Generative AI
Generative AI refers to AI systems that create new content—text, images, code, audio, video—rather than classifying or analyzing existing data. ChatGPT, DALL-E, Midjourney, and Stable Diffusion are all generative AI. The underlying models learn statistical patterns from training data and produce new outputs that follow those patterns. This is a meaningful shift from the previous decade of AI, which was dominated by discriminative models (spam filters, recommendation engines, fraud detectors) that sorted things into categories. Generative AI crossed into mainstream adoption faster than any technology since the smartphone, reaching 100 million users in two months. But the speed of adoption has outrun the infrastructure for using it well. Most organizations are still in the experimentation phase—running pilots, debating policies, and trying to figure out where generative AI creates value that justifies the cost, the risk, and the organizational change required to use it at scale.
Related terms:
Gravity Wells
Gravity wells describe economic dynamics where scarce resources flow disproportionately to entities with the greatest ability to pay and deploy, creating...
Inference
Inference is the process of running a trained model on new input to generate a prediction or output—such as sending a prompt to GPT-4 and receiving a...
Token
In large language models, a token is the basic unit of text—usually chunks of three to four characters—that the model reads and generates.