SAN JOSE, CA – Nvidia CEO Jensen Huang delivered a bullish outlook Monday at the company’s annual GTC conference, predicting that purchase orders for its Blackwell and Vera Rubin chips will reach a staggering $1 trillion through 2027. This forecast significantly exceeds the company’s previous projection of a $500 billion revenue opportunity between the two chip technologies through the end of 2026, signaling continued robust demand for artificial intelligence hardware.
Huang’s announcement, made during his keynote address in San Jose, California, comes as the tech industry grapples with questions about a potential “AI bubble.” Despite these concerns, Huang expressed confidence in the sustained growth of AI, stating that the demand for computing power is now a million times greater than it was just a few years ago. The GTC conference, often dubbed “AI-Woodstock,” is a pivotal event for Nvidia, attracting numerous partners and showcasing the latest advancements in accelerated computing and AI.
The company unveiled a series of new chips and alliances during the conference, most notably a new AI system stemming from its December acquisition of Groq, Nvidia’s largest acquisition to date. The deal involved licensing technology from the chip specialist, and was widely viewed as a full acquisition despite not being formally structured as such, reportedly valued around $20 billion. Adding to the integration, Groq co-founder Jonathan Ross has joined Nvidia as Chief Software Architect, bringing expertise gained from his previous perform at Google developing AI chips.
Nvidia is collaborating with Groq on a new AI chip that will work in conjunction with its Vera Rubin chip system, slated for release in the second half of the year. Groq’s technology specializes in AI inference – the application of AI models – rather than their development. Huang declared, “The inflection point for inference has arrived,” highlighting the growing importance of this area. While Nvidia dominates the market for chips used in developing AI models, it faces increasing competition in the inference space.
Looking ahead, Huang confirmed that the next chip architecture, Feynman, is expected to launch in 2028, maintaining Nvidia’s two-year release cadence. This year will see the introduction of the Vera Rubin system, succeeding the Blackwell chips, which currently drive the majority of Nvidia’s business. The company’s consistent innovation is a key factor in its continued success.
The news spurred a nearly 2% increase in Nvidia’s stock price on Monday. While the stock has faced some headwinds recently, it remains a strong performer, currently trading slightly below its value at the start of the year. In 2025, the stock rose almost 40 percent, following a near tripling in value in 2024. Nvidia’s market capitalization currently stands at approximately $4.5 trillion.
Despite its dominant position, Nvidia faces challenges from competitors like Advanced Micro Devices. Major Nvidia customers – including Google, Amazon, and Microsoft – are developing their own AI chips, aiming to reduce their reliance on a single supplier. This trend underscores the increasing strategic importance of AI hardware across the tech landscape.
Huang’s optimistic outlook is shared by other major US technology companies, all of whom are significantly increasing their investments in AI. Amazon plans to invest $200 billion in 2024, up from $131 billion the previous year. Alphabet, Google’s parent company, intends to increase its investment from $91 billion to as much as $185 billion, while Meta plans to boost its spending from $72 billion to $135 billion. A substantial portion of these funds is expected to flow into AI infrastructure.
These investments are being made by so-called “hyperscalers,” which account for roughly half of Nvidia’s revenue in its AI chip division. While companies are investing heavily in AI, some are also implementing cost-cutting measures. Amazon announced 16,000 job cuts in January, and Meta is reportedly preparing for a larger round of layoffs.
The demand for AI is driving a fundamental shift in computing needs, with a move towards “agentic AI” – systems that can spawn off other agents to accomplish tasks. Here’s leading to an explosion in the number of tokens being generated, requiring faster inference speeds. Nvidia’s GPUs have become essential for this new wave of AI applications, solidifying the company’s position at the forefront of the industry.
Nvidia’s continued success is not just about hardware; it’s about building an entire ecosystem around AI. The GTC conference serves as a platform for showcasing these advancements and fostering collaboration with partners. As AI continues to evolve, Nvidia is poised to play a central role in shaping its future.
The next key date for Nvidia is the release of the Vera Rubin chip system later this year. Investors and industry observers will be closely watching to see how this new technology performs and whether it can maintain Nvidia’s momentum in the rapidly evolving AI market.
Archysport will continue to provide updates on Nvidia’s progress and the broader AI landscape.
