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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, on supply of HBM bits: "We don't have enough bits. We are constrained in HBM memory, LPDDR memory. We are constrained in every part of the supply chain."

Nvidia $NVDA CEO, Jensen Huang, on supply of HBM bits: "We don't have enough bits. We are constrained in HBM memory, LPDDR memory. We are constrained in every part of the supply chain."

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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."

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403,365 просмотров • 6 месяцев назад

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

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50,630 просмотров • 5 месяцев назад

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

247,492 просмотров • 3 месяцев назад

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

89,906 просмотров • 3 месяцев назад

Elon Musk says memory is the limiting factor and demand is growing 200% a year while output is growing 20%, so prices go up, not down -- $SPCX Q2'26 earnings call "The limiting factor currently is memory. The memory output is increasing by around 20% per year." "Now, normally that would be fantastically fast and amazing for any large, mature industry." "But ask yourself, is the demand increasing by 20% a year?" "No, the demand is increasing by 200% a year, maybe higher." "So if you've got demand increasing much faster than supply, then Economics 101 would suggest that the price increases. "It does not decrease."

Elon Musk says memory is the limiting factor and demand is growing 200% a year while output is growing 20%, so prices go up, not down -- $SPCX Q2'26 earnings call "The limiting factor currently is memory. The memory output is increasing by around 20% per year." "Now, normally that would be fantastically fast and amazing for any large, mature industry." "But ask yourself, is the demand increasing by 20% a year?" "No, the demand is increasing by 200% a year, maybe higher." "So if you've got demand increasing much faster than supply, then Economics 101 would suggest that the price increases. "It does not decrease."

Fireside Alpha

23,044 просмотров • 23 дней назад

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

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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 просмотров • 6 месяцев назад

MICRON $MU CEO IS LITERALLY TELLING EVERYONE EXACTLY WHAT TO BUY: He says that memory supply will not catch up to demand until atleast 2028. Memory companies are priced at commodity multiples like the demand will stop this year or next year. That is not the case, and the Micron CEO is shouting it.

MICRON $MU CEO IS LITERALLY TELLING EVERYONE EXACTLY WHAT TO BUY: He says that memory supply will not catch up to demand until atleast 2028. Memory companies are priced at commodity multiples like the demand will stop this year or next year. That is not the case, and the Micron CEO is shouting it.

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$INTC CEO on memory, live on the earnings call: "the memory [has] become the big supply constraint challenge, and we [are] collaborating with the three big memory vendors. ... Clearly memory, it [has] become the bottleneck [for] a lot of AI infrastructure and pinpoint for customer." $MU $SKHY $DRAM $SNDK

$INTC CEO on memory, live on the earnings call: "the memory [has] become the big supply constraint challenge, and we [are] collaborating with the three big memory vendors. ... Clearly memory, it [has] become the bottleneck [for] a lot of AI infrastructure and pinpoint for customer." $MU $SKHY $DRAM $SNDK

Trade Whisperer

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SK Hynix's Hoshik Kim admits high bandwidth memory "is not the answer" to the memory-wall problem, and SK is working on different solutions to solve the bottleneck. "No, actually, I kind of agree with Pat. So HBM is not the answer." [SK Hynix is admitting that HBM is a bad memory?] "Nothing is a bad memory. It's a good memory, but it's not the final answer. So actually, HBM will not solve the memory-wall problem. Memory-wall problem is an inherent AI problem, which you cannot avoid." "So we try our best to provide higher bandwidth with this memory, with HBM technology even though it has some limitation, as Pat already mentioned, with thermal, IOs, cost, a lot of stuff. "But that's the only thing we got right now to help ease this memory-wall problem, memory-bottleneck problem. But at the same time, we are working in different directions to solve this memory-wall problem with different solutions."

SK Hynix's Hoshik Kim admits high bandwidth memory "is not the answer" to the memory-wall problem, and SK is working on different solutions to solve the bottleneck. "No, actually, I kind of agree with Pat. So HBM is not the answer." [SK Hynix is admitting that HBM is a bad memory?] "Nothing is a bad memory. It's a good memory, but it's not the final answer. So actually, HBM will not solve the memory-wall problem. Memory-wall problem is an inherent AI problem, which you cannot avoid." "So we try our best to provide higher bandwidth with this memory, with HBM technology even though it has some limitation, as Pat already mentioned, with thermal, IOs, cost, a lot of stuff. "But that's the only thing we got right now to help ease this memory-wall problem, memory-bottleneck problem. But at the same time, we are working in different directions to solve this memory-wall problem with different solutions."

Fireside Alpha

140,571 просмотров • 1 месяц назад

🚨 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

3,026,154 просмотров • 3 месяцев назад

Dylan Patel says the memory shortage is not a normal cycle "Memory capacity is only growing 20, 30% a year for the next three years. And yet, demand is doubling, is doubling...memory prices are going to keep soaring." "Our point there was memory isn't a shortage, and this is not a short-term shortage. It's a shortage that's going to last years." "Memory we've had the pricing go up like 4x and it's going to go up another 2x, 3x again, in addition to capacity growth. We talked about how KV cache was going to explode because of reasoning. And therefore memory was going to be the biggest winner." "We're still not at 85, 90% gross margins for memory, but we'll get there. And then at some point from there, it'll also halve back down to like 70s or maybe even lower."

Dylan Patel says the memory shortage is not a normal cycle "Memory capacity is only growing 20, 30% a year for the next three years. And yet, demand is doubling, is doubling...memory prices are going to keep soaring." "Our point there was memory isn't a shortage, and this is not a short-term shortage. It's a shortage that's going to last years." "Memory we've had the pricing go up like 4x and it's going to go up another 2x, 3x again, in addition to capacity growth. We talked about how KV cache was going to explode because of reasoning. And therefore memory was going to be the biggest winner." "We're still not at 85, 90% gross margins for memory, but we'll get there. And then at some point from there, it'll also halve back down to like 70s or maybe even lower."

Fireside Alpha

140,492 просмотров • 1 месяц назад

$MU is pushing back on the idea that memory is heading toward overbuild with CEO saying “We see no end when supply catches up with demand.” That confidence is backed by 5-year customer agreements committing to take Micron’s supply with options to extend even further.

$MU is pushing back on the idea that memory is heading toward overbuild with CEO saying “We see no end when supply catches up with demand.” That confidence is backed by 5-year customer agreements committing to take Micron’s supply with options to extend even further.

Shay Boloor

145,225 просмотров • 4 дней назад

$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

125,563 просмотров • 3 месяцев назад

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

149,504 просмотров • 2 месяцев назад

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 просмотров • 3 месяцев назад

Memory supply and demand won’t find parity until 2030 (or later) and with new AI powered innovation in and out of the datacenter the constraint will remain giving memory names asymmetric pricing power for a prolonged cycle that is still at its beginning.

Memory supply and demand won’t find parity until 2030 (or later) and with new AI powered innovation in and out of the datacenter the constraint will remain giving memory names asymmetric pricing power for a prolonged cycle that is still at its beginning.

Daniel Newman

28,092 просмотров • 1 месяц назад

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 просмотров • 2 месяцев назад

$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 просмотров • 3 месяцев назад