$AVGO launched its AI XPV platform with $APO and $BX to help deploy more than 20GW of AI compute capacity by 2028.
The first $35B tranche will back Anthropicâs 1GW+ AI infrastructure buildout using Broadcom XPUs and networking.
Optical interconnect names are running because $NVDA CEO Jensen Huang basically validated the future AI architecture where copper wins inside the rack but optics becomes unavoidable as AI clusters scale across full data centers.
Thats why optical components, transceivers, DSPs, silicon photonics & testing names are getting re-rated today:
⢠$MRVL +30%
⢠$AEHR +21%
⢠$COHR +16%
⢠$LITE +12%
⢠$VIAV +11%
⢠$AAOI +10%
⢠$CRDO -1% (due to earnings)
THE OPTICAL PHOTONICS BOTTLENECK
As AI clusters scale past copperâs physical limits, the bottleneck shifts to optical & these are the companies building that layer across the stack:
1. $AAOI building the transceiver layer of the AI network through vertically integrated U.S.-based InP laser manufacturing. It has already secured over $200M in its first volume 1.6T order from one hyperscale customer followed by another $124M in 800G orders from a second.
2. $AEHR building the reliability layer for the optical & AI hardware stack through burn-in & test systems. It just received a record $41M follow-on order from its lead hyperscale customer reinforcing the idea that Sonoma is becoming a key production burn-in platform for high-power AI ASICs.
3. $CRDO building the connectivity layer that helps AI clusters move data faster through active electrical cables, retimers & high-speed interconnect silicon. The DustPhotonics acquisition also extends that platform into silicon photonics before copper becomes a real constraint.
4. $LITE building the laser layer of the AI optical stack through EMLs, optical components & optical switching exposure. The setup is backed by a $2B $NVDA strategic investment & optical circuit switch backlog above $400M with orders reportedly extending through 2028.
5. $VIAV building the testing & validation layer of the optical stack through network instrumentation & photonics measurement tools. It is the picks-and-shovels layer of the transition because every high-speed optical buildout still needs to be tested regardless of which transceiver vendor wins.
6. $COHR building one of the core photonics bottlenecks through indium phosphide lasers, optical engines & communications components tied to next-gen AI networking. It also has a $2B $NVDA strategic investment behind it & is doubling InP device capacity into the 1.6T ramp.
7. $MRVL building the DSP & optical infrastructure layer through electro-optics, PAM DSPs, interconnect silicon & custom networking chips. The Celestial AI deal & NVLink Fusion exposure both strengthen its position as photonics becomes more central to AI cluster design.
SpaceX just filed with the FCC to launch up to 1M satellites designed to function as solar-powered orbital data centers creating massive AI compute capacity in space.
Elon wants to use Starshipâs low launch costs and laser-linked satellites to scale AI compute without stressing Earthâs power grid.
Every new AI generation requires more HBM per GPU which means more revenue per chip for $MU.
Just yesterday, $TSLA unveiled Cortex 2, a massive AI compute cluster to train Optimus humanoid robots and power an end-to-end neural network for Cybercab autonomy.
The AI economy is becoming memory-first which helps explain why Micron stock is up ~5x over the past year.
Teslaâs chip game is no joke.
AI5 chip will be roughly comparable to a Nvidia Hopper Chip in a single SoC, and Blackwell class when you run two of them together.
Those AI chips from Nvidia run ~$25K-$50K each. AI5 will run at ~250W compared to H100âs 700W or Blackwellâs 1,000W+ in full spec.
Tesla is LOCKED IN.
Micron $MU has officially broken ground on its new $100 Billion memory manufacturing complex in New York, calling it the largest semiconductor facility in the United States đşđ¸
Here are a bunch quotes from the press release
Jensen Huang, Founder and CEO, NVIDIA:
âAs AI transforms every industry, advanced memory has become essential. By bringing manufacturing to the U.S., Micron is strengthening Americaâs AI infrastructure and supply chain resilience to power the next wave of AI breakthroughs.â
- Tim Cook, CEO, Apple:
âApple is bullish on the future of American manufacturing, which is why we launched the American Manufacturing Program as part of our $600 billion commitment to the U.S. For more than two decades, Micron has been an important partner, providing memory technologies for Apple products people use every day all over the world. Weâre proud to support Micron as they make new investments to further strengthen leading-edge memory manufacturing and R&D here in America.â
- Satya Nadella, Chairman and CEO, Microsoft:
âWeâre entering an era where AI is being built into every application and every workflow, and memory is foundational to delivering that intelligence with the performance and efficiency needed at scale. Today, Micron is taking an important step towards increasing critical memory capacity and strengthening Americaâs leadership in advanced manufacturing.â
- Mark Zuckerberg, Founder and CEO, Meta:
âAdvancing AI depends on having a strong, reliable supply chain, and cutting-edge memory technology is a key part of that. Micronâs new manufacturing complex in New York is a big milestone for U.S. manufacturing, and itâs going to help deliver the performance and scale we need for the next generation of AI. Itâs great to see Micron making this kind of investment in infrastructure â itâs the kind of progress that will accelerate innovation for everyone in the industry.â
- Secretary of Commerce Howard Lutnick:
âTodayâs groundbreaking is more proof that American greatness is back. Under President Trump, weâre done outsourcing our future and, instead, weâre building it right here at home. Micronâs investment in New York means tens of thousands of great American jobs and strong supply chains finally back in the USA. We are committed to bringing back American leadership in semiconductor manufacturing.â
- Michael Dell, Chairman and CEO, Dell Technologies:
âMicronâs investment in U.S. memory manufacturing is a major win for the technology ecosystem and for the customers we serve. Advanced, domestically built memory will be foundational to the AI-driven future. Weâre excited to support Micron as they expand Americaâs leadership in this critical technology and accelerate innovation across industries.â
- Matt Garman, CEO, AWS:
âMicronâs investment in expanding memory manufacturing capacity is critical to ensuring the performance, reliability, and scale that our customers depend on. As AI workloads grow rapidly, advanced memory technologies play an essential role in enabling the cloud infrastructure of the future. AWS welcomes this milestone and applauds Micron for strengthening their semiconductor capabilities.â
- Dr. Lisa Su, Chair and CEO, AMD:
âAdvanced memory plays a critical role in unlocking the potential of AI and high-performance computing. Micronâs New York megafab is an important investment in strengthening the U.S. semiconductor supply chain and American manufacturing. We value our long-standing partnership with Micron and look forward to continued collaboration across the AI ecosystem as demand for AI compute continues to accelerate.â
Rene Haas, CEO, Arm:
âMicronâs New York fab marks a major step forward for the U.S. semiconductor ecosystem. As AI scales, memory bandwidth and system-level innovation are becoming foundational to next-generation compute from cloud to edge. Arm is proud to partner with Micron as they expand U.S. leadership in advanced memory manufacturing.���
- Thomas Kurian, CEO, Google Cloud:
âHigh-performance memory is foundational to the AI platforms and enterprise solutions we deliver worldwide. Micronâs New York megafab will strengthen the domestic supply chain and support the innovation required to meet accelerating AI demand. Weâre proud to partner with Micron as they expand U.S. leadership in this critical technology.â
3 WAYS $AMD BECOME A SUCCESSFUL 2026 STORY
1. Data center CPUs do the heavy lifting
The most underappreciated part of the story is CPUs which are AMDâs cash engine. Tight supply, strong hyperscaler demand, potential price increases & 50%+ server CPU growth create operating leverage that carries the model while GPUs scale.
2) Helios proves platform status
Helios is is a shipment test where rack-level systems, real customer deployments & sustained volume determine whether AMD graduates from component supplier to platform vendor.
3. Second source becomes default
AMD does not need to beat $NVDA but it needs $MSFT, $META, $ORCL, $TSLA to lock in procurement rules that prohibit single-vendor AI infra. Once that happens, AMD is no longer competing deal-by-deal but becomes part of the baseline architecture.
$TSM posted Q4 revenue of $33.1B beating the $32.7B estimate & growing ~20% YoY.
Revenue should re-accelerate in 2026 as $NVDA ramps GB200/GB300 & Vera Rubin, alongside rising orders from $AVGO, $AAPL, $AMD & $INTC.
TSMC is becoming the AI factory of the digital economy.
$NVDA acquiring Groq turns a competitive threat into a customer segmentation tool by allowing Nvidia to route premium customers to GPUs, price-sensitive inference workloads to LPUs & capture revenue either way.
INSIDE THE $1T AI ECONOMY
⢠$NVDA sells the compute every AI system runs on
⢠$MSFT packages AI into software & cloud for enterprises
⢠$AMZN turns AI demand into sustained cloud & logistics monetization
⢠$GOOGL creates AI demand through search & monetizes it through ads & cloud
⢠$META uses AI to compound attention & extract more value per ad
⢠OpenAI sells intelligence directly as a product
⢠$ORCL locks in enterprise AI workloads via OCI
⢠$AMD supplies alternative AI compute at scale
⢠$AVGO provides the silicon & networking that connects AI systems
ASML is up a nice +43% this year. When I was doing research on the semi/chip industry, I looked at which companies had the widest moat.
One thing that stuck out to me is that about 40% of Nvidia's revenue comes from Meta, Google, Amazon, and Microsoft alone. That's a lot of revenue from just 4 customers.
But it's also true that ASML has the same issue with revenue concentration with a few customers as well (TSMC, Samsung, and Intel). ASML's revenue concentration is even higher than Nvidia's.
The difference is, ALL four Nvidia customers are working on building their own custom chips to lower their dependence on Nvidia, once they do, they can also sell those solutions to other customers of Nvidia. Meanwhile, NONE of ASML's customers are working on replacing them with their own lithography machines, or even trying to lowering their dependence on them.
The difference is complexity. An ASML Lithography machine is on a scale of 100x more technically complex to build or replicate than a high-end Nvidia chip.
This is part of the reason I believe ASML is a win-win. It's so complex that most companies won't even try to compete.