Former director at Nvidia Corp
- Overview and update of Nvidia's (NASDAQ: NVDA) developments within AI and HPC (high-performance computing)
- Nvidia's AI product applications within the growing data centres
- Geopolitical relationships and implications
- 2023 outlook for AI and DPUs (data processing units
What 2-3 industry trends are most directly affecting Nvidia today? What would you say has the biggest direct impact? The broader semiconductor industry is an unprecedented time of macroeconomic turbulence.
How do you think Nvidia might position itself to make up for lost market share from competition? While it is a threat on one end, do you see a possibility of this increased competition becoming a catalyst for more complex technological developments for a company such as Nvidia also?
In a perfect world, Nvidia continues to be the leader to pioneer end-to-end DPUs [data processing units]. If this is the case in 4-5 years, what do you see as the biggest pros to emerge from nailing this technology?
What do you point to as the biggest trends in AI that drive companies’ decisions? Furthermore, for a company such as Nvidia that plays in various spaces of AI, what do you think its focus will continue to be as we head into 2023?
Is there anything similar about these two areas of investments that you mentioned – the omniverse and autonomous driving? Although seemingly these are different fields, why do you think a company such as Nvidia, who has resources, connections and the customers, will focus on these two areas specifically? Is there a common theme that ties them together?
What’s special about the way that Nvidia puts together AI operations and executes within its teams and its company? With a company this big, with so many different end markets and facets, can you detail your experience and explain its trajectory as more applications become more complex and specialised?
You mentioned Google, competitors such as Intel and AMD on the hardware side. How does the way Nvidia structures its teams compare vs competitors? Is there an inherent benefit you can see immediately?
You mentioned generative AI. What does this mean in terms of the current semiconductor landscape and the growth and increased appetite of AI? Could you highlight Nvidia’s developments here? Why is it so important and why is this something that the industry is ignoring?
It seems that in HPC [high-performance computing], Nvidia does have a pretty sizeable opportunity. How much of the market could the company take in terms of generative AI within HPC needs
Do you think Nvidia will capture HPC market share primarily through hardware with its GPUs, or more through from an infrastructure lens, as you were saying?
You mentioned the automation and fully autonomous data centre. Do you consider this a possibility by 2030, and if so, what are the major steps that need to be taken to ensure this?
Could you speak to the trajectory of the next generation of AI tools? Where do you think we’ll see the most needed applications, and why?
This shift that we’re seeing in these natural language processing tools, you’re talking about a lot of redundancy in the models. Is it safe to say that we’re going to see consolidation or saturation, with just a couple of leaders providing all these models?
Just wondering, as we look forward to 2023 now, the impact overall on the data centres, is the main goal going to be efficiency, or is it going to be cost reduction when it comes to the integration of these AI applications?
As you look towards 2023 and you notice Nvidia’s placements and developments in AI, what are you most excited about, what should we look forward to and what do you recognise as some of the biggest challenges? On the other side too, we’re seeing tensions across the seas between US and China and a lot of geopolitical turbulence. What are your thoughts on that?
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