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@unusual_whales I wonder what the timing will be with an OpenAI IPO? Not seeing much online about concrete timelines, feels like Anthropic will set the precedent with their IPO.
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@MelvinInvests Just goes to show how complex the machine is behind the scenes to bring intelligence to the consumer. So many winners here in the short and long term.
Morgan Stanley mapped out the entire AI infrastructure supply chain and it reveals who actually gets paid at every layer of the trillion dollar buildout (Save this).
This heatmap breaks the AI infrastructure value chain into two dimensions those who owns and operates the data centers at the top and what physical and technical components get built underneath to make those data centers function.
At the top sit the owners/operators, the hyperscalers like Meta, Alphabet, Amazon and Microsoft, alongside data center REITs, private equity giants like Blackstone and Brookfield, enterprises and neoclouds including CoreWeave and Nebius.
These are the companies writing the massive capex checks that fund everything below them.
Below that sits the actual build out, split into seven layers, semi production, processors, server components, servers, network, internal power/cooling and power supply.
Semiconductor production is dominated by names your audience already knows well, Nvidia and AMD for GPUs, TSMC adjacent foundries, ASML and Applied Materials for capital equipment, and Micron and SK Hynix under memory/storage.
But the less obvious money is in the physical infrastructure layers most retail investors never look at.
Server components include passive parts from Yageo and Murata, thermal solutions from Sanyo Denki, and PCB substrates from companies like Unimicron.
Network infrastructure includes InfiniBand and Ethernet gear from Nvidia and Arista, plus optical/DCI routing from Cisco and Ciena.
Internal power and cooling is arguably the most underappreciated category here.
It includes liquid cooling specialists like Vertiv and CoolIT, power electronics from Siemens and Eaton, and uninterruptible power supply makers like ABB and Legrand, all companies solving the literal heat and electricity problem created by cramming more GPUs into less space.
So who benefits from all of this?
Everyone in every box benefits in some way but the real insight is that value doesn't concentrate at just the GPU layer anymore.
The hyperscalers at the top are distributing capex across seven distinct physical layers which means the picks and shovels opportunity set has expanded well beyond Nvidia into cooling, grid infrastructure, and power generation.
Bullish on AI infrastructure, make sure to follow @MelvinInvests for more AI infrastructure insights, and if you want to see exactly what I'm buying as an analyst at Milk Road Pro, you can check out the link below for more.
Memory may be the AI raceβs next major bottleneck. Reports indicate $MU and $SKHY have already allocated much of their 2027 capacity as demand for AI memory continues to accelerate.
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