NVIDIA (NVDA) has announced that computing systems based on its latest Vera Rubin architecture have been delivered to several major artificial intelligence (AI) companies and are set to become operational. The company emphasized that its next-generation products are progressing as planned, which is expected to further solidify its leading position in the AI chip market.

Ian Buck, NVIDIA's Vice President and General Manager, stated at a media briefing at the company's headquarters, "We are now in full production, and all major customers are deploying these systems." The rollout of Vera Rubin products has been closely monitored by investors and analysts, with previous market concerns about potential delays or production bottlenecks.

Although NVIDIA CEO Jensen Huang has previously dismissed such concerns, the market remains watchful regarding NVIDIA's ability to maintain its technological edge as competitors accelerate their efforts. Data shows that while the benchmark chip industry index has risen approximately 66% this year, NVIDIA's stock price has only increased about 9%. In contrast, shares of Intel (INTC), Arm Holdings (ARM), and AMD (AMD) have more than doubled.

Currently, NVIDIA remains the dominant supplier in the AI accelerator market. AI accelerators are primarily used in data centers to run AI software. However, AMD and Broadcom (AVGO) are actively vying for more market share, and major data center clients like Amazon (AMZN) are developing in-house chips to reduce reliance on NVIDIA's products.

Against this backdrop, NVIDIA faces pressure to demonstrate that its new products can be delivered on schedule and outperform rivals. The company held multiple briefings at its Santa Clara, California headquarters, highlighting that the new generation of equipment not only offers higher performance but also significantly reduced deployment complexity.

NVIDIA stated that OpenAI, the developer of ChatGPT, plans to adopt Vera Rubin systems on a "large scale" in the third quarter. Companies including CoreWeave (CRWV), Google Cloud (owned by Alphabet (GOOGL, GOOG)), Azure (owned by Microsoft (MSFT)), Meta Platforms (META), and Dell Technologies (DELL) have also begun using the systems.

Although investors have been cautious about NVIDIA's stock performance this year, the market expects its revenue growth to accelerate further. Analysts project NVIDIA's revenue for this fiscal year to grow 82% year-over-year to $393.4 billion, up from a previous estimate of about 65% growth. Total revenue for the following fiscal year is anticipated to exceed $500 billion.

NVIDIA is expected to account for roughly one-third of global chip industry sales while maintaining high profitability. The market forecasts the company's gross margin for this fiscal year to reach approximately 75%.

NVIDIA executives noted the company is introducing a series of new technologies to enhance product performance and deployment efficiency by improving hardware design, manufacturing processes, and cooling systems.

In previous generations, computing trays housing AI accelerators, central processors, and networking components often required manual assembly, including connecting numerous cables. This process was time-consuming, especially when factory workers were initially learning the new designs, and had a relatively high failure rate.

The new generation system largely eliminates internal cables, connecting components primarily via circuit boards or specially designed connectors. NVIDIA stated that tasks that previously took humans hours can now be completed by robots in minutes, with a significant reduction in failure rates.

This improvement is partly due to the comprehensive adoption of liquid cooling for major components. Liquid cooling systems reduce the need for fans and air circulation space, allowing for higher component density within server racks.

NVIDIA indicated that its new-generation AI accelerator full rack, the NVL72, will deliver 10 times the token processing capability of the previous generation. Tokens are a fundamental unit for measuring AI computing tasks, and this performance data was measured by data center operator CoreWeave.

NVIDIA also made a rare direct performance comparison between its new product and a competitor's. The company claimed that when running Python programming language code, the new Vera processor can be up to 1.8 times faster than AMD's Turin processor. Both OpenAI and Anthropic are early customers for the product.

Additionally, NVIDIA has established several test sites near its Silicon Valley headquarters for the rapid development and validation of hardware, software, and supporting technologies required for AI data centers. Customers can test software and services on new hardware at these facilities before formal delivery.

At a small test data center in Sunnyvale, California, NVIDIA engineers demonstrated a set of Vera Rubin servers being tested by OpenAI. This move sends a clear signal that NVIDIA's new generation of AI computing equipment is ready to handle the world's most critical artificial intelligence workloads.