What is Gen AI?

As AI becomes more established in the industry, the distinctions between its various capabilities are more necessary. AI encompasses the use of machine-learning models that are given a training dataset and then used to make predictions. An iteration of this technology has further expanded into Generative (Gen) AI which takes the capabilities of the machine-learning model one step further to generate all new data from the original set. Thus, Gen AI opens up a huge array of possibilities in how it can be applied to solve numerous business challenges.

With the ability to create new content, Gen AI can be used in many facets of a business’s operations. Below are just a few examples:

Code generation
Generative AI can generate original code, autocomplete code snippets, and translate between programming languages. It can also help developers prototype, refactor, and debug applications, often with an increase in productivity and a decrease in time to launch.

Data analysis
Generative AI can help businesses and researchers analyze complex data to uncover patterns and trends.

Real-time data processing
Generative AI can help businesses process and interpret real-time data to adapt to market changes and optimize operations.

Virtual Assistant
Generative AI can be used to build a virtual assistant that could, for example, answer employee questions related to HR benefits or help with call-center-type customer interactions.

Customer feedback analysis
Generative AI can analyze unstructured customer feedback to identify key topics, detect sentiment, and surface trends.

Generative AI models can dramatically expedite AI integration. Although customization will require specialized knowledge, leveraging a generative model for a particular application can be achieved with savvy prompting techniques and minimal data.  This is an area in which we are experimenting constantly, and learning ways to tailor fit AI strategies to any business solution.