The concept of “artificial intelligence” (AI) is not a novel one. Recent years have been amazing for its existence, what with the explosion of smartphone and internet use around the globe. From now until 2022, one subfield of artificial intelligence has dominated discussions. This particular branch of AI may produce content in response to a user’s instructions.
Among these variants is OpenAI’s ChatGPT, a natural language processing service capable of assembling text in a variety of formats (articles, song lyrics, information, and so on) in response to a user-entered prompt. In addition to ChatGPT, you should be familiar with Midjourney, another AI service with a similar function. Midjourney, on the other hand, generates an image based on the user’s description of the question.
The term “Generative AI” describes a wide range of recent developments in the field of artificial intelligence. Therefore, the purpose of the article is to define Generative AI, explain how it functions, discuss its application (such as in digital business), and investigate the growth prospects in Indonesia. For more details, you can go on to the next chapter.
What’s Generative AI?
Generative AI is a subfield of AI that focuses on constructing models like visuals, audio, and text from raw data. It can generate new outputs that are stylistically and substantively like the original data, in contrast to traditional machine learning models that are taught to categorize or predict existing data.
Interestingly, the Generative AI system can be smart with other kinds of data as well. In order for this technology to be truly intelligent, it has to be outfitted with contextual learning techniques, such as natural language processing.
How Does Generative AI Work?
The functionality of generative AI is reliant on textual prompts. The scope of prompts is not restricted to textual inputs alone. AI can also process visual cues such as images, videos, and designs to generate prompts. Subsequently, the Generative AI’s algorithm shall analyze the given prompt and generate fresh and innovative content in accordance with it. The ultimate output is contingent upon the user’s initial request, naturally. In the event that the output of this user’s query is presented as an article, the resulting information will also be presented in the form of an article. The nature of the content in question exhibits a remarkable variety.
In the nascent stages of Generative AI, getting data involved either utilizing an API or navigating a rather intricate procedure. In order to excel in their field, developers need to have a comprehensive understanding of specialized tools and possess the ability to craft intricate application code utilizing programming languages like Python.
The latest iteration of Generative AI boasts an enhanced user interface that empowers users to input prompts using even the most rudimentary language. Once the preliminary output is generated, users have the freedom to tailor the results to their liking by providing feedback on various aspects such as writing style, tone, and other elements that require refinement, thereby enhancing the overall quality of the content.
Generative AI in Digital Business
Companies of all sizes have relied on Generative AI to help with a wide range of tasks. Generative AI can be used in a wide variety of departments, from information technology for coding to finance for data management to digital marketing for content generation, sales materials, and beyond. Here, however, we shall classify the ways in which Generative AI is used in the digital business world according to their respective contexts.
Image Generation
Images of all sorts (including things, buildings, people, and animals) can be created with the help of this method. When creating movies, video games, or animated shorts using computer graphics, this method is invaluable for use as visual references. Midjourney and Dall-E are two instances of generative artificial intelligence used here.
Text Generation
In the recent year, this method has risen to prominence as one of the most sought-after techniques; it can generate a wide variety of written works, including essays, new song lyrics, poetry, copywriting, and more. ChatGPT is, without a doubt, the most popular of these techniques. Google has developed a competing alternative to ChatGPT called Bard.
Music Generation
This Generative AI technology uses machine learning to generate new musical works, including those with new melodies, harmonies, and rhythm. Composers can use this technology to experiment with different musical genres and techniques. Soundraw is a service like which already exists.
Data Augmentation
In addition to preexisting data sets, this technique generates samples that are statistically indistinguishable from the original data. In computer vision, where big datasets are required for training machine learning models, this strategy is quite helpful.
How to Properly Use Generative AI?
Generative AI is often deployed in response to a prompt. To illustrate the use of Generative AI in text creation, we will use ChatGPT as our example implementation this time around. To use this feature, go to chat.openai.com/chat and sign in with your own personal credentials.
Make sure the prompt you write is very detailed if you want to create a poem. Do not ask Generative AI to write poetry if you want something basic, like “make me a poem.”
Make sure you get what you want out of the prompt you write: Which poetry do you wish to compose? Is your goal only to find all the poetry references? How would you describe the writing’s style? Does the language yearn for a more exquisite and unique vocabulary? How many paragraphs or words do you plan on composing?
To illustrate, you may write something like, “Make me a reference to a modern Indonesian poem, with hyperbole, a sad tone, emphasizing the topic of hopelessness in a relationship.”
As a result, the final produced content will match the requirements outlined in the brief. A comparable form of generative AI, picture generation, would produce visuals in response to textual input.
Generative AI Potential in Indonesia
Adhiguna Mahendra, Chief of Business Product and AI Strategy at Nodeflux, predicts that Indonesia will see enormous increases in both the development and application of artificial intelligence (AI), particularly generative AI. He mentioned that various sectors, including banking, retail, communications, and manufacturing, have already used AI.
Adhi stressed that despite AI’s promising future, implementing it won’t be as simple as many would think. AI bandwidth is only one of several obstacles that will slow down the technology’s widespread adoption. Indonesia too lacks comprehensive AI rules at this time. Since AI is certain to collect massive amounts of data, Personal Data Protection (PDP) is one of the rules alluded to in adopting AI. Therefore, it is envisaged that in the future Indonesia would establish distinctive laws concerning AI.
Read More: 2023 Forecast: Top 5 Technology Trends to Watch Out For
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