Firms like OpenAI and Meta claim a compute shortage while also exploring selling compute capacity. This isn't a contradiction but a strategic evolution. They are buying all available supply to secure their own needs and then arbitraging the excess, effectively becoming smaller-scale cloud providers for AI.

The anticipated scarcity of AI inference compute is forcing a new VC playbook. Firms predict they will need to broker "special deals" between their own portfolio companies to secure capacity for startups. This transforms the VC value-add from providing cloud credits to acting as a strategic dealmaker for compute, a critical and scarce resource.

The AI revolution isn't just about software. For the first time in years, venture capital is flowing into hardware like specialized semis and even into energy generation, because power is the core bottleneck for all AI progress.

Strategic investments in AI labs, like NVIDIA's in Thinking Machines, are increasingly structured as complex deals trading equity for access to cutting-edge chips. This blurs the line between traditional venture capital and resource allocation, making compute access a form of currency as valuable as cash for capital-intensive AI startups.

Despite massive infrastructure investments, Greg Brockman believes demand for AI will consistently outstrip supply, leading to a long-term state of "compute scarcity." As AI tackles bigger problems like curing diseases, the appetite for computation will prove effectively infinite, making it a chronically scarce resource.

During a rapid AI takeoff, the cost of compute could become prohibitively expensive, blocking safety efforts. Ajeya Cotra advises organizations to hedge this risk by investing in companies like Nvidia or even owning physical GPUs, ensuring they can afford the necessary AI 'labor' when it matters most.

While model performance gains headlines, the true strategic priority and bottleneck for AI leaders is the 'main quest' of securing compute. This involves raising massive capital and striking huge deals for chips and infrastructure. The primary competitive vector has shifted to a capital war for capacity.

The massive global investment required for AI will drive demand for GPUs so high that the annual market spend will exceed that of crude oil. This scale necessitates a dedicated futures market to allow participants, especially new cloud providers, to hedge price risk and lower their cost of capital.

Concerned about AI's potential to displace white-collar jobs, Wilkinson views investing in the underlying infrastructure as a key strategy. He specifically invested in a Bitcoin mining company pivoting to AI data centers, effectively buying into the "toll bridge" of the future to protect his capital.