In the past, whenever NVIDIA spoke about AI with a sense of triumph, praised GPUs as the backbone of AI, or occasionally highlighted Intel's more provocative stance, Intel remained relatively tolerant and low-key. Faced with the slowdown in Moore’s Law and the broader industry transition, Intel rarely made public responses. However, during a press conference in September, Yang Xu, President of Intel China, unexpectedly told the media, “The tiger does not speak, thinking it is a sick cat.†This statement reflected a shift in Intel’s approach.
With the implementation of its AI investment strategy and the integration of various services, Intel has become more vocal in recent times. From the headquarters to top executives in China, high-level leaders are frequently stepping forward to actively promote Intel’s AI vision and insights. At the same time, Intel is also engaging in market activities to help drive the adoption of artificial intelligence across industries.
Over the past two months, Intel has made several notable moves that have drawn attention from the industry. In mid-October, CEO Pat Gelsinger announced the launch of Nervana’s neural network processor by year-end. Later, Intel revealed a partnership with long-time rival AMD, followed by the recruitment of Raja Kodry, AMD’s chief GPU architect, to lead the development of a standalone GPU.
Wall Street has also started paying closer attention to Intel. In mid-November, an investment firm stated that investors should not overlook Intel’s AI capabilities, expecting growth in multiple long-term markets and raising the target price for Intel.
If Intel’s AI initiatives take off, what impact will this have on the future AI chip market?
Ten years ago, if Intel had acquired ATI instead of AMD, the current landscape might look very different. It’s likely that NVIDIA wouldn’t be dominating the GPU market as it is today, and Intel might not be seen as lagging in AI.
At the time, ATI and NVIDIA were both GPU vendors, while AMD and Intel competed in the CPU space. In 2006, AMD acquired ATI for $5.4 billion, becoming a company with both CPU and GPU capabilities. While AMD’s move was strategic, the acquisition came at a high cost, forcing AMD to take on significant debt. This financial burden made it harder for AMD to compete effectively against stronger rivals.
NVIDIA’s rise in the GPU market benefited from this situation, giving it more room to grow. As AI gained momentum, NVIDIA capitalized on its GPU expertise, leveraging their ability to handle complex calculations, which gave them a natural edge in AI applications. This led to a surge in stock prices, making NVIDIA a favorite among investors.
Intel and AMD clearly don’t want NVIDIA to maintain its dominance in the GPU space. In early November, reports surfaced that Intel and AMD would collaborate in the future, with AMD’s independent GPU being integrated into Intel SoCs. This alliance reflects the idea that there are no permanent enemies—only shifting interests.
However, AMD’s GPU architect, Raja Kodry, later left AMD to join Intel. He is now set to lead Intel’s new “Core and Visual Computing†group, focusing on developing a standalone GPU. This move is certainly a blow to both NVIDIA and AMD.
Previously, while companies like Google and Apple developed their own AI chips, they didn’t make a significant impact on the market. NVIDIA’s GPUs became the go-to solution for AI, leading to widespread adoption and strong investor confidence. Intel, on the other hand, was slower in launching its own AI chips, which affected its stock performance.
On October 18th, Intel CEO Pat Gelsinger announced that the Nervana Neural Network Processor (NNP) would ship before the end of the year. This marks Intel’s first industry-focused AI chip. Although it hasn’t been launched yet, the announcement caused a sharp rise in Intel’s stock, showing market expectations.
The Nervana chip was originally developed by Nervana Systems, which Intel acquired in 2016. The company was one of the first to create chips specifically for AI. After the acquisition, founder Raveen Rao became the head of Intel’s AI division.
Intel invested heavily in Nervana, aiming to regain market share lost due to competition with GPUs. According to Intel, the Nervana chip offers higher performance and scalability for AI models, with a goal of achieving 100x improvement by 2020. Facebook is already involved in the project, but its real-world performance remains to be seen.
In addition to Nervana, Intel has also invested in FPGAs through its acquisition of Altera for $16.7 billion—the largest in Intel’s history. These FPGAs are now integrated into Intel processors, acting as a GPU-like acceleration technology. CPUs combined with FPGAs offer an alternative to GPUs.
For example, the U.S. Group uses Intel’s FPGA-based deep learning platform, and Microsoft has adopted Intel’s Stratix 10 FPGA for its Project Brainwave. Some experts believe that FPGAs can match or even surpass GPUs in certain AI tasks, offering faster performance and lower power consumption.
Unlike NVIDIA, which focuses heavily on GPUs, Intel takes a full-stack approach to AI, integrating CPUs, FPGAs, and Nervana chips. At the 2017 Intel AI Conference, Fiaz Mohamed emphasized that Intel’s strategy covers the entire AI ecosystem, not just one component.
Intel has made extensive investments in AI, acquiring companies like Movidius, Itseez, and Mobileye, and establishing a $1 billion AI innovation fund. In October, it invested in 15 AI startups, including Horizon Group in China.
Analysts on Wall Street are watching closely. One concern is that Intel’s vertical integration could threaten NVIDIA’s gross margins. With control over both design and manufacturing, Intel may use pricing strategies to compete, similar to how it once suppressed AMD in the CPU market.
Another concern is the emergence of alternatives to GPUs. If Intel or Google’s TPUs gain traction, they could challenge NVIDIA’s dominance in AI. However, despite Intel’s overall strength, NVIDIA has a long history in the chip industry and is unlikely to be easily outdone.
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