Will DeepSeek Prove Neutral for Nvidia and AI-as-a-Service Providers?

Many financial analysts and investors are concerned that lower-cost language models such as DeepSeek will reduce demand for high-end graphics processor units, servers and high-performance computing services. 

But there also is an argument that lower-cost models and inferences will increase demand for all those products. Paradoxically, lower training and inference costs will stimulate more demand, possibly lead to new use cases 

Also, keep in mind that generative AI is only one form of AI. Perhaps SeepSeek points the way to lower processing costs for GenAI. That does not necessarily mean improvements for general AI or even machine learning. 

One might argue it remains necessary to use high-end processors and accelerators for use cases moving towards artificial general intelligence. 

The Jevons Effect, or Jevons Paradox suggests that an increase in efficiency in resource use can lead to an increase in the consumption of that resource, rather than a decrease, as some might expect, over the long term. 

Industry/Resource	Efficiency Improvement	Observed Increase in Consumption
Coal (Historical Example)	More efficient steam engines in the 19th century	Increased coal consumption as steam engines became more widely used
Oil & Gas	Fuel-efficient car engines	More people drive longer distances, leading to sustained or increased fuel demand
Electricity	Energy-efficient lighting (LEDs, CFLs)	More lighting is used due to lower energy costs, offsetting savings
Computing Power	More efficient processors (Moore’s Law)	Increased use of computing applications and data-intensive services
Water Usage	Efficient irrigation systems	More land is cultivated, increasing total water use
Internet Bandwidth	Faster and cheaper data transmission	More streaming, gaming, and cloud computing, increasing total bandwidth consumption
Paper Consumption	Digitalization and efficient printing	More documents are printed due to lower per-page costs
Ride-Sharing & Public Transit	Efficient, affordable transport services (Uber, electric buses)	More trips taken, sometimes replacing walking or biking
Air Travel	Fuel-efficient aircraft	Lower costs lead to increased air travel demand
Food Production	High-yield farming techniques	More food is produced and consumed, increasing overall agricultural resource use

As applied to more-affordable generative artificial intelligence solutions, a drastic decrease in cost might-also lead to a decrease in buying of high-end AI servers, for example, even if model training can be done on lower-capability servers. (at least in some cases). 

The argument is that efficiency doesn’t reduce demand—it increases it. As AI becomes cheaper and more accessible, more businesses, startups, and individuals will adopt it and new higher-end use cases will emerge, driving more higher-end GPU sales. 

Perhaps the bigger immediate concern is that many contestants have essentially overpaid for their infrastructure platforms. 

That becomes a business issue to the extent that, in competitive markets, the lower-cost producers tend to win. 

On the other hand, the Jevons Effect works when the price of the inputs does not change. If the price of high-end Nvidia servers does drop, then supply and demand principles--and not the Jevons Effect--will operate. And lower prices for high-end Nvidia GPUs then sustains demand. 

The Jevons Effect suggests that improved product efficiency leads to greater overall resource consumption rather than reductions. That might apply to use of AI models, AI as a service or power consumption. 

But  many have speculated that AI models such as DeepSeerk would lessen the need for high-end graphics processor units, for example. That might hold only if the prices for such servers remains the same. 

And the general rules of computing economics suggest lower prices with scale and time. So the ultimate impact of DeepSeek and other possible contenders might be more neutral than some fear.