Enter Spot AI which is making computer vision practical for underserved users in everyday businesses and industries that power the real economy. Imagine a car wash trying to understand the flow of vehicles through their facility over the course of a day. Or a warehouse operator who wants to know the moment a truck has arrived at the loading dock to begin processing materials. Or even an industrial plant or construction site where a foreman or plant leader wants to monitor safety operations more comprehensively.
We are closely following the momentum of these overlapping but distinct trends. And to track our own work and share some of the knowledge we’ve accumulated, we’re introducing the Scale Generative AI Index, a list of nearly 200 companies in the space and details about what they’re building. We’ll keep adding to this market map as our research progresses.
We believe that in this moment of generative AI hype, nothing is more valuable than hearing directly from entrepreneurs and product leaders building in the Generative AI space. That’s why last month we hosted a panel with a group of entrepreneurs and AI practitioners to discuss the key challenges entrepreneurs are facing when it comes to building category-defining generative AI companies.
Over the last few years, building an AI startup used to require “do-it-yourself AI,” which consisted of gathering training data, labeling it, architecting complex data transformations, tuning hyperparameters, and selecting the right model. It was a herculean task, similar in complexity to the workload of the Salesforce engineer above. But in the last year or two, foundation models have emerged as a time-saving shortcut that enable entrepreneurs to do more faster. These foundation models aren’t specific to particular AI use cases, but are largely general and have something to offer almost anyone. Entrepreneurs can now decouple parts of the training data and model (which comes pre-packaged in a foundation model) from the application layer, which we at Scale call a cognitive application.