EQIX
Equinix, Inc. Common Stock REIT
stock NASDAQ

Layer 1 Systems and Colocation:
This is the physical foundation. Server vendors like $DELL, $HPE, and $SMCI assemble and sell the actual compute hardware. Colocation providers like $EQIX and $DLR own and operate the facilities where that hardware lives. I think of this layer as the land and the building.
Layer 2A Memory:
High bandwidth memory and DRAM sit on or near the GPU and deliver data fast enough to keep up with AI workloads. $MU, SK Hynix and Samsung are the key players here. A GPU without enough memory bandwidth is like being stuck in city traffic with an F1 race car.
Layer 2B Networking and Optics:
Data only matters if it can move. $AVGO designs custom ASICs and network chips. $MRVL supplies switching and $PHY the silicon.
$AAOI makes the optical transceivers that transports data over optics cables across the data center. In AI, speed is useless if the network gets jammed or when there's a lot of interference, hence the importance of this segment.
Layer 2C Power and Cooling:
AI data centers are pretty amazing heat engines. $VRT and $ETN provide power distribution, $UPS systems, and liquid cooling infrastructure. $SU covers broader energy management and cooling solutions. When power is constrained or heat cannot leave the room, the entire buildout slows down.
Layer 3 In rack connectivity:
Inside the rack, data has to move from chip to chip with as little delay as possible. $AVGO, $ALAB, and $CRDO supply the retimers, PCIe and CXL connectivity that make that possible.
In this layer, tiny delays become massive inefficiencies. It's an often overlooked layer especially with all the focus on photonics.
Layer 4 Foundry and Packaging:
This is where chips are actually made and assembled. $TSM fabricates the most advanced nodes. $INTC and $ASX handle manufacturing and advanced packaging, including chiplets and CoWoS. $AMCR provides packaging materials.
I view this as the "industrial heart" of the stack.
Layer 5 Semiconductor Equipment
These are the tools that build the tools so to speak. $ASML makes EUV lithography machines that are essential for leading edge nodes. $AMAT, $LRCX, and $KLAC supply deposition, etch, and inspection equipment used throughout the fab process.
And there you have it. The full breakdown of the AI bottlenecks map.
If you liked this write-up, you might also like the pined article on my page which goes into more depth for each segment.

Layer 1 Systems and Colocation:
This is the physical foundation. Server vendors like $DELL, $HPE, and $SMCI assemble and sell the actual compute hardware. Colocation providers like $EQIX and $DLR own and operate the facilities where that hardware lives. I think of this layer as the land and the building.
Layer 2A Memory:
High bandwidth memory and DRAM sit on or near the GPU and deliver data fast enough to keep up with AI workloads. $MU, SK Hynix and Samsung are the key players here. A GPU without enough memory bandwidth is like being stuck in city traffic with an F1 race car.
Layer 2B Networking and Optics:
Data only matters if it can move. $AVGO designs custom ASICs and network chips. $MRVL supplies switching and $PHY the silicon.
$AAOI makes the optical transceivers that transports data over optics cables across the data center. In AI, speed is useless if the network gets jammed or when there's a lot of interference, hence the importance of this segment.
Layer 2C Power and Cooling:
AI data centers are pretty amazing heat engines. $VRT and $ETN provide power distribution, $UPS systems, and liquid cooling infrastructure. $SU covers broader energy management and cooling solutions. When power is constrained or heat cannot leave the room, the entire buildout slows down.
Layer 3 In rack connectivity:
Inside the rack, data has to move from chip to chip with as little delay as possible. $AVGO, $ALAB, and $CRDO supply the retimers, PCIe and CXL connectivity that make that possible.
In this layer, tiny delays become massive inefficiencies. It's an often overlooked layer especially with all the focus on photonics.
Layer 4 Foundry and Packaging:
This is where chips are actually made and assembled. $TSM fabricates the most advanced nodes. $INTC and $ASX handle manufacturing and advanced packaging, including chiplets and CoWoS. $AMCR provides packaging materials.
I view this as the "industrial heart" of the stack.
Layer 5 Semiconductor Equipment
These are the tools that build the tools so to speak. $ASML makes EUV lithography machines that are essential for leading edge nodes. $AMAT, $LRCX, and $KLAC supply deposition, etch, and inspection equipment used throughout the fab process.
And there you have it. The full breakdown of the AI bottlenecks map.
If you liked this write-up, you might also like the pined article on my page which goes into more depth for each segment.