 From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. After a tough 2022, the first half of 2023 has shown impressive strength and many technology bets have paid off. For sure, investors in the so-called Magnificent 7, i.e. Apple, Alphabet, Amazon, Meta, Nvidia and Tesla have been rewarded, but sharp investors have sought alpha beyond these issues, riding the wave of secular trends in AI, cybersecurity, cloud infrastructure, enterprise software, as well as other emerging spaces like clean tech and robotics. As we enter the second half of 2023, the run-up in tech stocks combined with macro uncertainty is a lot of investors taking a cautious posture, but we believe the long-term outlook for firms that can capitalize on the AI wave remains extremely attractive as an unstoppable force. Hello and welcome to this week's Wikibon Cube Insights, powered by ETR. In this Breaking Analysis, we're pleased to have back founder and chief investment officer of Spear Invest, Ivana Dilevska, to assess the current state of the market and explore how this investor is playing AI's rising tide. Ivana, it was a pleasure to have you on. Thanks for your time. Thanks for having me, Dave. Now, before we get into the data, I want to share with the audience some performance data on your ETF. You know, during a tough 2022, you added risk and earlier this year we had you on and you looked at the semi-rebound as a leading indicator of a tech run and you were right. And you made some bets on key sectors that we're going to talk about. As you can see here, the Spear Alpha ETF year to date is up over 60%, significantly outperforming the NAS and the S&P 500, so that's awesome. I want to bring up, Ivana, your top 10 holdings and talk about your thesis, how you're investing in the current market. Here are those names, many which we cover on breaking analysis quite extensively. But before we get into the names, Ivana, please explain for the audience your fundamental investment thesis, specifically in the context of today's market. Well, Dave, thanks for having me. Our fundamental thesis is based on the fact that consumer technologies drove the prior tech cycle and now we're seeing technology embedded in every industry, whether you're looking at manufacturing, auto, life sciences, we believe the next cycle will be technology impacting every industry and transforming a lot of this traditional industry. So we're looking to play a lot of these tech trends through the value chain. So trying to find undervalued opportunities for us, valuation is very important. So we're trying to find good entry points and trying to find the winners for the next tech cycle. Oh, great. And we're going to dig into some of that, but I want to ask you about the sectors in that pie chart and some of the specific names that we show here. Let me start with semis and then move to cloud, then we'll go into gen AI, cybersecurity and talk specifically about Snowflake. You own NVIDIA and AMD, also Marvell. You were in NVIDIA before the phrase magnificent seven was coined and your fund obviously has been rewarded. Obviously the AI heard around the world has been a tailwind. In your view, Ivana, does NVIDIA, does it have a moat? How do you see the competition to NVIDIA? Let's start there. Well, David, we still love NVIDIA going into the next cycle. We believe we're in the early innings of data center spending. So you're just starting to see companies like Microsoft, Meta, Google expand their CAPEX budgets going into next year. So we believe NVIDIA is going to benefit from that they're uniquely positioned in that they were very early on. So 10 plus years ago, they started investing in AI and now they've built a leading position that it's not just the GPUs, it goes beyond that. They've built ways to use the GPUs better and they've built ways to sit on top of the GPUs that customers can use to build applications easily. So they're very uniquely positioned. They're not going to be the only player in AI and in GPUs. So you will see other competitors like AMD introduce products and you are going to see the hyperscalers develop their own products as well. However, it's very important for investors to understand that the fact that AI is coming so strong, the fact that this cycle is coming so quickly, they do, it does give NVIDIA an advantage. So basically, instead of you taking time to develop your own products, you really do have to step up and use NVIDIA's products just to not lose that tech advantage during the next cycle. What do you like about AMD? Lisa Sue obviously has done a great job managing the company. They've got AI chips coming. Their data center business actually was soft but she was quite optimistic about it. Is it their AI? Is it their ability to compete and take share from Intel? I wonder if you could elaborate. Well, I think it's both. And what I think people don't appreciate about AMD currently is that it's not just going to be spending in GPUs. And that's something we heard from Microsoft and Meta during this earning season. They're spending across the board. So even demand for CPUs like newer generation ones that run faster, it's going to be pretty strong going into next year. And I think that's something that's missed by investors. Then early feedback on their MI, the new GPU that they're introducing has been very positive. We are yet to hear deal announcement. So I think that's going to be coming in the second half. But that's basically the thesis. I think people don't appreciate enough that this is not just a GPU game. It's a broader data center spent cycle coming. Yeah, right. I mean, CPUs, GPUs, NPUs, accelerators, components from other manufacturers, it's all in play. Let's pivot to cloud. AWS, of course, announced last night, Amazon announced. And the AWS growth came in almost exactly on our $22 billion number at 12% annual growth. Andy Jassy was very, spent a lot of time sort of really discussing not only the Amazon retail side of the business, but AWS, which of course he started. It's funny, Ivana, a couple of months ago, they were calling for his head, but Jassy, we know him well and very capable manager. But we also, we actually thought the number for AWS could come in even higher than what we predicted. And we feel like we're seeing the back end of the cloud optimization cycle. And that said, customers are still being cautious about launching new projects that aren't maybe AI related. Here we're showing the deceleration of AWS growth rates by quarter. And our forecast shows that the rate of decline we think is bottoming right now, coming off of that. And we do expect that the gen AI and other spending is going to benefit AWS and other cloud providers, you know, really in the second half, but especially we see a kick up in Q4. You own Amazon, and I think you look at the cloud as a platform that supports other names in your portfolio. And we're going to talk about that in a moment, but what was your take on Amazon's quarter and what's the investment thesis on the stock going forward? Well, I think for Amazon specifically expectations were very low going into the quarter. I think people were expecting below 10% growth for AWS. And the fact that that came out above that was really the upside surprise. So I think the company did a very good job on this call explaining their positioning in AI. They explained how there is not just one layer of opportunity, which is what most people are focused on and it's the application layer, but it's really three, the hardware, the infrastructure and then applications. So, and they're really positioned well in all three. So I think if you look at them compared to Microsoft, Microsoft may be slightly ahead, but Amazon is also well positioned. And I think a lot of people did not appreciate AWS's positioning in AI. And I think that's why the stock is reacting positively. Going forward, I think there is going to be more value across the value chain. So smaller cap companies are going to benefit as well. I think that's where we see a lot of the opportunities where this optimization trend has really affected everybody across the value chain. And a lot of stocks that we cover are barely off their lows. Even with this AI hype. So I think it's going to be interesting to see how second half developed, but the fact that companies like AWS and Azure are saying that basically they're seeing bottoming in this optimization, that's a pretty positive sign for the entire value chain. You know, it's interesting. I think you're right. I mean, Amazon's always been a leader in AI, AWS, specifically with tools like SageMaker and they've got their own silicon, as you well know. I think Microsoft, frankly, has out marketed them, you know, with all the chats and the noise. And I think Jassy, it probably pissed Jassy off. And that's why he took so much time in the call because he knows that Amazon, it's early days, as you say, and Amazon has such strong chops about that. And, you know, there's a lot of discussion about where Geni is going to get done. Is it in the cloud? Is it in data centers? You know, inference at the near edge like retail stores and the far edge. And our take is, yes, it's going to take place in all of those model training in the cloud, you know, on-prem inference in low latency situations like autonomous vehicles, you invest in some of that. Not in Tesla, I don't think, but others. And out in the network where latency maybe needs to be lower, but not, you know, real time, like a cloud flare for something, for instance. Now this ETR survey data that we're showing here it underscores that all of the above premise. And not only are we seeing CapEx build-outs in the public cloud, but we're also seeing in other sort of co-low centers take like a digital realty or an equinex. So this is from a recent drill-down survey that shows kind of a mixed picture to the question is where will GenAI work at done? Cloud is the best tooling, but organizations are concerned over IP leakage. We don't believe that the narrative that only 10% of the work has moved to the cloud. We think it's much higher than that. Maybe 40 to 45%. Nonetheless, we agree there's a lot of data outside of the cloud, which are candidates for bringing AI to the data. So a lot of data is everywhere and bringing AI to the data means that not only will the cloud benefit, but also there are other opportunities. NVIDIA is going to be in many places, other semiconductor players. I mentioned cloud flare, EVs at the edge. How do you think about the idea that data is distributed and AI is going to be done in many places? Is there an investment angle there? Oh, yes, absolutely. So I do think model training will generally take place in the cloud, but all of this other inference where you do need the decision-making to be closer to the action is really going to be either on the edge or the network. So I think that's going to be something where we're going to see a lot of companies benefit. And I think cloud flare is particularly well positioned here with their large network. They're going to be able to benefit from companies trying to use compute closer to where they're trying to make the decision. Like you mentioned, retail is one example. Automotive is another example where you're not going to be waiting for data to come from the cloud. It's going to be key to have speed and low latency. You know, I want to talk about cybersecurity, but I'll share with you. We had Matthew Prince on three weeks ago at our super cloud three event. And he joked that when they first were pitching the company to investors, they went in and said, hey, cloud flare, we're an AI company. And he said, everybody just rolled their eyes. But he said, the whole thesis of cloud flare is if you can get enough of the internet data behind one platform, you can get enough data to use it to protect customers using AI. So they're actually really an interesting cyber play. And I want to talk about your cybersecurity investment thesis. I want to show you a chart here in this ETR data. I think you're going to like this because a lot of your names are in there doing pretty well. So this shows net score on the vertical axis from ETR, which is a measure of spending momentum. And the horizontal axis shows the penetration within the data set. And that 40% line, that dotted line, the red line there, anything above that is extremely elevated. Anything above 30% is also quite good. You can see all the stocks you own are above those measures. Here's the question. Last month, we saw Microsoft announce new products in the street freaked out. They thought Zscaler and Palo Alto in particular, those stocks got hit. In Microsoft, we see here in the upper right, they're a dominant force in cyber. But companies like CrowdStrike and Okta have always effectively competed with them. But it's Microsoft, so you got to pay attention to them. Ivana, what's your thesis on cybersecurity generally? And specifically, I want to talk about Zscaler, CrowdStrike, Sentinel-1, Palo Alto, Okta. We talked about Cloudflare a little bit and Datadog. You own all of those. That's right, David. So I think cybersecurity is going through a similar cycle like Cloud is just delayed by maybe three months. Decisions are made and are driven by sentiment. So we believe there is a lot of companies that are facing extended deal cycles, a lot of deal scrutiny. So there is clearly a down cycle that's taking place. But this is creating a lot of attractive opportunities. And with AI, we believe there is going to be a next cybersecurity wave where like now, the threats are going to be AI based, as well as the defenses versus like currently, we have a lot of companies that are using AI to prevent threats. So I think as we see that shift, you're going to see the next cycle for cybersecurity. And different areas are going to benefit in different patterns. You mentioned Microsoft entering the space. We believe it's going to take time for them to enter the network security space. There is a lot of data that's gone into companies like Zscaler, for example. They've been compiling this for a long time. Similarly, Cloudflare, similar situation, I think you're spot on with your comment. So these companies have a leg up and we heard from Zscaler, for example, a lot of their innovation on their end is allowing customers to train language models using the security data that Zscaler owns. So everybody is developing pretty quickly here. It's not going to be so easy for a new entrant to catch up. And I think you're spot on with CrowdStrike being able to effectively compete against Microsoft. Microsoft is really well positioned on the low end where they can basically serve their installed customer base but anytime you're looking for something better or you're looking for top tier cybersecurity solution, you're likely not going to go with Microsoft. So we believe that while this is a new entrant, they're probably going to capture some part of the market. I don't see it as a big threat to Zscaler, Palo Alto, CrowdStrike. They all have their own niches and they all have their own strengths and weaknesses in each particular end market. What about Okta? Okta's really been disappointing to us. We like the company, they've done great in identity, they're kind of ubiquitous, if you will. You know, Todd McKinnon, they went, they tried to go after that big acquisition, they made it with Auth0, $7 billion. It seems like they really didn't get the go-to-market right. But we thought on paper that it looked good to go after the developers of which Auth0 had. Okta really knocking down the enterprise, but it's been a big disappointment. Why do you like Okta? We don't know Okta currently. So we basically got involved in the company late last year when it had that big leg down when they missed numbers. Then I went out and met with them and I did think the go-to-market strategy is actually something that is fundamental and it's still not resolved. So you can't really have, even though they have a great product, you can't really have a company that can't really sell their product. So until they resolve that, I think it's gonna be a little bit in the penalty box. They have a really good product. Everything I heard about at that investor day was pretty positive except for the go-to-market. And shortly after they hosted the investor day, one of the presenters was the woman leading the go-to-market effort, quit basically a month after. So I was like, okay, let's take a break here. And at the same time, CrowdStrike had that horrible quarter where they throwed significant slowdown in billing. So that was really an opportunity to shift from one to the other. Great, my apologies. I had some old DNA because you used to own them but so you paired that up. Okay, great. That's right. Lastly, I want to get it to a name that you and I have talked about a lot at Snowflake. When we first had you on, the topic was by the dip on Zscaler, Snowflake and Koopa. I believe you've exited your Koopa position. Of course, the Zscaler is your top holding. So we just talked about that. And you've always been positive on Snowflake. So let's dig into that a bit. This chart shows the breakdown of Snowflake's net score, which is again, ETR's measure of spending momentum. The lime green represents new logos and that's compressing as is the forest green, which is the percent of customers spending more than 6% relative to last year. The gray bars are growing. That's flat spending. So that's a negative. The red is also growing, which is also a negative. That red is two parts. The pink is spending, which is down 6% or worse. That's the percent of customers. And the bright red is churn, which is still small, but it's there. You subtract the reds from the greens and you get net score, which is that blue line, which has been coming down. Now it's still above the 40%, but it's decelerated pretty dramatically. So we have to pay attention to that. Now the yellow line shows the penetration within the survey. The survey's about 1,700 each quarter. And that's the number of responses, saying we spend on Snowflake divided by that 1,700. And you can see that's sort of flattening. So look, we still like Snowflake a lot. I mean, they're smack dab in the middle of the data trend. They've still got momentum. They're moving fast in AI. They've done M&A there. They got partnerships with NVIDIA. They're making big moves to dominate the build out of data apps with Snowpark. But the survey data has been consistent in the combination of cloud optimization. You got competition from the cloud vendors and also data bricks. You got the macro economy shifting budget priorities, which impressed the company's performance and it's expensive stock. So Ivana, given the still rich valuation of Snowflake and these other factors, have you changed your outlook on the company or do you still see massive opportunities ahead? And you're going to stick with the story. We still see massive opportunities ahead. And you attended the investor day as well, I believe, and you had some great insights coming out of there. There is a lot of innovation going on and a lot of new product introduction for this company specifically. They're still very early in early innings. So you're not going to be able to see the numbers flow through to the bottom line or show up in revenues. But this new introduction, I think a lot of them are breakthrough and a lot of them are going to get pretty wide adoption. Snowpark is one example with a lot of innovation there. So we're pretty positive on the new product announcement. I think they're going to play a critical role in the AI as companies try to build out their own language models or they want to use cloud vendors' language models. I think they're going to play a critical role in this infrastructure. I think your data is also spot on on showing the decelerating trends. I think people misunderstand the Snowflake business model and given that they're consumption-based, they're really the hardest hit out of everybody or all the other players we focus. So they're the most cyclical company in our coverage universe. So people buy credits, they don't have to consume them, they can scale down, they don't have to buy another set of like large block of credits, they can buy them slowly. So there is a lot of ways where companies can reduce their credit usage for Snowflake, which is what your data shows and it's spot on. Now, if you look at the commentary from the cloud vendors, like AWS is particularly important for Snowflake, once you see those bottom, I think that's the next leg would be to see Snowflake's numbers bottom. So I'd be curious to see this data next quarter, how it's tracking. I think there was also like some one-offs there with few customers changing their data retention policies and one-offs can really shift the numbers like on a quarterly basis and really make the quarter appear much worse than it actually was. I don't think companies are broadly changing data retention policies. I think people are trying to retain more data, if anything. So I think this was also like exacerbating already a pretty bad environment for the stock. So I think expectations are very low right now. And I think that it's pretty well positioned for second half. So it's actually one of our higher conviction ideas here as we go into second half. Yeah, thank you for that. And obviously have a lot of confidence in management. There's something else I want to pose. And as you go out and you do your, you do the deep value chain research and you go out in the channel, you talk to a lot of people. Something that I think you said is really important. It's a consumption model. People get credits and they can hold off spending those credits and they can dial down their consumption, save money, maybe put it elsewhere. And I would say this is a premise on Snowflake. They are a value play. They sell value. And right now they've got some perceived pricing issues where a lot of companies don't want to necessarily do the hardcore data engineering work inside of Snowflake because they perceive it as too expensive. So they're going out to Databricks. So using the Spark engine or maybe there are other older legacy sort of systems that they have and that potentially is hurting Snowflake on a tactical basis because they are perceived as expensive. But eventually that spending will come back as both the market comes back and they start to drive more apps, data apps and Gen AI. I don't know if you've seen or heard any of the sort of customer issues around pricing. I have not heard a lot of issues about pricing and pricing pushbacks. And I think during their investor date they did highlight Snowpark as actually being very cost effective. So I am going to look forward to getting more data points on this front, right? Like to see whether really like their select use cases where there is such a big price advantage to Snowflake or is it really just like a few one-offs that the company is talking about? But I think there was one interesting point that came out of the investor that while it's perceived as more expensive maybe if you dive deeper, it's actually not. Right, and so the other piece of our premise is that Snowflake as you know bundles in the AWS cost along with it. Whereas for instance, Databricks does not. So I think a lot of customers see that and say, oh wow, our cloud bill is X and then by our Snowflake bill is high, our database cost and a penalized Snowflake for that. So that's something that we're watching closely and we'll come back and maybe you and I can talk about that in a couple of quarters. All right, let's end with the outlook for tech in the near long-term. So there's a mix of good and bad news, right? The Fitch downgrade finally came. There doesn't appear to be a looming recession but that might mean the Fed tightening is going to continue, wage growth is moderating but it's still high. FTC, Lena Kahn wants to kill big tech and you got an election year ahead with mixed reviews and the candidates just to say the least but all that said, the markets have seemed to shrug off any bad news and when there's positive news, like today, you look at Apple misses but tech is up because Amazon looks good and people are excited. So generally earnings estimates have been met but much of that is due to conservativism and then there's the AI which is sort of lifting tech and giving us the promise of productivity gains but the market, Ivana, has run up a lot. So are you adding risk in this inflated cycle because the best of AI is yet to come? Are you waiting for better entry points? Where are you at? So we're fully invested generally and I think we're looking at it historically. We're on a pretty risk on that up going into second half. What gives us confidence is earnings. So once earnings bottom, stocks bottom and depending on the trajectory of earnings that will determine the slope of the recovery but I do believe we're in a recovery. So this earnings season, companies have reported pretty strong numbers overall. Some of the stocks reacted more positively like AWS where expectations were low or Amazon where expectations were low. Some were already priced in like Microsoft was a good example of that but you're still looking at the second half and the earnings trajectory and surprises is still levered more to the upside than the downside in my opinion. So we follow basically now that valuations have reset lower post this tech bust, right? I think the key will be which companies will surprise on earnings and which ones will have downside going into second half but broadly we see more upside than downside. Awesome, well listen, it's been great having you on. You do some awesome work, follow. Your Twitter is what at spear invest, is that right? Is that your spear? At Ivana Spear, yep. And at Ivana Spear is your personal one. Actually you'll get good information about them but at Ivana Spear where you put out some really detailed you also write on Seeking Alpha, so check that out. Good to see you again. Thanks so much for coming on. Great seeing you, Dave. Thanks for having me. You're welcome. All right, I want to thank Alex Morrison who's on production and manages the podcast and Ken Schiffman who's going solo flight today, Kirsten Martin and Cheryl Knight get the word out on social media and in our newsletters and Rob Hof is our editor-in-chief over at Silicon Angle. Remember all these episodes, you can get them as podcasts, just search Breaking Analysis podcast, it's doing great. Please subscribe, thanks for all your support. I publish each week on wikibon.com and siliconangle.com. David.Valante at siliconangle.com is my email at dvalante is Twitter. Comment on LinkedIn posts and definitely check out etr.ai, some really great survey data they tend to be ahead of the game. This is Dave Vellante for theCUBE. Insights powered by ETR. Thanks for watching and we'll see you next time on Breaking Analysis.