NVIDIA's AI Future: Jensen Huang on Rogan & NVDA Price

Key Points

• NVIDIA CEO Jensen Huang emphasized that robust energy infrastructure is fundamental for the proliferation of AI factories, chip plants, and supercomputer facilities.
• Huang credited former US President Donald Trump's "Drill Baby, Drill" energy policies for fostering the necessary environment for America's AI industry growth.
• The global AI race is intensely competitive, with China gaining significant ground due to its expansive power capacity and fewer regulatory hurdles compared to the US.
• Despite competitive pressures, NVIDIA maintains a dominant market share in the AI chip sector, with demand for its advanced hardware outstripping supply.
• Morgan Stanley recently raised its price target for NVDA to $250, signaling continued analyst confidence in the company's growth trajectory amid the AI boom.

Jensen Huang on Joe Rogan: Energy as the Unsung Hero of AI Advancement

The recent dialogue between NVIDIA CEO Jensen Huang and podcast host Joe Rogan on December 3, 2025, has ignited significant discussion across the technology and finance sectors. Huang, a pivotal figure in the artificial intelligence revolution, offered candid insights into the foundational elements driving the current AI boom, particularly highlighting the often-overlooked role of energy policy.

During the widely anticipated podcast, Huang unequivocally stated that the unprecedented growth of the AI industry in the United States owes a substantial debt to the energy policies championed by former US President Donald Trump. Specifically referencing Trump's "Drill Baby, Drill" mantra—a call for increased domestic energy production—Huang articulated how such policies provided the essential power infrastructure required for industrial expansion. He elaborated that without a sustained focus on energy supply, the ambitious undertaking of constructing AI factories, advanced chip plants, and sophisticated supercomputer facilities would have been an insurmountable challenge.

"I got to tell you flat out, if not for his [Trump’s] pro-growth energy policies, we would not be able to build factories for AI, we’d not be able to build chip factories. We surely wouldn’t be able to build supercomputer factories, none of that stuff would have been possible," Huang asserted. This perspective directly contrasts with the energy strategies of the current administration, which has prioritized clean energy initiatives and climate-focused regulations, suggesting a fundamental divergence in approaches to fostering industrial growth.

The Intertwined Fate of Energy and Industrial Might

Huang's core message underscored a crucial economic principle: accessible and abundant energy is the bedrock of industrial growth, particularly for energy-intensive sectors like advanced computing and AI. The development and operation of large-scale AI models, data centers, and chip manufacturing facilities demand colossal amounts of electricity. These processes not only power the vast computational resources but also require extensive cooling systems to maintain operational efficiency. Therefore, a national policy that ensures affordable and reliable energy supply becomes a strategic imperative for any nation aiming to lead the global AI race.

This emphasis on energy supply is not merely a theoretical concept but a practical necessity for the physical infrastructure of AI. From the foundries that fabricate cutting-edge semiconductors to the hyperscale data centers that train and deploy AI models, each component relies heavily on a robust energy grid. Huang's remarks highlight how political decisions regarding energy can directly influence a nation's technological competitiveness and its capacity to innovate on a global scale.

The Global AI Race: A Battle for Power and Innovation

The conversation naturally steered towards the global competition for AI supremacy, with Joe Rogan probing whether America is currently leading this critical race and its implications for national security. Huang's response was characteristically pragmatic: "I’m not sure. I don’t think anybody really knows." This humility from a leader at the forefront of AI technology reflects the dynamic and unpredictable nature of this global technological contest.

Earlier statements from Huang had already signaled potential challenges for the US, noting that China might eventually prevail in the AI race. His reasoning stemmed from China's rapidly expanding power capacity and a regulatory environment often less encumbered by the bureaucratic bottlenecks that can slow progress in countries like the United States. The stakes in this race are monumental, as the victor is poised to dictate global standards across defence, commerce, intelligence, and scientific discovery for generations.

US vs. China: A Tale of Two Strategies

Presently, the US holds a strong position in the AI model development landscape, with prominent firms such as Google, Anthropic, and Meta consistently pushing the boundaries of performance and influence. However, Chinese models are rapidly closing this gap, demonstrating significant advancements. Companies like DeepSeek, Alibaba, and Moonshot are developing highly competitive AI models, some of which are engineered to operate with remarkable energy efficiency—a critical factor given the growing energy demands of AI.

Where China exhibits a distinct lead globally is in the realm of granted AI patents and sheer electricity generation, producing nearly double the amount of electricity compared to the United States. This energy advantage is becoming increasingly crucial as the trajectory of AI growth becomes inextricably linked to the availability and cost of power. Huang underscored this point during the podcast, proposing that future AI infrastructure might benefit from small-scale nuclear reactors strategically located near demand centers. Such decentralized power generation could alleviate strain on conventional grids and provide dedicated, on-site energy for AI operations.

NVIDIA's Unwavering Dominance and Future Outlook

NVIDIA has consistently been a standout performer for investors, and prominent financial analysts foresee continued growth. Joseph Moore, an analyst at Morgan Stanley, recently reiterated an "overweight" rating for NVIDIA, elevating its price target from $230 to $250. This revised target suggests a potential upside of approximately 39% from its then-current trading price of $179, reflecting robust confidence in the chipmaker's trajectory.

Moore's analysis suggests that concerns about competitive threats from tech giants like Google's Alphabet or AMD are "becoming overstated." NVIDIA has maintained, and in many respects, solidified its dominant market share. The escalating demand for its sophisticated graphics processing units (GPUs) and advanced packaging solutions remains robust as an increasing number of companies globally commit to developing and deploying their proprietary AI models. The current tight supply of GPUs further indicates the aggressive scaling of AI workloads by hyperscalers and enterprises alike.

NVDA Price Prediction: Navigating December's Market Dynamics

For December, NVIDIA's stock, NVDA, is anticipated to trade within a relatively tight band, primarily between $170 and $185. This forecast assumes stable geopolitical conditions, particularly the absence of new trade restrictions, and consistent demand from markets outside of China. However, several factors could significantly influence its price action.

An easing of export regulations to China, for instance, would act as a powerful catalyst, potentially propelling NVIDIA's stock beyond the $185 resistance level. Such a development could see NVDA retesting the $190 mark and possibly even venturing into the $200-$205 range. Furthermore, the finalization of NVIDIA’s reported $100 billion deal with OpenAI, currently at the letter of intent stage, would undoubtedly provide another substantial boost to its stock valuation, cementing its critical role in the burgeoning AI ecosystem. Investors will be closely monitoring these developments as December progresses.