The shocking truth you need to know About Resource-Intensive AI

Artificial Intelligence (AI) has become increasingly popular in recent years, driving demand for resource-intensive AI systems such as ChatGPT. This market growth is expected to continue, leading to higher costs for processor, network, and storage requirements. This affects infrastructure costs and power bills and contributes to higher carbon footprints.

The rise of cloud computing has made AI more accessible and cost-efficient, making it possible to run AI systems on public clouds. However, the demand for AI services will put more pressure on these systems’ resources. Public cloud providers will increase their prices as demand rises, leading to higher cloud computing costs.

Cloud computing - Wikipedia
Image taken from Wikipedia – (Licensed under Creative Commons Attribution-Share Alike 3.0 Unported.) The Cloud Computing Metaphor – The Provider-managed suite of hardware and software

Although higher cloud computing costs may not affect businesses’ use of AI systems, it is essential to consider the impact of resource-intensive AI on sustainability. One approach to making AI more sustainable and cost-efficient is finding more efficient ways for AI to use resources, such as processing, networking, and storage.

Cloud Computing Market Size Growth from 2010 to 2023.
The growth of the cloud computing market from 2010 to 2023.

This graph shows the increasing market size of cloud computing from 2010 to 2023, based on data projections. In 2010, the market size was just $10 billion, but by 2023 it is expected to reach $591.8 billion.

One approach is pipelining, which speeds up deep learning by reducing the amount of data processed. This method limits the accuracy, which may be acceptable for some business use cases but not all. In-memory computing is another approach that can speed up AI processing by running calculations directly within the memory module, which reduces the need to move data in and out of memory.

Other approaches are being developed, such as using coprocessors for AI calculations or quantum computing. Public cloud providers are expected to announce more technologies to solve the problem of resource-intensive AI in the future.

Understanding the costs and impact of sustainability when developing AI-enablement or net-new AI systems is essential. Businesses need to make a cost/benefit choice to determine the value they can bring back to the company for the cost and risk required.

Innovation is expected to solve the issue of resource-intensive AI in the public cloud. AI technology and cloud computing providers are committed to making AI more cost-efficient and green. Although the growth of AI will continue to put pressure on the resources used, finding more sustainable and cost-efficient ways to use these resources can help to make AI more accessible to businesses and reduce its impact on the environment.

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