u/KeyTrainingk

I keep coming back to the same question with NVIDIA: at what point does an incredible business become an expensive stock?

The latest numbers are honestly hard to argue with. NVIDIA did $96.2B in revenue in Q2 FY2027, up 106% year over year, while Data Center revenue hit $89B, up 117%. Gross margin was still 75%. Management is guiding for another $108B in revenue for Q3, even without assuming any Data Center compute revenue from China.

And the next leg of the story is already starting. Vera Rubin is ramping into production, and NVIDIA expects fiscal 2028 revenue to grow roughly 70% year over year. That is a pretty wild forecast for a company that is already enormous. Management also says supply, especially memory, could remain a bottleneck through FY2028.

Then there’s the $150B increase to the buyback authorization announced in September, bringing the remaining authorization to $235B through FY2028. That tells me management is pretty confident about future cash generation.

The stock is around $237 right now and recently pushed back to record highs, with a market cap around $5.7T. Depending on the data source and estimate period, NVDA is trading around the mid 20s on trailing earnings and roughly 20 to 25 times forward earnings. That sounds expensive in absolute terms, but it also looks surprisingly reasonable if NVIDIA can actually sustain anything close to the growth it's currently projecting.

That’s where I get stuck.

The bull case almost writes itself. AI spending is still accelerating, Rubin gives NVIDIA another major product cycle, CUDA and the broader software stack keep customers locked in, and demand is spreading beyond the traditional hyperscalers into AI labs, enterprises and sovereign AI projects.

But the bear case isn't really “NVIDIA is a bad company.” It's more about expectations.

At a $5T plus valuation, NVIDIA doesn't just need to keep growing. It needs to keep growing at a rate that makes the current valuation look cheap in hindsight.

What happens if AI infrastructure spending eventually normalizes? What if hyperscalers start getting more disciplined about returns on all this capex? What if custom accelerators from Google, Amazon, Microsoft and others take a bigger piece of the workload? And how much should we worry about margins falling as memory and other component costs rise?

NVIDIA itself expects gross margins to fall toward 71% to 72% in Q4 before recovering somewhat later. That's still an incredible margin for a semiconductor company, but it shows that even NVIDIA isn't immune to the economics of scaling this fast.

Personally, I'm still bullish on the business. I'm less convinced that the stock is automatically cheap just because earnings are growing so fast.

The interesting part is that both sides can be right. NVIDIA could become an even more dominant company over the next five years and the stock could still have periods of disappointing returns if expectations get too far ahead of reality.

So I'm curious where everyone lands on this.

At around $237 and a roughly $5.7T market cap, do you think NVDA is still reasonably valued based on the growth ahead, or has the market already priced in too much of the AI story?

And what do you think is the biggest thing that could actually break the NVIDIA bull case over the next 12 to 24 months?

Hey everyone, glad to find the FIREyFemmes community. I haven't been on Reddit that long, but I have been reading posts about FIRE journeys and financial planning and it seems like a really great place for conversation

I am from Ohio, 42 years old, and working toward Financial Independence myself. Over the years learning about investing and managing money has made me realize FIRE is not just about the numbers, it is about having the freedom to choose how you live

Wondering if there are other women from Ohio or the Midwest in here. When did you start your FIRE journey? Are you more focused on growth, early retirement, or building a more flexible lifestyle?

Excited to connect with everyone. Sharing personal experience not financial advice

Hi,
I’m a 32 year old woman looking to connect with someone who’s genuinely interested in simple, everyday conversation. Nothing complicated. Just someone consistent to talk with about daily life, work, little things that happen during the day, or random thoughts. It would be nice to keep in touch naturally and casually, just checking in when we both have time and chatting a bit. If you feel the same way, feel free to message me 🙂

MU experienced significant volatility today. During the intraday plunge, sentiment immediately plummeted, and many probably thought it was entering a weakening phase. Interestingly, it didn't break down directly; there was consistent support below. It did fall, but there was a sense of "someone catching it," preventing it from spiraling out of control. Then, it was slowly pulled back up, ultimately closing in positive territory, which was quite unexpected

If it were a truly weakening stock, it would be very difficult to recover after a drop, but MU today seemed to have been slowly supported after the initial plunge, remaining in a consolidation phase without a clear trend reversal.

I bought some calls before the close, feeling that if it were truly weakening, it wouldn't have recovered like this, so I wanted to bet on a continuation tomorrow. The key questions are whether the low can hold and whether the momentum can continue, rather than just a brief surge. If it continues to be supported, then the sentiment from this AI memory rally might not be over yet

What are your strategies for today, guys?

Any good setups worth getting into

In the wake of Apple’s latest earnings report, a single question keeps recurring in my mind, Can AAPL continue to sustain its rapid pace of growth?

AAPL’s immense strength stems from far more than just the iPhone itself, it is rooted in its unique ecosystem.

Apple’s rapid growth is inextricably linked to its suite of products and services, including the iPhone, AirPods, Apple Watch, Mac, iCloud, the App Store, various subscription services, and payment features. It's precisely thanks to this robust ecosystem that Apple has been able to maintain consistently high levels of profitability over the past eight years.

If the dominant force in the next generation of computing shifts away from traditional applications and toward AI driven assistants, the value of existing app ecosystems could gradually diminish over time. In such a brand new landscape, users might become less concerned with which mobile operating system they are using, focusing instead on which company can deliver the most exceptional AI experience.

Moving forward, every major decision Apple makes will be critically important. Do you believe John Ternus has what it takes to ensure AAPL continues to achieve rapid growth in the era of AI?

Following the release of its earnings report yesterday, Google has earned newfound respect from both Wall Street and retail investors alike. Today, Google’s stock price surged by as much as 7% at its peak, pushing its market capitalization past the $4.5T mark. Yet, at the very same time, Nvidia’s market cap dipped below $5T. What exactly is going on here?

My own interpretation is that this phenomenon is fundamentally tied to their respective business models. If you understand how Nvidia operates, you realize that it is essentially a company focused on chip design and assembly. the actual manufacturing of the chips is outsourced entirely to TSMC. Its revenue is derived from the margins on chip sales, rather than from directly controlling the entire product ecosystem and user base. Consequently, the moment market expectations regarding AI hardware cool down, the stock price tends to be quickly brought back down to earth. Although its CEO made every effort to sidestep this issue in recent interviews, the market’s recent performance speaks through hard data: investors are now buying into whichever company presents the strongest financial figures, no longer willing to be swayed by mere market hype.

Google, on the other hand, designs its own chips, builds its own cloud infrastructure, and integrates AI across its core products Search, YouTube, and its mobile devices. This signifies that Google possesses not only the technical prowess to develop AI but also the ability to apply that technology in ways that generate revenue. Let’s stop labeling it merely as an AI concept stock, this is a company that genuinely transforms technology into tangible cash flow. As an enterprise generating over $400B in annual revenue, Google possesses a far deeper understanding of how to leverage AI and how to address the specific needs for AI within the market.

I believe this is precisely why its stock price is climbing so steadily, its AI strategy isn't about chasing abstract concepts, but rather about actively driving growth across its high traffic flagship products including advertising, cloud services, search results, and its virtual assistant technologies.

To put it simply, Nvidia resembles a manufacturer that sells individual components, whereas Google acts as the architect of the entire value chain seamlessly integrating components, services, and user traffic.

Once major AI and aerospace related concept stocks, such as SpaceX and Anthropic go public, I truly believe that Google’s market capitalization will surpass Nvidia’s. Furthermore, I anticipate that a significant gap will emerge between the two, not just a marginal difference, but a commanding, structural lead.

to be honest, I’m not trying to pit these two against each other, but when they’re the two biggest companies in the world, people are gonna compare them anyway

What are your thoughts?

After I posted a few discussions about Google, some friends asked me this question. I figured I’d share my perspective here and I’d also like to hear different opinions.

Earlier this year, Apple reached a multi-year AI partnership with Google. The next generation of Apple Foundation Models will be built on Google’s Gemini models and cloud infrastructure, helping power future Apple Intelligence features, including a more personalized Siri. That decision is important. It tells you that in the AI era, Apple isn’t just looking at model performance,they care about stability, cost, scalable compute, and full-stack infrastructure.

So why didn’t Apple go with OpenAI or Anthropic?

At the end of the day, Apple has billions of active devices. Siri isn’t some small pilot project,it’s a system level interface that needs to run reliably at global scale. For Apple, any AI model has to handle massive concurrency, low latency, global deployment, and a cost structure that stays under control long term.

In my previous posts, I talked about Google’s moat. Google doesn’t just have Gemini,it has the entire AI stack Google Cloud, TPUs, custom chips, global data centers, plus the data advantage from Search and YouTube, and years of experience running large scale distributed systems. This isn’t a single point advantage,it’s a full stack advantage. Google can train models, deploy them, scale them, and monetize them all within its own ecosystem.

I think that’s really the core reason Apple chose Google.

On a bigger picture level, Apple’s decision also feels like a signal that the AI industry is entering a new phase. The next winners in AI won’t necessarily be the companies making the most noise at product launches. It’ll be the ones that control the full stack models, compute, cloud, data centers, energy partnerships, and global distribution.

Today, GOOGL shares just hit a new all-time high of $350. A further increase of approximately $70 per share would push its market capitalization past the $5T mark

Currently, all eyes are focused on the earnings report scheduled for release this Wednesday. While core metrics such as revenue will undoubtedly dominate media headlines, for investors like us,who focus on a company's structural growth,the true highlights of this report lie in its capital expenditure guidance and its roadmap for AI monetization.

In my view, Google possesses a unique advantage that places it in an ideal position to perfectly bridge the gap between AI conceptual hype and actual AI application value. While other companies are still focused on building the most powerful AI models, Google has already advanced to the forefront of AI commercialization, driving robust and tangible real world applications. Their efforts extend far beyond merely selling computing power. Instead, they are deeply embedding AI technology into the digital fabric of the global economy,spanning use cases ranging from ad tech optimization and productivity enhancements within the Workspace suite, to large scale operations on Google Cloud, and even deep technical integration with Anthropic

We are entering a new market phase,one where the market will no longer reward companies simply for pouring massive capital into AI. rather, it will begin to demand concrete evidence regarding the return on those AI investments. I believe that, among the various tech giants, Google possesses the most powerful and robust commercialization engine,one fully capable of meeting these market expectations.

I believe the key question to watch in Wednesday's earnings report is this, Will Google further increase its investment in the AI ​​sector, strategically allocating capital to fortify and widen its own economic moat?

Furthermore, can they demonstrate to the market that the massive capital previously invested in infrastructure development has now begun to translate into scalable revenue growth?