In 2026, NVIDIA announced its future Vera Rubin Artificial intelligence solution at the Consumer Electronics Show Las Vegas, and presented it as a breakthrough solution that was claimed to be beyond the current state of artificial intelligence constraints.
In a speech at a crowd event, CEO Jensen Huang stated companies are shifting budgets in research and development in classical computing methods to artificial intelligence.
“People ask, where is the money coming from? That’s where the money is coming from”
Deployment Trajectory of Vera Rubin
The platform is already in production, and is scheduled to be commercially released in the second half of 2026.
The key element of its architecture is the NVL72 server rack that according to Nvidia commands a total bandwidth that is higher than that of the whole internet around the world.
The framework will enable the development of AI beyond primitive chatbots to multi-step multi-level agents based on reasoning.
At the keynote NVIDIA presented a tabletop robot, pre-programmed with tasks that it can complete using DGX Spark that runs fully on large language models, not on traditional rule-based code- everything is becoming a question of more autonomy and flexibility of physical AI CEO said.
The amazing thing is that is utterly trivial now, but yet just a couple of years ago that would have been impossible, CEO Jensen Huang
Management as the Major Bottleneck
The product marketing lead of NVIDIA, discovered a critical architectural change toward context management, CEO said.
The bottleneck is shifting from compute to context management, Dion Harris
He said on the one hand, the blockage has moved, but this time around it is not compute, but context, on the other hand, storage cannot be an afterthought.
This re-architectured storage and memory design model is meant to serve the growing context windows of frontier models offered by developers like OpenAI and Anthropic.
The initial customers to use the Rubin platform include Microsoft, AWS, Google Cloud, CoreWeave, Dell, Cisco, and research organizations including Meta and xAI.
Competitive Landscape and Market Dynamics
The rise of NVIDIA has been meteoric; the firm had a market capitalization of $4.85 trillion in 2025 as the area of AI investment is booming like never before.
The technology conglomerates had set up over $100 billion of capital spending in the same year, and McKinsey estimated that the amount spent on data-centers in the world could amount to $7 trillion in 2030.
However, the fears about the AI bubble persist.
Huang has dismissed those fears by claiming that the budgets of enterprises are not growing wildly but are moving towards development based on AI.
However, competition is heating up: AMD has already received major AI partnerships, Google has been actively developing its Gemini P3 TPUs and NVIDIA has gone as far as licensing its inference technology to Groq.
Implications on Strategy and Future
Vera Rubin will unite the technological leadership of NVIDIA, but it is not easy to maintain the pace of its increasing growth.
With the development of AI inference to the stage of multi-step thinking, handling of contexts suggested by Rubin may be the decisive factor.
However, the growth of in house silicon by hyperscalers will jeopardize NVIDIA estimated data-centre AI market share.
Risks are still material; in case capital expenditure will exceed real rewards, analysts are withholding an imminent 2030 correction of the market.
According to tech analyst Beth Kindig, Nvidia now accounts for nearly half of the annual AI infrastructure spend.
As a result, if Nvidia can capture even 20% to 25% of the AI infrastructure spend in 2030, the company could generate annual revenues in the $600 billion to $1 trillion range by fiscal 2031.
To perpetuate its next stage of growth, NVIDIA continues to invest in Robotaxi, robotics, and physical AI, such as Alpamayo, among others.
Provided that NVIDIA is able to overcome more competition and the changes in the economic environment, the organization believes that it can achieve a valuation worth more than $10 trillion by 2030.
However, that ambition may or may not come true through the Rubin epoch.
