What's Up With Tech?

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Sara Awad from Tech Contrarians talks tech’s tough year (0:40) Great results being viewed as not good enough (3:20) Semiconductors have more downside, but potential remains (6:50) Memory dynamics (8:40) Thinking about 2027 (14:50) ASIC shift favors ARM (19:45) Are we in a bubble? (23:30)

Transcript

Rena Sherbill: Very happy to welcome back Sara Awad from Tech Contrarians, and a new podcast she’s gonna tell you about at some point too. Sara, welcome back to the show. Really great to have you as always.

Sara Awad: Yes. It’s always great to be here. It’s a pleasure to speak with you, Rena. Thanks for having us on again.

Rena Sherbill: It’s always great to talk and always great to talk tech, especially well, I mean, I think I say that every time, especially these days, but as questions continue to unfold about the strength of the AI trade and various players, what would you say to investors right now?

Sara Awad: I think what investors are I think dealing with this year is a bit of a tough situation, right? Because it’s really been an interesting year. We had Q1 was a bit of a lull and then Q2 was a huge rally with the stocks going up eighty seven percent, a little over eighty-seven percent.

And then Q3 starts, second half of the year begins, and then we have this downturn, right? It’s a lot of profit taking, a lot of fear. We switch from this greed sentiment to a fear sentiment and then we’re seeing the market kind of struggle back and forth with it now.

And I think last time when we spoke, that was around maybe mid-May. That was essentially mid the entire rally that happened in Q2. And what we were discussing is that in the rally everyone looks like a winner. But not everyone’s gonna come out of a correction as a winner.

And I think that’s really what’s becoming more pronounced in Q3. So the names that we saw as high flyers in Q two are actually some of the underperformers in Q three and vice versa.

So if we take that and you know, we think about the switch between first half and second half, you really see that kind of dynamic materialize.

And alongside it, this theme in which earnings are acting more as a test rather than a catalyst, specifically after that Q two run, everything is kind of coming out as not good enough.

I think that’s a theme to be really cautious of and sensitive to. I mean, we saw (TSM) report great results, we saw (ASML) report great results and you know even raise their outlook. we saw Samsung (SSNLF) report a nineteen-fold increase in profit, and all three still traded down. I think what we’re seeing is a hypersensitive market in which everyone is waiting for the other shoe to drop and I think we let out some steam since the beginning of of Q3, specifically on the semi-front.

But it seems that the market is still in limbo and also dealing with new red flags from the circular financing to the Chinese competition. So they’re just dealing with new realities.

A lot of these red flags existed in Q two, but I think they’re getting a lot more attention in Q three.

Rena Sherbill: Does it make sense to start with the red flags, or does it make sense to ask the question about the companies that do seem to be doing, in your words, good enough? Is it truly good enough? Like will it turn back around? How would you describe it in context given that the reaction in the investor community reaction hasn’t necessarily been reflective of what’s going on with the stock?

Or would you put stocks in the even better category that have been reflected in investor sentiment being positive?

Sara Awad: I think, and let me know if I understood the question right and I’m answering it from from the right angle, but I think a big part of what we’re seeing is this this theme of great results being viewed as not good enough is because in Q2, the market preemptively priced in a lot of the positives to come and didn’t really pay attention to the fact that at the end of the day, what we’re talking about is a semi-rally. And at the end of the day, we’re talking about components and a supply chain in which there’s a shortage. and even if

From our perspective, we believe that this shortage is a supply chain-driven shortage rather than an end-demand-driven shortage because we know that you know PC TAM and smartphone TAM are expected to contract by double digits this year. So end demand is pretty weak. even though we think this is a supply chain-led shortage, the idea that so much of the positive news got preemptively priced in in Q2 made it so that by the time we got

To earnings in Q3, there was a combination of the results didn’t look good enough against what was priced in. Investors were looking for more. And simultaneously, you know, when we entered Q2, expectations were pretty low. And we were entering Q3, it’s a different kind of expectation game. So that really does shift a difference. And then turning back to the supply chain factor in all of this, at the end of the day, there are physical constraints to achieving more financial upside. Right? You have components, and we see this really clearly with the optical guys.

There’s a ton of demand, but there’s not enough supply. There’s a lot of bottlenecks within the semi-industry at the moment. So there’s physical constraints that really prevent further upside that has already been priced into the stock. And I think that’s part of what we’re seeing get reset right now. and so it even when we look further out, I don’t think that we’re gonna see necessarily the this you know AI bubble pop conversation happen in the second half. we’re thinking about that more for, you know, twenty twenty seven, first half of twenty twenty seven around then.

But what we’re seeing in the second half is the semi-correction. And a lot of it is because the supply chain inflated a lot of the the pricing. A lot of the pricing went up because of this idea that there’s a shortage. So there’s a lot more leverage for these guys in the semi-supply chain to raise prices. That made their financials look extremely good in Q2 against what is a weak end demand environment. And then by the time that Q three comes around, you don’t, you know, you have more pricing leverage, but then that begins to wane as end demand becomes more pronounced as a negative.

So that’s kind of how we’re thinking about it in terms of how investors should view these earnings. a big part of what we’re seeing get reset are the expectations that preemptively got built up in Q2 and now are being digested against reality. and at the same time, and I I would say that’s healthy, right? Because everyone knew in Q2 that this can’t last. And that’s why we saw such a mechanical shift, I would say, between Q2 and then Q3. But then looking into the second half, I don’t think that this is the end of it, right? The the socks.

Being down, I think it was as of this Monday at roughly 13%. I don’t think this is the end of this semi-correction. Instead, the way we’re looking at it is in the second half of the year, we’re gonna see, you know, we’re gonna see semi-semis correct bay as the the price increases in the supply chain also rebalance against the reality of end demand. So we saw a lot of double ordering, in our opinion. We’re seeing a lot of customer pull-ins out of

fear that this there’s shortage and and you know, you can’t get components and you need to get components for the outlook that you’ve guided and for the expectations that Wall Street is kind of holding now against the semiconductor industry. Does that do I hope that helps answer that question?

Rena Sherbill: I think as we continue to have the question and answer unfold, would you does that mean that semis are a hold right now? How are you looking at the semis? And are you looking at them as a group? Are you looking at any individual stocks separate from that group, if so?

Sara Awad: I would say that in general I think there’s an overarching kind of blanket on the semis in which we are gonna see this, we’re gonna see the (SOXX). I think it has more downside to come. That doesn’t make us, you know, ignore the semis entirely.

Instead, I think there’s a lot of potential still on the table in the semiconductor industry. But the idea is that you wanna think about the guys who s who have more balanced expectations around them.

And so for example, and and you wanna think about the guys with more balanced expectations and equally as important, you wanna stay away from the the companies that have, you know.

Where the where the narrative has run ahead of where reality can can really achieve that upside. And that when I say that, I think mainly of memory, right?

I think part of what we’re seeing is that the AI narrative this year is going to is has in large been built on that dynamic of the supply chain-led shortages. and that really did prop up a lot of specific players as the winners. I think as we see these price increases moderate in the second half, or there’s less leverage for price increases as inventory builds up.

We’re gonna see a lot of expectations or the financial performance around these players that got propped up by these price increases come down. And that’s where, you know, memory is is center focused for us because I think when we last spoke, memory was it was we were mid-May, memory was gaining a lot of traction.

Micron during Q2 entered the one trillion dollar club. And a lot has happened since, in the sense that a lot has happened to unpack the this bull narrative around memory in which memory is regarded as no longer cyclical.

So we saw the three big DRAM guys report since the last time we spoke, we had SK hynix (SKHY) come to the US market.

And I want to highlight in specific Micron’s results, I think they underpin this kind of dynamic. So if there’s a company that I would stay clear of in the second half, I think it would be the memory kind of sector because I think those guys are at the highest risk because memory is the component that increase the most in terms of of price.

And I thinkm was most misunderstood by the market in terms of what was driving this mem memory rally. and I think we touched upon this briefly in May, but I’d love to get into it a bit more.

Rena Sherbill: Yeah, please do. Please do.

Sara Awad: Essentially so a couple of things to get to here, right? So the bull argument is that memory is no longer cyclical, but all the data points since you know since Q2 until today actually point to the exact opposite, right?

I think there’s three main ones to point out here.

The first is SK hynix coming out in, I think it was late June, on what’s being what’s you know looked at or called Black Tuesday and saying that, hey, we’re gonna reallocate capacity, manufacturing capacity from HBM to general purpose DRAM.

And SK hynix has the largest share in the HBM market, around something like 58%. And so them saying that we’re gonna shift from HBM, which is you know the hot AI memory, to general purpose DRAM is essentially highlighting this idea that general purpose DRAM is where the money is.

And we already know this from Micron’s own CEO when he noted that on the earnings call that I think this was in December, that non-HBM gross margins, not in December, sorry, I think it was it was in Q2, non-HBM gross margins are actually higher than HBM gross margins. So SK hynix making that shift as the largest shareholder in HBM does underpin this idea that they’re following the money, right?

And so I think that helps break down that that misunderstanding the market had on the memory trade. And then the other part of that equation is that SK hynix adding more supply, more DRAM supply into the market actually has the impact of reducing the ASP leverage that’s happening right now on the DRAM front.

So to take it back a minute, the reason why we think memory kind of popped and Micron had these great run and great outperformance, huge margin expansion, we don’t think that happened because of HBM.

We think that happened because of the non-AI side of the memory, because of general, you know, general purpose DRAM spot prices going up insanely high.

And we think that’s what underpinned the gross margin expansion from Micron, in which they guided to I think it’s 86 for next quarter, and they printed 84.6 for this quarter. So they’re really benefiting from the higher ASP on the DRAM side.

So just going back to the quarter they reported at the end of June, their DRAM sales grew 67% sequentially. And that was driven mainly by a 62% in ASP and bit shipments, on the other hand, we’re only up 2%. So it’s really highlighting the results are telling us that the growth is coming from pricing.

And if we believe that memory is cyclical, and it’s you know historically proven to be cyclical, if we believe that memory is cyclical, then at the end of the day, when you have a shortage, you’re gonna have higher, higher pricing, high ASP.

But then when supply begins to catch up to demand, what you’re gonna have is that you’re gonna lose that ASP leverage. And so as SK Hynix shifts supply from HBM to DRAM, that’s gonna create a lot more output on the market.

And where it becomes a bit more technical is this idea that HBM has tripled the diet size of DRAM.

So when you shift capacity from HBM to DRAM, you actually have your output increase at a much faster pace. So we’re talking about a lot more supply in the market.

And so more supply in the market means you lose this ASP leverage. And that means that we’re looking at microns, gross margin trajectory that’s been something like a dream, right? 86%. That’s the highest gross margin there is in the semiconductor industry.

That’s even higher than NVIDIA (NVDA) at its peak, which is crazy. We’re looking at that that gross margin expansion, moderating, or even U-turning back to more, I would say, realistic levels.

And so that’s just one factor of how we’re looking at memory and the risk there, thinking about what names we’d be cautious of in second half.

The other factor is the Chinese DRAM supply also entering the market with CXMT IPOing in China and then also talking about adding 85,000 wafer starts per month of DRAM. That’s compared to SK Hynix adding 60,000 a month and MU adding 30,000 a month, and Samsung (SSNLF) adding 50,000 a month.

And I specify these three because they’re the largest DRAM players. So the idea is that CXMT is actually gonna be looking at an output of 350,000 wafer starts per month by the end of the year. And that puts it within, I think, roughly a 25,000 range of microns own output.

So if we’re seeing more supply from SK Hynix, we’re seeing more supply from China DRAM, and we’re seeing guys like Apple (AAPL) shop for Chinese memory and lobby at the Pentagon to be able to use Chinese memory, Chinese DRAM.

I think this sets up the kind of conversation in which we’re looking at more supply. The shortage will ease, ASP leverage will come down.

And then to add just a cherry on top here, Trend Force is expecting now DRM contract pricing to moderate to 13 to 18% growth in Q3 this quarter, as opposed to what we saw in Q2, which was 53 to 63% growth.

So I think that the conversation on memory, and we were early definitely on Micron on the downgrade, but I think that we’re seeing our thesis play out now. I think the conversation on memory is beginning to become more pronounced.

I mean Q2, no one was talking about the red flags in memory. And in Q3 we’re seeing a lot more conversation about that. So I think it reaffirms what we discussed back in May.

It also I think speaks to looking at the second half as the supply comes online, a more risky dynamic around memory.

Rena Sherbill: Could you share more of how you see the coming months and the coming year playing out vis a vis the different lanes in tech?

Sara Awad: Yeah. So I think when we we’re thinking about the second half and then we’re thinking about twenty twenty-seven, I think a big part of what we’re seeing is the AI, AI is maturing and it’s segmentizing.

And this is a theme that we’ve been watching for a while and I think we discussed on this podcast before. And as AI matures and segmentize, what we’re seeing is that we’re shifting from this conversation of token maxing to token efficiency.

This is underpinned by this idea that earlier this year and even last year, everyone was pushing for enterprises, for individuals to use AI as much as possible, right?

Even Uber (UBER) was pushing employees to use AI as much as possible, and then they blew through their budget in the first four months of the year.

So what we’re seeing is that compute is not free, but AI is free. A lot more of the end users and enterprises are beginning to become more cost conscious.

We’re entering a more cost conscious, I would say, phase of of the AI boom or the AI cycle.

As we enter this more cost conscious phase, I think the conversation is a lot more about what kind of solutions you’re using for compute. So we have AI GPUs, NVIDIA still dominates the scene and Vera Rubin is coming up and the demand from all of our data points looks really great on that front.

Very strong demand. Case in point, Google (GOOG) (GOOGL) and Tesla (TSLA) haven’t spent the majority of their full CapEx. And I think that’s part of what we’re gonna see go fully to Vera Rubin and into NVIDIA’s pocket with the ramp of Vera Rubin and into the second half and then early ’27.

But what we’re seeing is that because of the the AI conversation is much more cost conscious, we’re seeing more hyperscalers gravitate to lower cost compute solutions.

And that’s where ASIC comes in. So I think as we think about you know second half of this year, I think Vera Rubin is really gonna dominate the scene, but then in 2027, I think ASIC is going to become a much bigger part of the inference market because you need to focus on how can you get the lowest cost solution to power what you’re doing?

And this becomes even more, I would say, important with the dynamics that we’ve seen kind of play out over the past two months from Chinese competition entering the scene.

So it’s kind of like we had a a Deepseek moment revival when Moonshot’s Kimi K3 came out last month, because you know, we’re seeing China really compete with US frontier models on performance, but massively undercut them on price at a time when the market as a whole is very conscious about all this AI capex spend and whether or not we’re gonna see this AI return on investment and how these hyperscalers can show that.

So it became a very, I would say, tangled web in which the US frontier models, for the hyperscalers to remain meaningfully competing and being able to show a return on their investment, they need to make sure that their their compute is at the lowest cost possible.

And so that’s what ASIC I think is gonna really provide. And we’re I think, again, at the top of the ASIC race is Google with their TPUs. Not only that they use for their internal use and then they rent out to others, but also that they’re now as of this quarter selling full TPU rack systems.

So I think Google has executed the best on that front and now we’re seeing Amazon be a close second. And then Meta and Microsoft are really trying to to catch up.

OpenAI (OPENAI) is working with Broadcom (AVGO) on their own ASIC chip. Anthropic (ANTHRO) has plans to to work on its own ASIC chip. So we’re seeing this kind of shift in terms of a shift to lower cost solutions as the the idea that you need to get the lowest cost solution for compute available.

I think that’s a big part of where the conversation headed. So looking into 2027, that makes us a lot more, I would say, cautious on NVIDIA, because I think NVIDIA has the most to to lose from the switch to this shift towards more ASIC adoption.

Because now for the first time ever, NVIDIA’s gonna have to be forced to share a part of the AI accelerator market with ASICs, right? From a eighty to ninety percent, those are the current estimates, eighty to ninety percent market share is is gonna be pressured.

And so I think that’s what keeps us more on the sidelines of NVIDIA, thinking about it into next year. Because at the end of the day, I think the AI Capex is gonna have to be spent across all of these players.

I just wanna emphasize that’s where we like guys like Marvell, right? ‘Cause when these hyperscalers are going for ASICs, they’re multi-sourcing. No one wants to have all their eggs in one basket.

Similarly to how they were forced to have all their eggs in one basket at the beginning of the AI boom with NVIDIA. So everyone is trying to multi-source. Google went with Broadcom, then Media Tech and then Marvell (MRVL).

And now we have new ASIC players entering the scene like Qualcomm (QCOM).

So I think that’s where the 2027 conversation is leading towards. So that’s where I would pay attention for investors kind of trying to gauge how to think about the semis for for next year.

Rena Sherbill: Much appreciated. Any other stocks or notes to mention?

Sara Awad: Yeah, I would say part of that ASIC conversation I think really favors part of that ASIC shift really does favor ARM (ARMH) because ARM-based CPUs are actually, I think they’re the best fit for the ASIC conversation because they have the lower power consumption, which is increasingly important in the AI infrastructure build out.

And I think ARM CPU are already embedded into a lot of the the tier one players via, you know, ARM’s designs.

So I think that we’re gonna ARM be the favorite choice on that front. It’s not to say that the X86 market where Intel (INTC) and (AMD) have their playground, it’s not to say that these guys aren’t gonna benefit, but I think ARM is gonna be the winner from that theme.

Both the ASIC theme and then this agentic AI theme. Because at the end of the day, ARM is was the first to show us what an agentic AI rack would actually look like.

Everyone else liked to talk, and there’s definitely benefit to go around, but I would say I think ARM is is the favorite choice there and the others still need to prove themselves. the other stock I think it’d be kind of worth addressing is Intel, because it also had this huge pop-out moment in Q2.

And for Intel, they had this huge you know pop-out moment. We had a lot of rumors about them getting external customers for their for their foundry business. Interestingly enough rumors that management never confirmed but that Trump did. So we we didn’t really get a lot of clarity on those.

But I would say for Intel, we’re we’re more cautious as well. we the reason why we’re more cautious is because of this last earnings call. Basically, on the last earnings call, management talked about, not on the last earnings call, excuse me, on (ASML)’s earnings call, actually.

ASML announced that Intel is using their high NA tools, their high in A lithography tools for its 18A node. and that’s that to us was a big flag, a big red flag. And the reason why is because it’s a big red flag for the foundry business.

And the reason why is because Intel was meant to use the high NA tool, which comes at a very high price, close to 400 million. It and almost you know double what a UV tool would cost. So Intel was supposed to use that more expensive tool on its 14A node rather than its 18A node.

The fact that they used it on their 18A node tells us that the yields on their 18A node weren’t the greatest, and so they needed to use this farly more expensive machine to be able to up the yields there. and so that makes us feel like there’s a lot more uncertainty about whether Intel is gonna get a meaningful external customer because any customer coming on will have to, you know, will be harming their own business if if they go to a foundry with bad yields or at least with yields that don’t compete with those of TSMC.

So that’s how we’re also thinking about the Intel foundry side of the business because we’ve been watching Intel for a sign of, you know, external customers coming on and our indicator for that was if Lip-Bu Tan decided to raise CapEx, and we still didn’t get that even as of you know this quarter. We got a very mild increase in CapEx.

I think that this underpins this idea that the Intel Foundry business it moves more on moves the stock more on headlines rather than the fundamentals. so you know we know that as of this call, you know, they’re raising their their fiscal capex to 20 billion up from 18, which which up from 18 last year, which isn’t that much more meaningful.

And they said that in twenty twenty seven they’re gonna raise it substantially, but we didn’t get any numbers. So I think this is also management kind of having a foot in the door and then a foot outside of the door because there’s some uncertainty on that front. So that makes us a bit more cautious as well on Intel in the second half after that run up that we saw in Q2.

Rena Sherbill: It strikes me that, as we close out the this conversation, and again, anything else that you feel like is worthy of investors’ attention right now, happy for you to share that.

But it strikes me that there’s often talk of this bubble in tech. I believe you did mention some bubble language at the beginning in terms of something coming to burst, but A, do you see the conversation as a useful conversation? B, do you see it as a large bubble? Do you see it as a series of smaller bubbles in different lanes in the tech sector and also at different points in the cycle, like this is a bit of a bubble and then this becomes a bit of a bubble and then they kind of even things out and return to center. How would you respond to that? Or how do you think about that?

Sara Awad: That’s a great question. I think that’s a question more people should be asking.

I think when it comes to the bubble conversation, there’s definitely a bubble and it’s growing. I think that’s without a doubt the case.

The way that we’re looking at it is basically, yeah, there’s gonna be a semi-correction second half, but then the more pronounced real bubble conversation, I think more it’s more related to AI capex, right?

And we had the bubble fears get revived when there was a really clear dynamic in which semis were being rewarded while the hyperscalers that are funding the semi-rallies were being punished for that spend.

And so then when you have China enter the conversation as well with cheaper alternatives and other models, making it so that essentially, as of now, 45 China wins 45% of US company AI use.

That puts a lot of pressure, I think, on the AI CapEx spend and the pressure from investors on these tier one players to show return on investment. So I think that’s at, you know, that’s that’s at the core of when the bubble pop is gonna really materialize.

And I think it comes more from a financing perspective. That’s I think what’s gonna really push us off the edge. and that’s you know, that’s when we think about the things that we’ve seen NVIDIA and and the broader market do and the creative ways, really the ri very creative ways that the market is beginning to try to finance this AI boom.

So we had NVIDIA and talks to provide, I think it was about 250 billion financial backstop for open AI, which is unprofitable private company with the IPO likely pushed out until next year, and rumors of missing internal targets. And we know getting pressured in terms of market share by competition from Anthropic, competition from the other Chinese models.

And then you have a conversations or negotiations for financing up to $350 billion to fill up those data centers with chips.

That NVIDIA claims is not circular financing because there’s no written commitment in which OpenAI has to buy NVIDIA GPUs, but I think it’s it’s kind of implied. and then NVIDIA stakes a bunch of the neo-cloud players, including Nebius, Core Weave, and then Iron this year.

So it looks like NVIDIA is increasingly funding its own customers. and so if we think about the circular financing structure that this creates, it creates essentially what I would say a scenario in which money moves in a loop, right? You invest it and then it gets bought out from your chips and then you invest it again and then rinse and repeat.

I think that’s where that’s that’s a conversation to pay attention to for the bubble pup because that underpins this idea of how much more money can we put into the AI infrastructure build-out. and and indeed the idea is that how much more money can we put into the AI infrastructure build out without seeing a material return on this investment, right?

Specifically that we’re seeing people like companies like Google and Amazon (AMZN) go free cash flow negative and we’re seeing guys like Meta (META) really struggle internally with their with their AI kind of narrative or their AI persona and how they want to pursue that.

So this idea I think is is what we’re seeing. And then Meta coming out also last quarter and talking about this potential in which they may be leasing access capacity is a positive for Meta. And it’s one that we forecasted in our investing group prior to the jump on that headline, but it’s one that’s actually pretty much a negative for the AI CapEx story because it opens this conversation or it asks, proposes this question of did Meta overspend so that they do have this access capacity?

We didn’t get confirmation from Zuckerberg that that’s the case, but the fact that this is now something that Zuckerberg is mentioning, even the mention of the word access capacity is a spook to this AI Capex story because it means are you did you guys overspend?

Did you miscalculate something in this? So that’s I think that’s what we’re paying attention to on the bubble front. I think that’s where it’s really gonna come from.

And then this week we had very interesting news with NVIDIA essentially partnering up with Wall Street’s six biggest lenders to establish what’s being called the compute financing platform, where they’re creating pools of capital at attractive rates for NVIDIA’s customers.

And you know, this is being framed by Jensen that chips are now an investable asset class. that entire dynamic, I think, it also speaks to this I w it speaks at very worrying environment forming because these firms are looking to deploy $500 billion when more expected to come.

And this is clearly trying to solve a problem that is the reality that spending commitments on AI infrastructure are hitting peak levels and compute is getting increasingly more expensive.

So the market is really getting creative about how to finance that. But then how sustainable is this considering that we don’t have the cleanest proof points about return on investment from these hyperscalers yet?

So this isn’t a one-off situation. I think we’re seeing an accumulation of this, and that’s why I would say, yeah, there is a bubble and it is inflating. and one data point doesn’t make a trend, but we’re not talking about one data point.

We think the bubble pop is gonna be driven by how we’re beginning to fund the AI infrastructure build out, you know, from the free cash flow to credit. and and that’s where we enter a riskier territory. and I think that’s where investors should also, that’s what they should focus on to think about the timing of the AI bubble CapEx.

I think that it’s also worth joining this conversation with China. Because I know a lot of people compare this AI bubble to the dot-com bubble, but something we like to throw into the mix is that we didn’t have China be such a prominent part of the last bubble, right?

It really is a much bigger part of today’s bubble. When we look at how this is impacting the cost of AI or the spend on tokens, essentially the cost for businesses to run AI models has fallen, as of article published this week, report published this week by Jeffries, it’s fallen to a yearly low with the surge in adoption for Chinese models, right?

And model routing and a lot of what we’re seeing on that front side. So average inference in prices are now ranging between a dollar sixteen to a dollar eighteen in August.

And that’s down from two dollars and four cents to one dollar and forty-five cents between May, end of May, and then mid-July. So the price decline really does emphasize this idea that we’re we’re in a a phase of AI that’s much more cost conscious, and that’s why we’re seeing this have a ripple effect through the entire semiconductor sector and I think through the broader AI theme.

And I think that’s really important to to pay attention to because the LLM token expenditure expenditure index is actually coming down.

So people are spending less to use AI, but compute is still, we’re still seeing over 740 billion spent on AI CapEx. So there’s this mismatch that needs to reconcile.

Rena Sherbill: Appreciate it as always. For those wondering, you can find out more from Tech Contrarians on Seeking Alpha. You can find out much more about the tech sector on Tech Contrarians on Seeking Alpha. Anything else to add to to this conversation?

Sara Awad: The one last thing I’d love to jump in and and add is that I’d love to tell everyone that we’ve launched a podcast called the Tech Talk on our Tech Contrarians page and we do two kinds of episodes there.

One in which we bring on an industry-driven perspective on specific parts of tech or the periphery of tech. So we started off actually with an episode on SpaceX (SPCX), bringing on Jeff Foust and Jason Rainbow, two experts on the space industry. They’ve been covering it for each well over a decade.

And the second kind of episodes we’re launching there are we’re calling them bulls versus bears. And that’s where we’re hoping to bring on two Seeking Alpha analysts with opposing views on the same stock, to to really talk through it and give the investor community kind of both aspects of a bull case and a bear case confronted against one another.

Rena Sherbill: Nice. You know, we did that on this podcast a couple times. We did it on Tesla and another one, I think maybe Exxon. I love the idea and that sounds really exciting.

Sara Awad: Really? That’s awesome. I mean Rena, you’re our inspiration, if I’m being completely honest. So yeah, you make it look so easy. So we’re hoping to provide some value similar to the value that you’ve added to so much of the Seeking Alpha investing community.

Rena Sherbill: Stop stop, thank you. I appreciate it. Again, where can people find the podcast? Your podcast?

Sara Awad: Yeah, so it’ll be on the Tech Contrarians page. Feel free to check it out and feel free to visit our Investing Group and hop on a one on one call with us. That’s the community’s favorite feature, I like to say. And so feel free to join the group and jump on a call.

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