At its core, an artificial intelligence (AI) image generator primarily operates by conducting a text search. However, what many misconceive is the tool’s capacity for grasping context (they don’t). There’s a popular misconception that image generators utilize the capabilities of GPT-3.5. Amusingly, this rumor seems to have been propagated by GPT itself. In actuality, the generator does not use GPT to process text; rather, it is an advanced keyword search engine which has images in its database. What AI image generators genuinely excel in is identifying keywords within your text and regenerating them.
To understand this, consider the following scenarios.
If you ask then an AI image generator to visualize “a man pointing at a blue ball and a woman pointing at a red ball,” you might end up with an image of people wearing red and blue and pointing at the sky. This is because the AI works with keywords rather than understanding the actual essence of the scene.
An even clearer illustration of this is when determining material compositions. Request an image of a “house made of wood,” and the tool will likely provide a logical depiction of a wooden house. But when asked for a “house made of marshmallows” or inversely, a “marshmallow made of houses,” it struggles. In both cases, the end results are approached with the same algorithmic logic.
Importantly, the sequencing of your text matters. Earlier parts of your prompt hold more weight, influencing the generated output more significantly. While sometimes the results can be spot on, there will be occasions when the outcome may be unexpectedly off the mark. Thus, mastering the art of prompting AI image generators becomes crucial.
Overloading your prompt with words can also lead to unintended results. For instance, if you list multiple celebrities, the resultant image may amalgamate features, giving you unrecognizable amalgams instead of distinct personas. This difficulty in maintaining subject consistency in AI image generators becomes especially apparent when crafting intricate storylines for mediums like movies or comics.
While there is an option to upload images into these generators, the technology still needs refinement. The true advancement we should anticipate in the realm of AI image generators is the capacity to consistently maintain characters and backgrounds to foster effective storytelling, a prospect that genuinely excites me.
A point of contention for many users is the tool’s understanding of specific cameras and lenses. If you request an image imitating a particular lens or camera, the AI won’t precisely emulate that equipment. Instead, it mimics the type of images typically captured by such devices. My suggestion is to keep it straightforward. For instance, mentioning a renowned camera model might produce more professional-looking images, but avoid getting lost in the technicalities.
Lastly, always remember that experimentation is key. AI image generators work based on the association of keywords with images. By trying out various combinations, you can achieve some genuinely stunning effects. And remember, as with any skill, practice makes perfect.
Use Cases in L&D
Within learning and development (L&D), AI image generators have emerged as a powerful tool for trainers. They can create custom visuals on demand, allowing trainers and instructional designers to design course materials that cater specifically to the requirements of their curriculum and the diverse needs of their learners.
Instead of relying on generic stock photos or investing significant resources in bespoke graphic design, trainers can now input descriptions into an AI image generator to procure precise visuals. This could range from creating avatar speakers for a course, to generating graphs and chart visuals to accompany a workshop or seminar, or even developing contextual illustrations for an eLearning module. The flexibility and adaptability of AI image generators mean that trainers can have a vast library of tailor-made visuals at their fingertips, ensuring that their instructional materials are always engaging, relevant and up to date.
Moreover, when it comes to video production for online courses, AI image generators can prove to be invaluable. Video content, being one of the most consumed media formats in online learning, often requires a diverse array of visuals to keep learners engaged. With AI image generators, course creators can craft storyboard scenes, backgrounds or even illustrations that can be integrated into animations. There are even tools that can make full educational videos from a simple prompt, or from a script.
For handout materials, these generators can assist in producing infographics, clipart or any illustrative content that enhances comprehension. Not only does this speed up the content creation process, but it also offers greater customization. The end result is a cohesive and engaging learning experience, where visual content is as informative and tailored as the instructional text itself.
