Maja Vujinovic proposed using waste energy from testing airline engines to mine Bitcoin or power AI. GE's conservative culture and risk-averse legal department rejected the idea, showcasing how large corporations' inertia causes them to miss disruptive opportunities.
Bitcoin mining generates immense heat as a byproduct, which has historically been wasted energy. Now, companies are packaging mining rigs as home heaters. While inefficient for heating, it represents a clever strategy of finding commercial value in operational waste, turning a liability into a potential asset.
Large enterprises navigate a critical paradox with new technology like AI. Moving too slowly cedes the market and leads to irrelevance. However, moving too quickly without clear direction or a focus on feasibility results in wasting millions of dollars on failed initiatives.
The massive demand for GPUs from the crypto market provided a critical revenue stream for companies like NVIDIA during a slow period. This accelerated the development of the powerful parallel processing hardware that now underpins modern AI models.
For years, the tech industry criticized Bitcoin's energy use. Now, the massive energy needs of AI training have forced Silicon Valley to prioritize energy abundance over purely "green" initiatives. Companies like Meta are building huge natural gas-powered data centers, a major ideological shift.
Bitcoin miners have inadvertently become a key part of the AI infrastructure boom. Their most valuable asset is not their hardware but their pre-existing, large-scale energy contracts. AI companies need this power, forcing partnerships that make miners a valuable pick-and-shovel play on AI.
The most profound innovations in history, like vaccines, PCs, and air travel, distributed value broadly to society rather than being captured by a few corporations. AI could follow this pattern, benefiting the public more than a handful of tech giants, especially with geopolitical pressures forcing commoditization.
To secure the immense, stable power required for AI, tech companies are pursuing plans to co-locate hyperscale data centers with dedicated Small Modular Reactors (SMRs). These "nuclear computation hubs" create a private, reliable baseload power source, making the data center independent of the increasingly strained public electrical grid.
The conversation about Bitcoin's energy usage often misses a key point. The network doesn't just consume energy; it actively encourages developing underutilized energy sources by monetizing stranded or wasted energy, driving innovation toward a more energy-abundant world.
Satya Nadella reveals that the initial billion-dollar investment in OpenAI was not an easy sell. He had to convince a skeptical board, including a hesitant Bill Gates, about the unconventional structure and uncertain outcome. This highlights that even visionary bets require navigating significant internal debate and political capital.
Most of the world's energy capacity build-out over the next decade was planned using old models, completely omitting the exponential power demands of AI. This creates a looming, unpriced-in bottleneck for AI infrastructure development that will require significant new investment and planning.