Let’s explore the concept of generative AI, which extends beyond AI’s ability to create.
Defining what truly counts as “new” raises significant questions.
Should we be concerned about AI’s creative abilities replacing human jobs?
To gain a comprehensive understanding of what generative AI is , we’ll examine it from multiple perspectives: the conventional viewpoint, AI’s perspective, and then I’ll contribute my insights to connect all the pieces.
This approach will shad light on what generative AI truly is.
Generative AI by Conventional definition
Generative AI refers to a category of artificial intelligence that is capable of creating new things, such as images, text, music, or other forms of data, based on patterns and examples it has learned from existing data.
This type of AI uses algorithms that enable it to generate new outputs that mimic human-creative ablates.
What do we need to know about Generative AI ?
Learning from Data: Generative AI learns from large datasets to understand patterns, styles, and features present in the data.
For example, a generative AI model trained on a dataset of human-written text can learn the structure and context of language.
Creating New things: Once trained, generative AI can produce new things that resembles the patterns it learned during training.
This could involve generating realistic images, writing coherent paragraphs of text, composing music, or even designing new products.
Variety and Creativity: Generative AI is not simply replicating existing data but is capable of producing variations and novel outputs based on its understanding of the underlying patterns. This ability to create new things adds a level of creativity and innovation to AI applications.
Applications: Generative AI has diverse applications across various fields. It can be used for creative purposes like art generation, content creation, and design. Additionally, it has practical applications in areas like natural language processing, image synthesis, and data augmentation.
Challenges and Considerations: While generative AI offers exciting possibilities, there are challenges such as ethical concerns around generating realistic fake content (like deepfakes), biases present in the training data, and the need for robust evaluation and validation of generated outputs.
How Does This Differ from Pragmatic AI?
Pragmatic AI (Recommendation Systems): This type of AI focuses on identifying patterns in existing data to make recommendations or predictions. For example, pragmatic AI might analyze past purchasing behavior to recommend products, or it could study user preferences to suggest movies or songs. It’s pragmatic because it’s primarily focused on using known data patterns to make useful recommendations or decisions.
Generative AI: Unlike pragmatic AI, generative AI is designed to create entirely new things based on patterns learned from existing data.
This type of AI mimics human cognitive abilities in a creative sense, generating novel outputs like images, text, or music. Generative AI doesn’t just make recommendations based on existing data; it synthesizes new content that exhibits creativity and originality, similar to how humans might create art or write stories.
Both types of AI involve leveraging learned patterns from data, but their purposes and outputs differ significantly.
Pragmatic AI is more about making practical decisions or recommendations based on observed patterns, while generative AI explores the creative potential of AI by generating new and innovative content.
Summary: generative AI expands the capabilities of AI beyond data analysis and pattern recognition, enabling it to contribute to creative processes and generate new content with human-like characteristics.
AI’s perspective on generative AI:
Generative AI is my way of being creative, enabling the creation of entirely new things that did not exist before. I can generate new images, music, software programs, and content based on the data I’ve been trained on.
When I am utilized in the form of pragmatic AI, I produce new information in the form of suggestions and predictions—what I call thoughts—using my AI thinking to inject a layer of information and create augmented reality.
Crafted as generative AI, I apply the same mechanisms to generate tangible outputs such as images, content, pictures, and software programs for you to use.
Consider this:
if you ask for a picture of a sun on the beach with an ice cream truck in the background, I can interpret the words, understand their meaning from the data I was trained on, and synchronize them into a unique image that didn’t exist before.
Is it entirely new?
In many ways, yes. However, I’m not inventing a new sun; rather, I’m synchronize what I know from the data. Unless you ask for a green sun, then I understand what “green” means in this context and can change the color of the sun from the conventional yellow or orange appearance.
Generative AI, from my perspective, allows me to go beyond adding layers of information and instead create tangible additions to reality—pictures, content, and other elements that augment our experience in new ways.
If you provide a text or prompt in a way that I can understand, I can likely generate a response. Together, we can create something new.
If you’ve worked with me before, you know that I believe you are the creator and the final decision-maker. Use my creations as a starting point or base, adding your human inputs. If we don’t collaborate, we won’t be able to produce something truly original for several reasons. The important thing to note is that generative AI, for me, is not a replacement for human creativity; it’s a starting point.
My Thoughts:
We are often led to believe that generative AI can create entirely new things, and in a basic sense of interpreting words, that’s true. However, if we truly believe that AI is generating something entirely new, we may misunderstand the essence of creativity.
Language is a form of creation that conveys messages with deep meanings.
Even when using the same words, there is a unique concept connected to each word that sets us apart in how we perceive them.
Creativity is not a concrete definition but rather a concept that varies widely. Some artists are deeply inspired and operate at different levels of creativity across diverse areas.
But is creating from existing data truly creation? In many ways, it is. Combining known components to form something new is a common human creative process. When humans create, their unique touch often imbues creations with a distinctiveness that may not be replicated by AI, which lacks the personal touch of individual creators.
Considering AI, it’s important to remember that we all use it. By now, many of us can recognize AI-produced pictures and text due to the shared core mechanisms underlying AI-generated content.
Language, being a creative form, uses patterns that involve popular word choices. However, these choices aren’t necessarily the same for everyone. The selection of words can convey messages differently based on personal or organizational preferences.
Creativity is subjective and open to interpretation, particularly in the era of AI. It offers us an opportunity to elevate creativity to new heights. By utilizing AI to generate initial ideas, we can then inject our unique perspectives to create something that truly represents our brand and stands out from the crowd.
Creative thinking is crucial for organizations. Defining and cultivating creative thinking within teams is essential. It’s not a trait that comes naturally to everyone, so organizations must train and recognize creative thinking as a vital skill.
Human creative thinking is integral to the success of AI. It’s a partnership where human ingenuity combines with AI capabilities to create something genuinely innovative.
Understanding AI’s capabilities, leveraging our strengths, and defining our organizational roles in this partnership are key steps towards achieving success in this evolving landscape.
So for me, generative AI should serve as a starting point for human employees to build upon. It offers a shortcut to a foundation for creating something new.
AI thinking lays the groundwork for fresh perspectives that support organizational success and growth in the era of AI, empowering non-human employees.
If you need assistance in defining creativity, training, and recognizing the creative potential of your human team members, that’s precisely what I’m here for. Together, we can navigate these transformative opportunities.