Interview Synopsis

Nvidia – Trends & Developments in AI

  • Public Equity
  • TMT
  • North America

Nvidia’s recent focus on developing end-to-end data processing units (DPUs) is being fuelled by soaring demand for extra-large data centres and supercomputers that are critical to AI models and an area in which an industry expert told Third Bridge Forum Nvidia has a competitive edge.

Nvidia hones in on DPUs, omniverse and autonomous driving  

However, generative AI, which creates new content or data using machine learning algorithms, could “dominate the AI world in the coming years” – but Nvidia does not currently have a footprint here. “Google is [participating], Microsoft is, through OpenAI, Facebook also tries to, Apple tries to, but not Nvidia,” the expert said, adding that this is something the company must address to remain relevant in AI applications. The expert also flagged signs of “real competition” regarding graphics processing unit (GPU) hardware from companies like Google, AMD, Intel and Apple.   

What Nvidia is trying to do with its acquisition of Mellanox and attempt to acquire Arm is to be the only company that provides an end-to-end DPU, the specialist told us. They commented that its recent product, the BlueField-2, has improved drastically in terms of data centre power consumption and latency. 

Nvidia is also intensifying its focus on omniverse and autonomous driving. The former is gaining momentum and has many different applications, with the expert highlighting Nvidia’s vision to build a “digital simulation of the entire world”. Meanwhile, as hardware improves, the company is also enhancing its autonomous driving algorithms. Autonomous driving is an open area but one in which Nivida could become a leader in, according to the Interview. Though serving different end markets and applications, omniverse and autonomous driving share similar purposes. 

In terms of the broader competition, the Interview revealed that Google could become a close competitor to Nvidia in the DPU space, with Intel already trying break into this field. Nvidia’s ultimate aim is to be “the only provider of everything related to hardware and infrastructure within high-performance data centres”, which combined with AI models that automate data centre operations would be a “really big advantage”.

Regarding the trajectory of next-generation AI tools, we heard there will be limited change in areas such as cybersecurity, fraud detection and manufacturing. But expect bigger developments in natural language processing and/or images and video generation, with the specialist pointing to a big shift in the former. Many engineers and internal products could become redundant, we heard, as bigger and better tools come to market. This could also prompt industry consolidation leaving only a few leaders – including Nvidia, but in the hardware sense only. 

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The information used in compiling this document has been obtained by Third Bridge from experts participating in Forum Interviews. Third Bridge does not warrant the accuracy of the information and has not independently verified it. It should not be regarded as a trade recommendation or form the basis of any investment decision.

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