Prompt engineering has become the cornerstone of effective AI communication, and its applications span a myriad of industries. Let’s explore some sectors where it’s making tangible differences, underscored with real prompt examples to illustrate its transformative potential.
Case Study: Healthcare
The complexities of the healthcare sector are vast, but the nuances of prompt engineering have enabled enhanced diagnostic and treatment accuracy.
1. Using Generative AI for Accurate Diagnoses:
– Prompt Example: “Given symptoms of fever, fatigue, and shortness of breath, list potential medical conditions that could be responsible.”
This allows medical professionals to get a list of possible conditions that align with the symptoms presented.
2. Using Generative AI for Proper Treatments:
– Prompt Example: “Given a diagnosis of stage II lung cancer, provide the most recent recommended treatment protocols.”
Such prompts assist in identifying the latest and most effective treatment modalities.
But there is more. Now with the addition of Vision to the the skillset of ChatGPT you can train ChatGPT with thousands of images such CT scans, PETscans, x-rays, etc. Think about the possibility of doing this over time. For example, if you do a study on breast cancer and are not only able to train the model with scans when the cancer is obvious but also train previous scans that potentially went undiagnosed or misread you can imagine using generative AI as a prediction tool.
The possibilities are literally endless.
Case Study: Advertising Technology
In the rapidly evolving world of advertising, targeted communication is key, and prompt engineering provides the precision required.
1. Using Generative AI to Increase Ad Revenue:
– Prompt Example: “Design an ad copy for women aged 20-30 interested in sustainable fashion, highlighting summer collections.”
AI, in response, could generate an appealing advertisement that resonates with the target demographic.
2. Using Generative AI in CTV Video Ad Campaigns:
– Prompt Example: “Generate a 30-second video ad script for a streaming service targeting families, emphasizing a wide range of kids’ programming.”
Tailored ads such as these can lead to higher viewer engagement and subscription uptakes.
How about using generative AI to plan and deploy your campaigns? In the past we accomplished finding the sweet spots for specific campaigns through trial and error but what if we made this trivial. What if we were able to turn campaigns on and off hourly in a test phase to test performance and increase their frequency based on performance.
Case Study: Real Estate Technology
Real estate thrives on accurate market insights, and with generative AI, these insights are more accessible than ever.
1. Using Generative AI to Understand Market Opportunities:
– Prompt Example: “Analyze the last five years of real estate data for Seattle and predict neighborhoods expected to gain popularity in the next two years.”
By evaluating such predictions, realtors can strategize investments and sales efforts.
2. Using Generative AI for Social Media Campaigns:
– Prompt Example: “Craft a Facebook post targeting first-time homebuyers, focusing on affordable three-bedroom homes in suburban areas.”
This enables agencies to connect with potential clients effectively.
ChatGPT now has the ability to use plugins. These plugins extend the capabilities of ChatGPT. You can feed current housing data into ChatGPT allowing it to understand migration patterns within the US. For instance, it will be able to understand how many homes are for sale, how long those homes have been for sale, if those homes asking prices have dropped, if inventory is higher than the number of people moving to a given area, if inventory is less, etc.
Case Study: Software Development
Software development is all about efficiency, and with generative AI, the development cycle can be significantly accelerated.
1. Using Generative AI for Process Development:
– Prompt Example: “Given a project to develop a mobile e-commerce application with user registration and product recommendation features, outline a detailed software development lifecycle process.”
This aids in streamlining the entire development process, from ideation to deployment.
2. Using Generative AI to Develop Code:
– Prompt Example: “Generate a Python function that takes in user preferences and recommends products from a given list.”
Developers can utilize such AI-generated code snippets to speed up the coding process.
I do not think software developers can or will be fully replaced by generative AI but it is an amazing tool for speeding up software development. Given enough context you can train ChatGPT and other tools to become an effective member of your software development team. You can tell it exactly what you would like it to develop and it will. That said, there may be mistakes or the code may not use the latest techniques but imagine having something that works to start with that you can improve on without having to develop something from scratch.
With tools that allow you to convert Figma designs to code we are now moving so fast to exponentially increasing the effectiveness of virtual automated generative AI agents.
Conclusion
From healthcare to real estate, the capabilities of prompt engineering paired with generative AI are redefining traditional operational boundaries. By understanding and effectively implementing prompt engineering, industries can leverage AI’s vast potential, driving efficiency, accuracy, and innovation.
Stay tuned for the next chapter where I will discuss “Best Practices in Prompt Crafting.”
