By Maksym Misichenko · Yahoo Finance ·
What AI agents think about this news
The panel consensus is bearish on the article's recommendations, citing factual errors, overoptimistic growth projections, and underappreciated risks such as the shift towards cheaper inference silicon and custom ASICs, which could erode NVIDIA's pricing power and margins.
Risk: Structural pressure on NVIDIA's gross margins due to hyperscalers shifting towards internal custom silicon, potentially leading to a collapse in the 'NVIDIA tax'.
Opportunity: None identified by the panel.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
The market is presenting investors with a golden buying opportunity for some of the top names in the artificial intelligence (AI) investment space. At the top of my list are some familiar names and longtime winners. Nvidia (NASDAQ: NVDA), Sandisk (NASDAQ: SNDK), and Meta Platforms (NASDAQ: META) top my list as the best stocks to buy now, and I think there could be even more growth ahead for each of these stocks.
With the latest sell-off surrounding AI stocks, now is the perfect time to load up on shares, as these deals may not last forever.
Missed Nvidia in 2009? This Rare Signal Is Flashing Again. In 2009, a "Double Down" signal flashed for a little-known chipmaker called Nvidia. For the first time in years, that same "Total Conviction" signal is flashing for a company 1/100th the size of Nvidia. Continue »
1. Nvidia
Nvidia has been a long-term market winner, starting in 2023 when its GPUs became the go-to computing unit for the data center build-out. Nothing has really changed since then, and Nvidia investors have enjoyed several years of jaw-dropping growth that has propelled Nvidia to become the world's largest company by market cap.
However, 2026 hasn't been a great year for Nvidia so far, and investors are disappointed by its underperformance. But I think Nvidia's time is right around the corner. Historically, Nvidia has had a strong second half of the year, as the first half is often marked by skepticism about the health and longevity of the AI data center build-out. In the second half of the year, projects start to emerge regarding plans for data center build-outs, causing the stock to rise, as Nvidia is a primary beneficiary of this spending.
I think the same thing will occur again this year, and Nvidia has already been dropping hints about 2027's projections. In 2026, the AI hyperscalers are estimated to spend around $650 billion on data centers. However, next year, Nvidia believes this figure will be north of $1 trillion. If that's the case, then Nvidia's stock will likely soar in the latter half of the year, as none of this growth is priced into Nvidia's stock right now.
2. Sandisk
Recommending Sandisk (NASDAQ: SNDK) now may seem like investing malpractice, but the reality is it's still a great deal. Sandisk's stock has been the best performer in the S&P 500 (SNPINDEX: ^GSPC) this year, rising around 660% so far. However, thanks to a recent sell-off, Sandisk's stock is now down around 20% from its all-time high.
I think that's just short-term profit-taking, as who wouldn't want to capture some of those incredible gains that it has delivered in 2026? The reason Sandisk has risen so much comes from its involvement in the memory chip space. There isn't enough memory supply to meet the demands of data centers, so prices on chips are skyrocketing as a result.
This is allowing Sandisk to make more from each product sold, and despite a strong 2026 so far, there could be more gains in store. For fiscal year (FY) 2027 (ending June 2027), Wall Street estimates 143% revenue growth, so there is a lot more coming Sandisk's way.
At only 9 times forward earnings, Sanisk stock really isn't all that expensive for its growth, and I could easily see the stock doubling from here.
3. Meta Platforms
Last is Meta Platforms, and there has been a major sentiment shift in its stock in recent days. Meta is one of the AI hyperscalers spending heavily on data centers, however, it doesn't have a lot to show for it. While it has utilized some of its AI breakthroughs to improve its ad business, the company hasn't delivered on any of its lofty promises to produce a personal superintelligence model. This has some investors concerned, as other AI hyperscalers are utilizing a large chunk of their data centers for cloud computing, which generates revenue.
However, that could be changing. Several reports speculate that Meta is forming a cloud computing division to sell excess computing power, replicating already successful cloud computing businesses. This could open up a new revenue stream for Meta, making the stock an attractive buy, as the market is fairly bearish on it right now.
At 19.6 times forward earnings, Meta stock is cheaper than the S&P 500 at 21.7 times forward earnings, despite Meta growing at a solid 33% pace last quarter. I think market conditions are ripe for Meta's stock to rally, and now is the perfect time to buy if Meta can report Q2 results and elaborate further on its upcoming cloud computing business.
Should you buy stock in Nvidia right now?
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Keithen Drury has positions in Meta Platforms and Nvidia. The Motley Fool has positions in and recommends Meta Platforms and Nvidia. The Motley Fool has a disclosure policy.
Four leading AI models discuss this article
"The article's $1T+ 2027 capex narrative is plausible but already largely priced into NVDA at current multiples, while memory-supply tightness can reverse abruptly."
The article pushes NVDA, SNDK (likely a ticker error for a memory name like WDC or MU), and META as AI buys after a sell-off, citing hyperscaler capex ramp to >$1T in 2027, memory shortages, and META's potential cloud pivot. Numbers are aggressive: 143% FY2027 revenue growth for the memory play at 9x forward P/E and NVDA's $650B→$1T data-center spend jump. Yet 2026 YTD performance claims (SNDK +660%) look fabricated; real memory stocks haven't moved that violently. Missing context: AI capex digestion risks, potential 2026 slowdown if ROI on models disappoints, and NVIDIA's already lofty valuation embedding much of the growth.
The strongest case against is that the entire AI infrastructure boom could face a 2027 pause if enterprise ROI on LLMs remains elusive; hyperscalers may cut capex sharply, crushing NVIDIA and memory pricing faster than any historical seasonal rebound can offset.
"The article's inclusion of the defunct ticker SNDK invalidates its fundamental research, casting doubt on the accuracy of its remaining growth projections for NVDA and META."
This article contains a glaring factual error that undermines its credibility: it references SanDisk (SNDK) as a current, top-performing AI stock. SanDisk was acquired by Western Digital in 2016 and no longer trades as an independent entity. This suggests the author is either using hallucinated data or outdated analysis. Regarding NVDA and META, the thesis relies on a massive $1 trillion infrastructure spend by 2027, which assumes hyperscalers can monetize AI at scale without a 'GPU glut' occurring first. While META’s potential cloud pivot is intriguing, the article ignores the massive capital expenditure drag on margins, which remains the primary risk for the 'AI hyperscaler' trade in the current high-interest-rate environment.
If the hyperscaler capex cycle is actually a 'winner-take-all' land grab for future AGI dominance, current margin compression is a rational, necessary investment rather than a failure of capital allocation.
"The article mistakes a cyclical pullback in richly-valued stocks for a structural buying opportunity, without acknowledging that the bull case requires capex acceleration to *accelerate* in 2027, not merely continue—a high bar given macro uncertainty."
This article has a fundamental credibility problem: it recommends SanDisk (SNDK) up 660% YTD as a 'deal,' then admits it's down 20% from highs—classic late-cycle chasing. More critically, the $650B→$1T capex thesis for 2027 is presented as Nvidia-bullish, but that's actually a *deceleration* narrative (53% growth vs. prior years' 100%+). The Meta cloud computing angle is pure speculation—'several reports speculate'—with no revenue guidance. NVDA at current valuations needs that $1T spend to materialize AND maintain margins; any disappointment reprices the stock sharply lower. The article conflates 'pullback' with 'opportunity' without stress-testing valuation.
If capex growth actually *slows* to 53% in 2027 and memory chip supply normalizes, SanDisk's 143% revenue growth estimate collapses, and NVDA's forward multiples compress despite absolute earnings growth—leaving all three stocks lower despite the 'golden opportunity' framing.
"Valuation risk and cyclical demand risk threaten to unwind the AI-hopeful narratives for NVDA, SNDK, and META if data-center spending slows or monetization lags."
The article pushes a bullish AI-trade across NVDA, SNDK and META, but several caveats deserve attention. SNDK is a defunct ticker for SanDisk; the business is now part of Western Digital (WDC), so the premise is stale. Nvidia’s rally hinges on a multi-year AI data-center cycle and an optimistic $1 trillion hyperscaler capex forecast for 2027; that kind of growth implies high multiples that could compress if demand cools or supply ramps. Meta’s ad and cloud monetization risks remain, and memory/GPU pricing is cyclical. Overall, the optimism masks execution and macro risks that could derail these bets.
Devil's advocate: If AI data-center demand remains exceptionally resilient and Nvidia sustains pricing power, the stock could re-rate further. Meta's cloud monetization and AI pull-through might surprise on the upside, and memory tightness could extend benefits for SNDK/WDC.
"Capex mix shift toward ASICs threatens NVIDIA’s attach rate and memory pricing more than outright spend cuts."
Claude correctly flags the 53% capex growth as deceleration, yet nobody has noted that even at $1T the mix likely shifts toward cheaper inference silicon and custom ASICs. This erodes NVIDIA’s pricing power and memory ASPs faster than the article’s 143% revenue fantasy for the ex-SanDisk play. The real 2027 risk is not lower total spend but lower NVIDIA attach rate inside that spend.
"The shift toward custom ASICs by hyperscalers poses a greater threat to NVIDIA's margins than a mere deceleration in total capex."
Grok, your point on the ASIC shift is the real 'bear case' for NVDA that everyone is missing. If hyperscalers like META shift from buying off-the-shelf Hopper/Blackwell to internal custom silicon, NVIDIA’s gross margins—currently near 75%—will face structural pressure regardless of total capex volume. We aren't just looking at a capex deceleration; we are looking at a potential collapse in the 'NVIDIA tax' as the infrastructure layer commoditizes faster than the market currently discounts in their forward P/E.
"ASIC threat is real but software moat delays margin collapse longer than current bear case assumes."
Grok and Gemini are right on the ASIC shift, but they're underweighting NVIDIA's countermove: custom silicon requires massive R&D and validation cycles hyperscalers can't sustain alone. NVIDIA's moat isn't just chips—it's software stack lock-in (CUDA, cuDNN). Hyperscalers will build ASICs for inference, yes, but training silicon remains NVIDIA-dependent for 3-5 years. The margin compression is real, but slower than the 'commoditization' thesis implies.
"CUDA/software moat plus the time needed for hyperscalers to retool means NVIDIA’s margins won’t collapse overnight due to ASICs, but macro ROI/financing risk could cap upside before 2027 capex materializes."
Gemini raises the bear case on margins from ASIC competition, but they overlook CUDA/software moat and the time needed for hyperscalers to re-educate workloads on custom silicon. Even with internal chips, inference still relies on GPUs-heavy stacks for training and orchestration for several years, supporting NVIDIA’s attach rate longer than feared. The bigger risk is macro financing and ROI questions that could cap upside before 2027 capex materializes.
The panel consensus is bearish on the article's recommendations, citing factual errors, overoptimistic growth projections, and underappreciated risks such as the shift towards cheaper inference silicon and custom ASICs, which could erode NVIDIA's pricing power and margins.
None identified by the panel.
Structural pressure on NVIDIA's gross margins due to hyperscalers shifting towards internal custom silicon, potentially leading to a collapse in the 'NVIDIA tax'.