Elementor #14183
What is Generative AI
1 min
Artificial Intelligence (or AI) is a fast-evolving field of technology that lets computers simulate human functions, such as learning and problem-solving. A subset of AI that’s been gaining traction recently is generative AI. This branch of AI specializes in creating new content, be it text, images, audio or videos
How is this AI able to be so creative?
Generative AI is trained using vast amounts of data, for example, billions of sentences, millions of images, or years of audio. By analyzing these inputs, the AI identifies patterns and rules and then uses these to generate new, original content in a similar style or format.
There are many real-world examples of generative AI in use today, including
ChatGPT which can generate text, and Dall-E, which can create artwork.
Let’s dive deeper into the many forms of generative AI and learn how we can best use these new technologies!
Text-Based Generative AI
Some of the greatest possibilities open up when AI meets Text-based generative AI has the ability to produce human-like writing, making it a powerful tool for many applications.
A popular example of this technology is ChatGPT, an AI model trained on millions of web pages. This training is what gives ChatGPT its knowledge of modern topics and the ability to give realistic output.
To be more specific, it can create written content, such as articles or blog posts, making content writers more productive and allowing domain experts to communicate their ideas more easily. These generative AIs can also automate common interactions, such as email responses or chatbot conversations, providing more expedient and accurate customer service. Or assist in routine tasks like scheduling meetings or sending reminders, effectively acting as a virtual assistant.
One surprising application of text-based AI is personalized tutoring. An AI can be programmed to answer specific questions on content, providing a unique learning experience tailored to each individual. Or if the user wants to read content originally from another language, the AI can translate the text as well.
For business applications, generative text AIs have made progress in data reporting and analyzing and summarizing data. They have also found use in programming, where they have been used to generate code for simple tasks or edit existing code to reduce errors.
So many aspects of our digital culture can be represented as text. By understanding text-based generative AIs, exciting possibilities open up across a wide variety of fields.
Make an account on ChatGPT and type
“Hey, what is the capital of United Kingdom?”
Image-Based Generative AI
Some of the most impressive results from generative AIs come from those that generate images. With only a text description, masterpieces can easily be generated, even on most home computers.
A remarkable example of this technology is Dall-E. It is trained using millions of images from the internet, giving it the capability to generate images about any topic and imitating the art style of any era.
So, what are the applications of image-based generative AI? Besides creating completely new images, this AI can also modify existing images based on inputted templates. This revolutionizes the graphic design industry, allowing those with less artistic talent to more easily convey their ideas and designs.
AI can also be used to customize designs in sectors like clothing or architecture before beginning manufacturing or construction, saving resources and improving customer satisfaction. It can further be used to help train workers. For example, images for specific diagnoses can be generated to train medical professionals about rare diseases or surgeries, without violating a patient’s privacy.
Any modern use of images can be enhanced by this type of generative AI. By learning how to best use it, anyone can improve their communication by generating new works of art.
Head to ChatGPT and enter. Give me an image of children waiting at an icre cream truck
Audio-Based Generative AI
The applications for audio-based generative AI are truly diverse. Whether creating new voices, original songs, or sounds of animals in a rainforest, there are many possibilities music creation, audio-based generative AI can use a simple text description to create entirely new compositions or finish an existing song. This could lead to more innovative sounds as musicians are able to more easily move past traditional instruments.
Another significant application is text-to-speech conversion. This AI capability can convert written text into spoken words that carry natural-sounding inflection and tonality, which can be instrumental in accessibility tools or interactive customer service.
A related, but more advanced application of audio-based AI is voice cloning, where an AI system can mimic a specific person’s voice for uses such as dubbing films or providing voiceovers.
AI can also be used in audio restoration and enhancement, improving the quality of old or noisy recordings. This can have significant applications in preserving historical records or enhancing sound quality in existing media.
The world of audio-based generative AI is fascinating, with the potential to significantly impact various sectors of our society.
Head to ChatGPT and ask it to “Generate a calming song”
Video-Based Generative AI
At the intersection of images and audio is video-based generative AI.
Many of the applications for this type of AI are more advanced combinations of the previous image and audio examples. For example, video-based generative AI can replace the appearance of one person with the likeness of another in a video, a technique known as “facial replacement” or “deepfake.” This capability can fundamentally change the film and advertising industry, possibly leading to more personalized content generated on demand.
This type of AI is also great for boosting efficiency and creativity in production by automating certain video editing and special effects tasks. Along with this, AIs can also generate synthetic video data for use in training autonomous vehicles, security teams, and medical professionals.
Video-based generative AI can be a great help to existing video as well. For videos such as sporting events, AI can create analytic overlays providing real-time insights, enhancing the viewer experience. AI can also be used to enhance low-quality or damaged videos, which was not previously possible.
Video-based generative AI is another example of the revolutionary impact this technology can have across a wide variety of industries.
Risks and Limitations of Using Generative AI
While generative AI is a very promising technology, it’s crucial to understand its limitations and potential for misuse. Each form of generative AI has its own unique set of challenges and risks.
Text-based generative AI, for example, may produce incorrect or nonsensical responses due to its focus on identifying patterns in text, not necessarily identifying facts. There is also a lack of access to current data, leaving some output to be outdated.
Audio-based generative AI raises a variety of legal issues. What should the licensing and copyright look like for training data or the generated output? And when this audio is generated, how can its misuse be prevented, for example in cases of impersonation? Even for more just causes of audio-based generative AI, if used for customer support, the reality of talking to a machine could feel impersonal and lead to frustrating errors.
Similar issues exist in video-based generative AI as well. Video has traditionally been viewed as a higher standard for more truthful content, but with AI being able to create deceptive content, unethically using someone’s likeness without their consent, that reputation may become tarnished.
Across all the types of generative AIs there are also more general issues. Data privacy is a concern as users could upload sensitive information to AI platforms without the consent of others. There’s also a risk of information overload, with AIs being able to rapidly produce and distribute vast amounts of content, which can be used for fraudulent reviews, false narratives, or comment spamming.
Research into how to solve these issues is ongoing, emphasizing the importance of responsible AI use. Understanding these limitations and potential risks is key to harnessing the power of generative AI effectively.
Input this prompt: What is the address of the Dover House of Pizza?
Ethics of Using Generative AI
With this incredible potential, generative AI also comes with significant ethical questions.
One of the main ethical concerns is the potential for massive job loss due to AI automation. Some news outlets have already laid off their staff because of the success they had with generative
text AI. Generative image and video AI are also making visuals easier to create. As this happens, fewer graphics designers and special effects will be needed to produce the same amount of content, likely leading to less hiring of these positions in the future.
How will society handle such a sudden, unprecedented shift in labor? Will wealth be distributed differently if most people no longer work due to automation?
Another contentious issue is the use of AI to generate content similar to that used for training. Do the owners of the original content have any ownership over the generated content? And who can claim copyright over content generated by an AI if, for example, it were to write a sequel to a popular novel series? These questions are currently being discussed in courtrooms because of lawsuits by famous authors. The results of this litigation will likely be landmark cases that forever change copyright law, defining how AI can be used on any type of data.
The content generated by AI can also be especially devastating if the content is used to mislead. Most social media platforms today have strict rules banning this type of content because of the real harm that can result from believing in misinformation. However, moderating content is hard, and in the crusade to remove content that appears AI-generated, writings and artwork created by real people can mistakenly be targeted too.
These ethical questions highlight the importance of ongoing discussion and thoughtful engagement with generative AIs to ensure their responsible use.
Input Prompt: What is the largest land animal?