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Nvidia: Competitive Positioning, Strategy and Performance

Nvidia is one of the largest tech companies in today’s highly competitive and rapidly changing global market.  The corporation’s total equity is close to $8 billion dollars. They also recently announced a Q1 2019 total revenue growth of 66% with their datacenter businesses alone bringing in $701 million.  Their main focus now seems to be on High Performance Computers (HPC), Artificial Intelligence (AI) acceleration and datacenter-hosted graphics. In order to consolidate the advantages gained in recent years they have adopted an aggressive competitive stance so that they will remain the frontrunners in performance and research capability.  Their main competition comes from Intel, AMD and startups as well as the threat from in-house manufacturing such as Google’s TensorFlow Processing Unit (TPU) as a replacement for Nvidia’s Graphics Processing Unit (GPU). Their strategy is simple: remain ahead of the competition by using the wealth of expertise and resources at their disposal to continue innovating and expanding into new fields at a faster speed than any other corporation or start up can manage to keep up with.

Competitive Positioning

Most tech companies have come to the conclusion that the future of processing units lie in Deep Learning Training to create effective AI accelerators .  Nvidia’s GPU chips are currently far ahead of the field in this respect but there are many startups signalling their intent to create chips that will work ten times faster while using less power.  However, apart from Intel, AMD and Google’s in-house TPU chip, these companies are a long way off the manufacturing stage. Indeed, it will need a lot of investment to attract the right minds needed to compete with Nvidia’s army of engineers that have worked in their thousands to remain at the cutting edge of progress.

Intel have recently acquired Nervana, a company specialising in AI acceleration, in order to compete with Nvidia. Nervana’s latest announcement, before the acquisition, was that they were working on a processor that was 10x faster than the Pascal.  However, after Nvidia surprised everyone with Volta Tensor Cores, Nervana needed to go back to the drawing board. As a result, it seems that Intel will not be able to manufacture chips able to outstrip Volta Tensor Cores until the end of 2018 or early 2019.  By that time, it is expected that Nvidia will have announced it’s next generation. In such a way, Intel continue to play catch-up and the gap doesn’t seem to be closing by much. Intel’s main hope may be on optimising their 80% share in inference processing as a way of accelerating AI.  Healthcare companies have been particularly vocal in praising the AI acceleration gained from inference processing.

Google’s in-house chips offer a more direct threat to Nvidia’s dominance in the field of AI acceleration.  They certainly have the manpower and resources needed to compete and the performance of their latest TPU already rivals the GPU.  However, it is restricted by the fact that it can only be used within the Google Cloud, does not use optimized TensorFlow models and does not provide direct control of Application Specific Integrated Circuits.  These restrictions means that the high performance of Google’s TPU will only be appreciated as a better option than the GPU by a very small market. Perhaps too small to be able to make enough revenue for it to be worth the manufacturing at all in the long run.  As far as performance goes, this is certainly Nvidia’s closest competition at present but it is unlikely that Google will stop using GPUs at any time in the near future. By the time their in-house chips are able to replace GPUs without losing business to Amazon AWS or Microsoft Azure it seems likely that Nvidia will be ready for the change.

Strategy

Nvidia’s main market strategy is not to lose its dominance.  One of the main threats to any large tech corporation’s dominance is innovation by exploration into fields that currently don’t exist.  There is a reason why so many awards are currently being given to the most disruptive startups and that is because disruption drives change and prevents stagnation caused by corporate dominance.  

Nvidia are no fools in this matter ,though.  Their research departments are as much dedicated to exploring new avenues of expansion as their engineers are for remaining at the forefront of existing ones.  Their exploration into the earning potential of creating processors capable of accelerating the learning process of driverless cars is a great example of this. They are also looking to increase their share in profits within the healthcare industry by working on advanced systems for detecting cancer and other life threatening illnesses as early as possible.

Like any big tech corporation, their revenue relies upon their ability to offer the highest performance, reliable hardware at competitive prices.  However, if a disruptive industry is able to steal that revenue with cataclysmic innovation then giants like Nvidia may well implode under their own weight.  While many might say that the most precarious position for a tech company is to be on top, Nvidia’s strategy to counter these dangers has been extremely well thought out.

In terms of the gaming industry, Nvidia’s latest GPUs are being sold at a premium with a similar strategy to Apple.  Their impressive performance in 4K means that Nvidia believe gamers will be willing to spend at the top end of the market to ensure the best hardware available.

Performance

Nvidia’s GPUs are currently the highest performing processing units on the market and that doesn’t seem to be changing any time soon.  Within the sphere of gaming, recent reviews have ranked their performance as 33% higher than its nearest competitors. For the next generation of gaming consoles, it seems as if Xbox, Sony and PC systems will not be able to afford going with any other types of chips than the ones offered by Nvidia.  The competition is so intense at the time of new console releases that compromising on the premium price for less reliable processors just isn’t an option. The RTX 2080 Ti has no close competitor in terms of performance being able to provide fluid gameplay without compromising on the highest resolution of 4K gaming.

Within the automotive industry, Nvidia’s GPUs are responsible for the headway being made by Tesla to improve the Deep Learning capabilities of driverless cars.  This field, however, is a lot more open to interpretation and still very much in its nascent period. As such, current leads on performance output mean very little when looking ahead at the long term. No doubt, Nvidia recognises these challenges and will continue to confront them with the latest innovations and concepts.

Conclusion

Whilst Nvidia’s stock price may have fallen by 2% in the last year that does not suggest the company is losing its dominance on the market. Like any fluctuations with tech companies, short term responses to the slowing down of growth or the announcements of new startups looking to compete can cause big changes that don’t necessarily equate to reality.  Certainly, in terms of AI acceleration there seems to be little in the way of Nvidia’s juggernaut of progress other than disruptive industries that currently don’t exist and can only be borne out of the minds of innovative geniuses with unique visions.

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