Michael - memory is the challenge. Jensen - we will have billions of agents, and we will need to give each agent essentially its own computer to use.

Jensen Huang and Michael Dell discussed the supply bottleneck: Michael - memory is the challenge. Jensen - we will have billions of agents, and we will need to give each agent essentially its own computer to use.

The AI Investor

242,630 görüntüleme • 1 ay önce

Jensen Huang says $NVDA has “the largest supply chain in the world” but AI demand is still outstripping global capacity. The bottleneck is memory, compute, power and the physical buildout required to turn AI demand into usable capacity.

Jensen Huang says $NVDA has “the largest supply chain in the world” but AI demand is still outstripping global capacity. The bottleneck is memory, compute, power and the physical buildout required to turn AI demand into usable capacity.

Shay Boloor

89,861 görüntüleme • 1 ay önce

Jensen Huang just made a statement that every investor in AI infrastructure needs to hear (Save this). He said that the AI buildout is accelerating, the second half of this year is going to be much larger than the first half, and next year is going to be very, very large. Micron is the best positioned to win from this because every Nvidia GPU requires High Bandwidth Memory stacked directly on the chip to feed it data fast enough to keep up. There is no AI compute without memory, and right now there is simply not enough memory to go around. Micron's entire HBM supply for 2026 is already completely sold out under multi-year agreements before the year even started. Micron's own management has acknowledged they can only satisfy 50 to 65 percent of demand from some of their most important customers. That is not a problem that gets fixed quickly, because new fabs take years to build. Micron's Idaho expansion does not come online until mid-2026, a second Idaho facility is not expected until 2028, and a new New York fab is looking at 2030. The demand Jensen just described is arriving right now, and the supply to meet it is years away. The financial results already reflect this dynamic. Micron's Q2 fiscal 2026 revenue came in at $23.86 billion, nearly triple what it was a year earlier beating consensus by roughly $3.8 billion. The HBM market alone is expected to grow from $35 billion today to $100 billion by 2028, and Micron has been consistently ahead of that forecast. Jensen just told the world the second half of this year and all of next year are going to be larger than anything that came before. Micron is the company that supplies the memory those GPUs need to run, and it cannot build supply fast enough to keep up with demand. Come join Milk Road Pro for our full deep dive on Micron, the HBM supply thesis and our AI trade thesis! Link below!

Jensen Huang just made a statement that every investor in AI infrastructure needs to hear (Save this). He said that the AI buildout is accelerating, the second half of this year is going to be much larger than the first half, and next year is going to be very, very large. Micron is the best positioned to win from this because every Nvidia GPU requires High Bandwidth Memory stacked directly on the chip to feed it data fast enough to keep up. There is no AI compute without memory, and right now there is simply not enough memory to go around. Micron's entire HBM supply for 2026 is already completely sold out under multi-year agreements before the year even started. Micron's own management has acknowledged they can only satisfy 50 to 65 percent of demand from some of their most important customers. That is not a problem that gets fixed quickly, because new fabs take years to build. Micron's Idaho expansion does not come online until mid-2026, a second Idaho facility is not expected until 2028, and a new New York fab is looking at 2030. The demand Jensen just described is arriving right now, and the supply to meet it is years away. The financial results already reflect this dynamic. Micron's Q2 fiscal 2026 revenue came in at $23.86 billion, nearly triple what it was a year earlier beating consensus by roughly $3.8 billion. The HBM market alone is expected to grow from $35 billion today to $100 billion by 2028, and Micron has been consistently ahead of that forecast. Jensen just told the world the second half of this year and all of next year are going to be larger than anything that came before. Micron is the company that supplies the memory those GPUs need to run, and it cannot build supply fast enough to keep up with demand. Come join Milk Road Pro for our full deep dive on Micron, the HBM supply thesis and our AI trade thesis! Link below!

Milk Road AI

77,554 görüntüleme • 21 gün önce

Memory is a MASSIVE Constraint for GPUs $TSLA CEO Elon Musk mentioned this on his earnings call. $NVDA CEO Jensen Huang covers this. $MU, SK Hynix, and Samsung continue to hike prices as demand grows

Memory is a MASSIVE Constraint for GPUs $TSLA CEO Elon Musk mentioned this on his earnings call. $NVDA CEO Jensen Huang covers this. $MU, SK Hynix, and Samsung continue to hike prices as demand grows

Sam Badawi

11,027 görüntüleme • 4 ay önce

🚨 JENSEN HUANG: “The amount of energy that we need for computing is probably 1,000x more than we currently have.”

🚨 JENSEN HUANG: “The amount of energy that we need for computing is probably 1,000x more than we currently have.”

Chief Nerd

3,002,690 görüntüleme • 1 ay önce

$MU CEO Sanjay Mehrotra said Micron can only supply ~60% of what key customers are requesting as AI demand creates an unprecedented memory shortage. Every wafer shifted into HBM can cost ~3x the standard DRAM output and demand keeps rising because inference, agents, robotics and autonomous systems are all memory-bandwidth-bound. Memory fab capacity takes three to five years to build so the shortage Mehrotra is describing today could define the supply curve for the rest of the decade.

$MU CEO Sanjay Mehrotra said Micron can only supply ~60% of what key customers are requesting as AI demand creates an unprecedented memory shortage. Every wafer shifted into HBM can cost ~3x the standard DRAM output and demand keeps rising because inference, agents, robotics and autonomous systems are all memory-bandwidth-bound. Memory fab capacity takes three to five years to build so the shortage Mehrotra is describing today could define the supply curve for the rest of the decade.

Shay Boloor

124,980 görüntüleme • 1 ay önce

I still think $MU is cheap because the SCAs should force investors to rethink the multiple. Over time, Micron expects more than 50% of total revenue to be covered by these agreements giving the business a level of visibility memory companies historically never had. A memory company with no visibility deserves a commodity multiple but a memory company with minimum pricing, multi-year supply agreements and a structurally higher AI demand floor deserves more credit for normalized earnings power.

I still think $MU is cheap because the SCAs should force investors to rethink the multiple. Over time, Micron expects more than 50% of total revenue to be covered by these agreements giving the business a level of visibility memory companies historically never had. A memory company with no visibility deserves a commodity multiple but a memory company with minimum pricing, multi-year supply agreements and a structurally higher AI demand floor deserves more credit for normalized earnings power.

Shay Boloor

144,323 görüntüleme • 6 gün önce

JENSEN HUANG: “We have to make sure that the supply chain upstream and downstream are prepared for this future … We're going to have billions of [AI] agents in the world, and they're going to be working 24/7.”

JENSEN HUANG: “We have to make sure that the supply chain upstream and downstream are prepared for this future … We're going to have billions of [AI] agents in the world, and they're going to be working 24/7.”

Chief Nerd

19,784 görüntüleme • 1 ay önce

NVIDIA CEO, Jensen Huang introduced: "DGX Station" — designed for data scientists and researchers it includes: - 20 petaflops of performance - 72 CPU cores - Chip-to-chip interface - HBM (high bandwidth memory) - PCIe slots for GeForce

NVIDIA CEO, Jensen Huang introduced: "DGX Station" — designed for data scientists and researchers it includes: - 20 petaflops of performance - 72 CPU cores - Chip-to-chip interface - HBM (high bandwidth memory) - PCIe slots for GeForce

Haider.

206,611 görüntüleme • 1 yıl önce

$MU hit a $1T valuation today because the market is waking up to the idea that memory may actually become one of the core infrastructure layers of the AI economy. The catalyst was SK Hynix unveiling iHBM which is a new cooling technology for next-gen HBM but the bigger point is that token growth, AI factories, inference demand & next-gen accelerators all require more HBM per system. More HBM per accelerator means more memory dollar content & with only three major HBM suppliers in the world the entire memory complex is getting re-rated.

$MU hit a $1T valuation today because the market is waking up to the idea that memory may actually become one of the core infrastructure layers of the AI economy. The catalyst was SK Hynix unveiling iHBM which is a new cooling technology for next-gen HBM but the bigger point is that token growth, AI factories, inference demand & next-gen accelerators all require more HBM per system. More HBM per accelerator means more memory dollar content & with only three major HBM suppliers in the world the entire memory complex is getting re-rated.

Shay Boloor

306,107 görüntüleme • 1 ay önce

DeepMind CEO Demis Hassabis says the AI bottleneck is already moving from model ideas to physical supply chains. "How much of the restriction at this point is physical? I am talking memory shortage, GPU shortage, and electricity." Demis: "That is constraining a lot of the deployment for sure. We see so much more demand for our models - Gemini and the other models that we have - than we can possibly serve." Then the less obvious part: "It does constrain a little bit the research, because you need a lot of chips to be able to experiment on new ideas at big enough scale that you can actually see if they are going to work." And on memory: "The whole supply chain is kind of strained... It still in the end actually comes down to a few suppliers of a few of the key components. Anywhere where there is some kind of constraint on the capacity, there is a sort of choke point." Important framing: The next AI race is not just who has the best model architecture. It is who can secure memory, chips, power, suppliers, and enough experimental capacity to find the next breakthrough before everyone else.

DeepMind CEO Demis Hassabis says the AI bottleneck is already moving from model ideas to physical supply chains. "How much of the restriction at this point is physical? I am talking memory shortage, GPU shortage, and electricity." Demis: "That is constraining a lot of the deployment for sure. We see so much more demand for our models - Gemini and the other models that we have - than we can possibly serve." Then the less obvious part: "It does constrain a little bit the research, because you need a lot of chips to be able to experiment on new ideas at big enough scale that you can actually see if they are going to work." And on memory: "The whole supply chain is kind of strained... It still in the end actually comes down to a few suppliers of a few of the key components. Anywhere where there is some kind of constraint on the capacity, there is a sort of choke point." Important framing: The next AI race is not just who has the best model architecture. It is who can secure memory, chips, power, suppliers, and enough experimental capacity to find the next breakthrough before everyone else.

Karl Mehta

25,716 görüntüleme • 4 gün önce

If $MU confirms tomorrow that DRAM, NAND and HBM tightness can last into 2027 or 2028 then memory companies have more reason to keep spending on capacity and advanced manufacturing tools. That matters for $ASML because it sits at the most important equipment layer of the semiconductor supply chain where more advanced memory capacity means more demand for lithography systems.

If $MU confirms tomorrow that DRAM, NAND and HBM tightness can last into 2027 or 2028 then memory companies have more reason to keep spending on capacity and advanced manufacturing tools. That matters for $ASML because it sits at the most important equipment layer of the semiconductor supply chain where more advanced memory capacity means more demand for lithography systems.

Shay Boloor

426,844 görüntüleme • 8 gün önce

Dylan on why memory prices will double again: "Memory can only grow capacity low double digit percentages a year. 20-30% a year, even less for NAND, a little bit higher for DRAM, but whatever. Even though the demand signal was very strong at the end of 2025, the memory companies immediately started reacting. None of that incremental capacity really gets here until 2028, even if they wanted to build as fast as possible. So the result is memory prices have gone through the roof. They're going to double and triple again. DRAM, especially. People are like, "oh, the memory story is overplayed." No, you don't get it. DRAM will double or triple from here still, because that's how much capacity is required. And they have to steal capacity from somewhere else. And the only way to steal capacity from somewhere else in a capitalist economy is demand destruction via higher pricing."

Dylan on why memory prices will double again: "Memory can only grow capacity low double digit percentages a year. 20-30% a year, even less for NAND, a little bit higher for DRAM, but whatever. Even though the demand signal was very strong at the end of 2025, the memory companies immediately started reacting. None of that incremental capacity really gets here until 2028, even if they wanted to build as fast as possible. So the result is memory prices have gone through the roof. They're going to double and triple again. DRAM, especially. People are like, "oh, the memory story is overplayed." No, you don't get it. DRAM will double or triple from here still, because that's how much capacity is required. And they have to steal capacity from somewhere else. And the only way to steal capacity from somewhere else in a capitalist economy is demand destruction via higher pricing."

Patrick OShaughnessy

189,478 görüntüleme • 2 ay önce

Very interesting conversation where Jensen Huang and Michael Dell explain how AI is structurally changing the memory industry 💾👇 $NVDA $DELL $MU $HXSCL

Very interesting conversation where Jensen Huang and Michael Dell explain how AI is structurally changing the memory industry 💾👇 $NVDA $DELL $MU $HXSCL

The Future Investors

180,405 görüntüleme • 1 ay önce

This year, the US will spend 40% more than it’s taking in. This number is increasing each year — and our debt plays a major role. This is a big problem, especially because cutting our spending is a difficult political issue. And as we continue to add to the debt, the supply-demand picture worsens. I fear that we are approaching the point where we won’t be able to rectify it.

This year, the US will spend 40% more than it’s taking in. This number is increasing each year — and our debt plays a major role. This is a big problem, especially because cutting our spending is a difficult political issue. And as we continue to add to the debt, the supply-demand picture worsens. I fear that we are approaching the point where we won’t be able to rectify it.

Ray Dalio

78,230 görüntüleme • 8 ay önce

The AI boom just hit a wall nobody saw coming. And it's not software. It's not regulation. It's not even energy... It's memory chips. Right now, Dell is raising PC prices by 30%. Intel can't ship chips. Nvidia is slashing GPU production by 40%. And almost nobody understands why. Here's the "hidden" crisis the AI industry is trying to hide: AI data centers are hoarding memory. Not GPUs. Not processors. MEMORY. Every AI server needs massive amounts of high-bandwidth memory (HBM) to run those models everyone's hyping. One problem: There are only 3 companies in the world that can make it. Samsung. SK Hynix. Micron. That's it. And all 3 just diverted their entire production capacity away from normal RAM to feed AI data centers. The math that breaks everything: 1 gigabyte of HBM takes 4X the manufacturing capacity of regular DRAM. AI will consume 20% of global DRAM production in 2026. But the thing is, consumer demand for RAM didn't disappear. PCs still need memory. Phones still need memory. Cars still need memory. But there's no capacity left to make it. The price explosion: RAM prices are up 246% in the last 6 months. DDR5 contract prices jumped 100% month-over-month in some cases. Dell's CFO said he's "never witnessed costs escalating at this pace." SK Hynix and Micron? Sold out through all of 2026. Micron straight up EXITED the consumer memory market entirely to focus on AI customers. If you're not building an AI data center, you're not getting memory chips. AI data centers pay 3-5X margins compared to consumer products. So memory manufacturers are rationally choosing: Serve Microsoft and Google's AI buildout, or serve Dell's laptop business? Easy choice. Every wafer allocated to an Nvidia H100 GPU is a wafer DENIED to your next laptop. It's a zero-sum game. And consumers are losing. The dangerous cascade effect: Nvidia is cutting RTX 50-series GPU production by 30-40% because they can't get GDDR7 memory. Dell, Lenovo, HP are all raising PC prices 15-30% in early 2026. Xiaomi and other smartphone makers are cutting shipment targets. Even Intel's crash last week? Partially driven by memory shortages limiting chip production. This is a PERMANENT reallocation of the world's silicon capacity. Not a temporary supply hiccup. For decades, consumer electronics (phones, PCs, laptops) drove memory production. Now? AI data centers are the priority customer. And that priority shift is reshaping the entire tech economy. The timeline Is worse than you think: Industry analysts project shortages lasting through 2027, maybe 2028. Why? Because building new memory fabs takes 3-5 YEARS. Micron's new Idaho fab won't meaningfully impact supply until 2028. Samsung and SK Hynix are too busy ramping up HBM4 production to expand consumer DRAM. So we're stuck. AI companies need memory to scale. But producing that memory DESTROYS the supply chain for everything else. My question here: Everyone's betting on AI scaling infinitely. But what if the AI boom STALLS because there's not enough memory to support it? What if we're not in an "AI supercycle" but a "memory shortage that kills the AI buildout"? Intel crashed 17% because they can't manufacture enough chips. The root cause though? Memory shortages limiting what they can even produce. Nvidia is cutting GPU production by 40%. AMD is struggling to get GDDR6 for Radeon cards. This isn't just a consumer problem. It's an AI infrastructure problem. And if memory doesn't scale, AI doesn't scale. The AI industry sold you on infinite scaling. But they forgot to mention the part where there's only 3 companies making the memory chips that power everything. And all 3 just chose AI data centers over you. Even Nvidia can't make enough GPUs to meet demand. Not because of energy. Not because of regulation... But because the memory supply chain is BROKEN. And it won't be fixed until 2028.

The AI boom just hit a wall nobody saw coming. And it's not software. It's not regulation. It's not even energy... It's memory chips. Right now, Dell is raising PC prices by 30%. Intel can't ship chips. Nvidia is slashing GPU production by 40%. And almost nobody understands why. Here's the "hidden" crisis the AI industry is trying to hide: AI data centers are hoarding memory. Not GPUs. Not processors. MEMORY. Every AI server needs massive amounts of high-bandwidth memory (HBM) to run those models everyone's hyping. One problem: There are only 3 companies in the world that can make it. Samsung. SK Hynix. Micron. That's it. And all 3 just diverted their entire production capacity away from normal RAM to feed AI data centers. The math that breaks everything: 1 gigabyte of HBM takes 4X the manufacturing capacity of regular DRAM. AI will consume 20% of global DRAM production in 2026. But the thing is, consumer demand for RAM didn't disappear. PCs still need memory. Phones still need memory. Cars still need memory. But there's no capacity left to make it. The price explosion: RAM prices are up 246% in the last 6 months. DDR5 contract prices jumped 100% month-over-month in some cases. Dell's CFO said he's "never witnessed costs escalating at this pace." SK Hynix and Micron? Sold out through all of 2026. Micron straight up EXITED the consumer memory market entirely to focus on AI customers. If you're not building an AI data center, you're not getting memory chips. AI data centers pay 3-5X margins compared to consumer products. So memory manufacturers are rationally choosing: Serve Microsoft and Google's AI buildout, or serve Dell's laptop business? Easy choice. Every wafer allocated to an Nvidia H100 GPU is a wafer DENIED to your next laptop. It's a zero-sum game. And consumers are losing. The dangerous cascade effect: Nvidia is cutting RTX 50-series GPU production by 30-40% because they can't get GDDR7 memory. Dell, Lenovo, HP are all raising PC prices 15-30% in early 2026. Xiaomi and other smartphone makers are cutting shipment targets. Even Intel's crash last week? Partially driven by memory shortages limiting chip production. This is a PERMANENT reallocation of the world's silicon capacity. Not a temporary supply hiccup. For decades, consumer electronics (phones, PCs, laptops) drove memory production. Now? AI data centers are the priority customer. And that priority shift is reshaping the entire tech economy. The timeline Is worse than you think: Industry analysts project shortages lasting through 2027, maybe 2028. Why? Because building new memory fabs takes 3-5 YEARS. Micron's new Idaho fab won't meaningfully impact supply until 2028. Samsung and SK Hynix are too busy ramping up HBM4 production to expand consumer DRAM. So we're stuck. AI companies need memory to scale. But producing that memory DESTROYS the supply chain for everything else. My question here: Everyone's betting on AI scaling infinitely. But what if the AI boom STALLS because there's not enough memory to support it? What if we're not in an "AI supercycle" but a "memory shortage that kills the AI buildout"? Intel crashed 17% because they can't manufacture enough chips. The root cause though? Memory shortages limiting what they can even produce. Nvidia is cutting GPU production by 40%. AMD is struggling to get GDDR6 for Radeon cards. This isn't just a consumer problem. It's an AI infrastructure problem. And if memory doesn't scale, AI doesn't scale. The AI industry sold you on infinite scaling. But they forgot to mention the part where there's only 3 companies making the memory chips that power everything. And all 3 just chose AI data centers over you. Even Nvidia can't make enough GPUs to meet demand. Not because of energy. Not because of regulation... But because the memory supply chain is BROKEN. And it won't be fixed until 2028.

Ricardo

594,270 görüntüleme • 5 ay önce

We did it. We finally did it. Infinite memory. Microsoft AI CEO Mustafa Suleyman: “We have prototypes that have near-infinite memory. And so it just doesn’t forget, which is truly transformative. (...) 2025 is going to be truly transformative” Eric Schmidt (Ex-Google CEO) wasn't lying when he said infinite context window will be solved this year. Thats it, AGI is so close.

We did it. We finally did it. Infinite memory. Microsoft AI CEO Mustafa Suleyman: “We have prototypes that have near-infinite memory. And so it just doesn’t forget, which is truly transformative. (...) 2025 is going to be truly transformative” Eric Schmidt (Ex-Google CEO) wasn't lying when he said infinite context window will be solved this year. Thats it, AGI is so close.

Chubby♨️

261,843 görüntüleme • 1 yıl önce

Jensen Huang: “We have a surprising new product that we haven’t told anyone about yet. We will announce it later” If $NVDA gets into the memory game—it’ll be game over…limit down!!

Jensen Huang: “We have a surprising new product that we haven’t told anyone about yet. We will announce it later” If $NVDA gets into the memory game—it’ll be game over…limit down!!

Nicholas Mugalli

517,184 görüntüleme • 1 ay önce