Nebula Nerd The Commoditization of Generative AI: What it Means for the Industry
Artificial intelligence (AI) has been a buzzword in the tech industry for years, but it’s only recently that we’ve seen significant advancements in generative AI. This type of AI is capable of creating new content, such as text, images, and even music, without human intervention. It’s a game-changer for industries like marketing, journalism, and entertainment, where content creation is a crucial part of the business.
However, as with any new technology, the cost of generative AI has been high. Until recently, only large corporations and research institutions could afford to develop and use these models. But that’s changing rapidly, thanks to commoditization and competition.
The Cost of Inference is Falling
Inference is the process of using a trained AI model to generate new content. It’s a crucial part of the generative AI process, and until recently, it was expensive. However, the average cost of inference is falling at a rate of 86% annually, according to a recent report by OpenAI. This is due to commoditization and competition in the industry.
Google and OpenAI, two of the biggest players in the generative AI space, have been slashing prices on their text-generating models. This has made it more accessible to smaller businesses and individuals who couldn’t afford it before. As a result, we’re seeing more and more applications of generative AI in various industries.
The Downsides of Commoditization
While commoditization has made generative AI more accessible, it’s not without its downsides. Vendors are burning through cash to keep up with the competition, and high capital expenditure (capex) and operational costs could force vendors to adopt entirely new pricing structures.
Additionally, commoditization could lead to a race to the bottom in terms of quality. As vendors compete on price, they may cut corners on the quality of their models, leading to a decrease in overall performance. This could be detrimental to industries that rely on generative AI for content creation.
The Future of Generative AI
Despite the potential downsides of commoditization, the future of generative AI looks bright. OpenAI, for example, is working on a new AI product called Strawberry, which can reason through problems better than existing models. This could lead to even more applications of generative AI in industries like healthcare and finance.
As the cost of generative AI continues to fall, we’re likely to see even more innovation in the space. Smaller businesses and individuals will be able to experiment with generative AI, leading to new and exciting use cases. However, it’s important to keep an eye on the potential downsides of commoditization and ensure that quality doesn’t suffer as a result.
