General AI is great. Everyday people can load up ChatGPT and get fairly good results. But when a business requires a model to perform specific tasks custom to that business at a near-perfect rate, then firms encounter issues. As a result, the biggest companies in the world are specializing in AI models, applications, infrastructure, and other systems, to suit their needs.
Companies first tried hiring prompt engineers, with some roles paying up to staggering $335,000 a year for simply writing AI prompts. For many, this isn’t enough as specialized models need to be built to address specific business needs. Ernst & Young, for example, has built an in-house AI platform, in collaboration with Microsoft, to ensure high-quality outputs and reduce privacy risks.
Neurochain is offering an accessible alternative for companies that don’t have the funds, personnel, or time to build an AI-system from the ground up. With the largest AI dApp store in the world, businesses can browse a wide-library of specialized AI models—sorting through them using an intelligent categorization and tagging system.
Community members are encouraged to develop, refine, and enhance specialized models in exchange for a slice of the model’s royalties. This creates a continuously evolving hub of AI solutions for businesses to leverage.
That said, however, businesses often have requirements so niche that community-made models don’t perfectly suit their needs. In this scenario, a business would normally have to hire a team of developers and engineers to create the perfect model for them. With cost starting at $50,000 for a very basic system, this is not an accessible option for the majority of businesses. Fortunately, on Neurochain AI businesses can request AI
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