Nvidia's Blowout Forecast Fuels AI Stock Rally

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00:00yeah you're absolutely correct you know solid numbers but that was to be expected

00:04single digit beats i mean no one's running out and buying stocks when you're just beating by

00:07single digits i think what's the most important thing was the messaging around 2026 here and the

00:12company came out and gave a very strong demand signal on 2026 talked about essentially being

00:19sold out on gpus supply constraint and also within that 500 trillion you mentioned you can back out

00:25this year and it implies around 320 350 billion dollars for the data center business for next

00:30year so very strong growth forecast again for next year and we needed to hear that messaging

00:35given the concerns around the ai capix bubble um that has kind of led to a correction in the last

00:40couple of weeks well jensen delivered in terms of the positivity that uh was needed both on demand

00:46and on supply are we past peak gpu pricing power um i think not yet um while the supply chain is

00:54still constrained and demand ahead of supply um they still have uh pricing power in their pocket

01:00and also on their road map once they can deliver better performance per watt going forwards that kind

01:06of leads them to better pricing so while you're constrained um i would say better pricing is set to

01:13continue so better units um from bigger supply chain and also better content due to better um more

01:20performance chips so for now we can continue to rally and the bubble talk concerns get pushed to

01:26the side but david just talking about a bubble missed the point is it more about the financial health of

01:32these ai labs of anthropic of open interest uh rather open interest is here we're not spending on

01:38open ai we're not spending on data centers as far as i know but anthropic all of them to continue to

01:42raise these giant amount of funding fundings to push into that spending is that not the real concern do we

01:48not address need to address that head on and what happens if they can't keep raising huge trillions

01:54numbers of money to continue to build out ai infrastructure yeah look essentially there's uh

02:00there's three questions we keep getting from investors right now around uh ai names number one

02:05um is um are we in the ai infrastructure bubble number two who's going to fund this to your point

02:12and number three uh ai monetization like show me the money who's making money out of this

02:17um that's front and foremost for investors at the moment and i think last night we got some answers

02:22or certainly nvidia tried to kind of address those concerns now they don't go away um but certainly

02:27kind of um eased concerns from investors and i think um you know on the first point are we in the ai

02:34infrastructure bubble i would say we are in an ai news flow bubble right now maybe not quite an

02:39infrastructure bubble there certainly is a bit of a disconnect between the two because essentially you

02:43you know we're most constrained here on power power availability that is the biggest headache

02:48for csps visit biggest headache for um nvidia and and their customers wait is power the biggest

02:53constraint or funding i mean if right now power is the biggest to spend 1.4 trillion but he only has

03:0013 billion in revenue where does he get the other you know 1.39 trillion no that's a i mean that's

03:07a good point matt and uh but you have to look over what time frame is that right i mean we're all

03:11cognizant of the fact that you know data center number two doesn't get built until data center

03:15number one gets kind of filled up essentially um so it will take time so don't read too much into

03:22that one trillion i mean that's where we're going right that's a kind of aspirational uh but in the

03:27real again going back to kind of the reality that disconnect between what the news flow would

03:31suggest and what actually can be rolled out in terms of standing up new data center capacity it all

03:36takes time and that's that that's important here as well because it gives us maybe more time to answer

03:42point three which is the ai monetization yeah like who's actually making who right now that's not

03:48microsoft you know or other big tech companies actually making real money on this yeah yeah i mean

03:54that's uh front again front and foremost for investors i would say you know we started to see kind of

04:00a split within ai into kind of um previously with the accelerated kind of ai now we're moving into a

04:07bit more uh generative ai and then next is kind of agentic ai on the first point there's already

04:14monetization there's already roi on that you can see hyperscalers for instance um social media companies

04:20better click-through rates uh better market share more screen time for users so that is that is a roi right

04:26there is that enough to fill the gap should funding market seize up or at least become more complicated

04:31you're already starting to see some of the fears oracle cds spreads have started to widen out uh

04:36doubling just over in the past month if that funding market disappears do these hyperscalers have the

04:42ability to get that monetization to replace it well i think on the second two points on generative ai

04:50and agentic ai we haven't seen much in by in terms of monetization of those two yet

04:55so the funding that has been done already by csp has justified the kind of roi that we've seen from

05:01essentially recommender engines but the funding that's kind of coming next year and beyond that

05:06we really need to see monetization on generative ai and agentic ai and that is where there's a big

05:11question mark and not clear exactly what those business models will look like and how much revenue

05:17can be generated off that

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