Generative artificial intelligence (AI), also referred to as gen AI, is becoming an important tool in many industries. If you have heard of generative AI, but have wondered exactly what sets it apart from other types of AI and how it is being applied in work processes, this blog will seek to answer some of those questions.
How is Generative AI Different From Other Kinds of AI?
Gen AI takes data, images, or other information and creates something entirely new from it. It has a creative, designing aspect to it that other types of AI do not. For instance, you can use ChatGPT to write a new paragraph in an application of generative AI, but an app that translates a sentence uses AI, only not in a creative way.
The new outputs delivered through generative AI include examples such as composing music, drafting a research paper, or designing how a cartoon character might look as a realistic human face.
How Does Generative AI Work?
The basic answer is that gen AI uses statistical models to recognize patterns in data to generate new but similar data. Mathematical equations are applied to understand the relationship between variables. And this isn’t just for numerical creations; sentences in English can be generated by AI models that understand the statistical likelihood of how words follow one another in a sentence. This allows it to create new, logical sentences.
In order to develop statistical models that produce quality content, the models must depend on good data. Data gathering and sources are a critical component of solid gen AI. Quality and quantity are important.
What About Transformers?
If you have dug into generative AI at all, you may have run across discussions about transformers, which are the foundation for most models. Transformers are a kind of neural architecture for networks that allow the model to focus on some pieces of data over others. It mimics the way humans focus on critical words when listening to a sentence and helps generative AI determine what input is relevant to the task.
Where Is Generative AI Being Used?
Across many industries, companies are finding that this technology allows them to streamline processes. In some cases, they are also forced to navigate some controversial aspects of using it. Here are a few examples:
- Art and design: Entirely new pieces of art, graphic design and even music are being generated, but in some instances, it could violate copyright laws.
- Natural language processing: In fields like law, marketing and journalism, customer service and more, natural language is being used to create new content as well as interact with customers, but some users find it impersonal and even annoying.
- Medicine: Generative AI is being used to speed the process of examining new drug compounds, but some experts worry that precision will be sacrificed for speed.
- Gaming: Realistic game scenarios thrill some gamers, but others say it lacks the narrative approach and intentional design that higher quality games provide.
There remain many concerns about generative AI, but as with any emerging and disruptive technology, these are likely to be addressed over time. If you are considering whether gen AI might have a place in your organization, contact us at Safari Solutions. We specialize in assessing how any given solution will affect your overall organization, taking a holistic approach to any new tech investment.
