$GOOGL, $AMZN, $META Alphabet raised its 2026 capital expenditure outlook to $195 billion–$205 billion, while Amazon expects to invest about $200 billion and Meta plans $125 billion–$145 billion. Together, the three companies could spend as much as $550 billion, much of it on AI infrastructure. Alphabet said approximately 60% of its second-quarter technical infrastructure investment went to servers, with the remainder allocated to data centers and networking equipment. The AI buildout is therefore benefiting not only GPUs, but also power, cooling, networking, and physical infrastructure. The main risk is NVIDIA’s dependence on the capital budgets of a relatively small group of customers. Companies such as Meta continue deploying NVIDIA systems but are also expanding custom silicon developed with Broadcom and adopting AMD accelerators to reduce reliance on a single supplier. --> There is still little evidence that hyperscaler infrastructure spending is approaching an end. The more important question is no longer simply how much they are spending, but which layers of the infrastructure stack are capturing that investment. Spending on GPUs and compute systems will continue, but as AI clusters become larger, the constraint increasingly shifts from raw computation to the ability to store and move data efficiently. That makes scale-up and scale-out connectivity inside the data center, data center interconnect, and memory bandwidth and capacity increasingly important. The areas to watch now may therefore be the memory and connectivity layers that allow expanding compute capacity to be fully utilized. As long as the AI buildout continues, these layers are likely to remain critical system bottlenecks rather than optional infrastructure spending.