AI Stocks & Markets

Today's Stories

1. 1

   Marvell deepens CPO role in AI data center infrastructure

   Marvell Technology is developing Co-Packaged Optics (CPO) platforms designed to address rising bandwidth and power efficiency needs for AI workloads in large-scale data centers. A recent 10-year market analysis highlights CPO as a key interconnect approach, positioning Marvell alongside other major chip and optics suppliers in this segment. CPO is described as a material factor for AI infrastructure buildouts. By working on CPO, high-bandwidth optical fabrics, and AI memory infrastructure, Marvell aims to supply more of the silicon and optics stack that hyperscalers need for AI clusters. This reinforces Marvell's existing narrative that its upside is tied to AI data center networking and custom silicon.

   Investors should track product and customer progress through late 2026, including Bravera SC6 PCIe 6.0 controller sampling in Q4 2026, concrete updates on Photonic Fabric deployments across AI racks, and any disclosed CPO design wins with major cloud providers.

2. 2

   AI Networking Stocks Rally on VR200 Demand Signal

   Marvell Technology rose 7.8% to $239.33, Credo Technology jumped 8.3% to $281.48, and Ciena gained 5.18% to $451 on Monday, August 16, 2026, driven by a Mizuho research note published Sunday citing strong VR200 ramp and positive supply-chain checks for NPO/CPO connectivity and Spectrum-X (NVIDIA's AI networking stack). The Mizuho note flags Marvell and Credo as beneficiaries because higher VR200 adoption means more optical and switching content per rack. For Marvell specifically, the note also cites CoWoS growth of more than 75% in 2027, which matters because CoWoS is the advanced packaging technology that has bottlenecked custom AI silicon supply. This directly supports Marvell's XPU and interconnect programs. Credo's FY26 revenue tripled to $1.3 billion, and CEO Bill Brennan called FY27 an "inflection point" for the optical business.

   Marvell's next earnings report, with Polymarket showing a 75.5% crowd probability of a beat ahead of the August 27, 2026 market expiry, and analyst consensus at $257.29 with 38 buy ratings. For Credo, the FY27 optical ramp toward more than $600 million of optical revenue is the metric to track. Ciena's Q3 FY26 guide of approximately $1.625 billion is the next checkpoint.

3. 3

   Micron's cheaper valuation vs. NVIDIA as HBM demand surges

   Micron has sold out its 2026 high-bandwidth memory (HBM) supply, with significant 2027 production already committed to customers; the company's Q3 FY2026 revenues surged 346% year over year to $41.46 billion. NVIDIA's data center revenues reached $75.25 billion in Q1 FY2027, up 92% year over year and representing roughly 92% of total sales. Both companies are essential to AI infrastructure—NVIDIA designs the processors, Micron supplies the memory those systems require. The key difference is valuation: Micron trades at 6.29 times forward earnings versus NVIDIA's 20.54, suggesting investors are paying a larger premium for NVIDIA despite Micron's higher forward earnings growth profile (Zacks Consensus Estimate for FY2027 indicates 113.7% non-GAAP EPS growth for Micron versus 90.6% for NVIDIA). This valuation gap may indicate more room for Micron's stock to move if AI memory demand holds.

   Micron is ranked Zacks Rank #1 (Strong Buy) versus NVIDIA's #3 (Hold). The durability of AI memory demand hinges on whether major cloud providers—expected to spend around $700 billion in capital expenditures in 2026, with the majority going to AI infrastructure—continue committing long-term to Micron's HBM products; the company's HBM4 ramp and customer agreements will be critical signals.

4. 4

   SanDisk, Kioxia launch 9th-gen QLC flash for AI data centers

   SanDisk and Kioxia announced a new 9th generation QLC 3D flash memory platform designed for AI and data-intensive workloads, along with a High Bandwidth Flash (HBF) technical specification released through the Open Compute Project to support AI infrastructure storage standards. SanDisk is positioning itself directly in the high-capacity, high-throughput storage segment that AI data centers rely on. The move aligns with expected shifts in NAND demand toward higher-performance enterprise and storage-class SSDs, potentially allowing SanDisk to gain share against competitors like Samsung and Micron in a segment where density and energy efficiency are key.

   The open HBF specification could drive adoption across the industry, but may also limit SanDisk's pricing power over time if industry capacity expands and more suppliers adopt the standard.

5. 5

   AI infrastructure stocks join Eli Lilly on investor buy-point screen

   Investor's Business Daily's stock screener identified a dozen names near buy points, including four notable stocks: Hewlett Packard Enterprise (HPE), Coherent (COHR), Amphenol (APH), and Eli Lilly (LLY). The first three are described as central players in the artificial intelligence trade. The selection reflects investor appetite for AI infrastructure—the hardware and components that underpin AI systems—alongside established pharmaceutical names. For business readers, this signals where major funds are positioning capital amid continued confidence in AI buildout.

   The article does not provide specific price targets, entry points, or forward dates for these positions. Readers should consult the full Investor's Business Daily screener for detailed buy-point levels and entry criteria.

6. 6

   AI moves beyond software into space, robotics, energy infrastructure

   BlackRock's head of global technology, Tony Kim, returned from his 13th annual tech tour across San Francisco and Silicon Valley in June with 35 colleagues, observing that AI investment is expanding beyond model development into data center design, physical systems like autonomous vehicles and humanoid robots, and low Earth orbit satellites. The conversation has shifted from pure AI models to compute-centric infrastructure and the supply chains supporting it. As AI infrastructure demand grows, scarcity is emerging in energy, materials, and semiconductors—challenges that space-based compute may partly address. The value accrual in technology markets is now concentrated in compute and model-centric companies rather than broader software players, signaling a reshaping of which technology businesses will benefit most. Companies tied to the physical buildout of AI (power, chips, data centers, satellites) may be positioned differently from service-oriented software vendors.

   Real adoption of physical AI systems is expected within the next five years, with Kim noting that a million-plus cars and humanoids in production could be possible. Self-driving trucks without drivers are expected to begin operating in Texas in the beginning of next year, marking a shift from pilots to operational deployment. The integration of satellite constellations for both AI data (via satellite imagery) and compute infrastructure represents a new frontier in AI's infrastructure layer.