W2 1 Using generative AI in software applications

This episode explores the transformative impact of generative AI on software application development. The speaker begins by contrasting the traditional, resource-intensive methods of building applications like sentiment analysis systems for restaurant reviews—involving extensive coding, supervised learning, data labeling, model training, and deployment, often taking six to twelve months. Against this backdrop, the speaker introduces prompt-based development using generative AI, showcasing how a sentiment classifier can be built with minimal code, drastically reducing development time from months to days or weeks. More significantly, this shift is not limited to sentiment analysis; the speaker argues that generative AI has simplified the creation of numerous applications previously requiring substantial expertise and time. For instance, the speaker highlights how tasks like answering company policy questions or building chatbots have become significantly easier and more efficient. In conclusion, the accessibility afforded by prompt-based AI is fostering a rapid expansion in the number and variety of AI applications, although the speaker acknowledges that generative AI currently works best with unstructured data like text and images. This democratization of AI development is leading to a flourishing of innovative applications and represents a significant shift in the landscape of software engineering.