What is Generative AI? Everything you need to know.

Wareesha Khan

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Wareesha Khan

What is Generative AI?

Generative AI is a subfield of Artificial Intelligence that possesses the capability to produce texts, images, audio, videos, and synthetic data that is often indistinguishable from human-created content. The recent excitement surrounding Generative AI stamps from the user-friendly interfaces that allow users to effortlessly create high-quality text graphics and video within seconds. This fascinating technology has various applications ranging from content creation to art creation and even scientific research. As the world of AI is spreading rapidly, Generative AI is making a remarkable impact on various industries. This technology is not new though, it was introduced back in the 1960s in chatbots. But later modernized with the introduction of GANs-Generative Adversarial Networks and many more analyzing the modern world problems. Now moving forward and see how Generative Ai works.

The Science Behind Generative AI: How does it work?

Generative AI begins with a prompt which can take the form of text, image, video design, audio, musical notes, or any input that the AI system can process. Various AI algorithms generate new content in response to the given prompt, this content can range from essay and problem solutions to realistic data created using images or audio of a person. AI utilizing the technology involves submitting data through an API or a complex process. Developers need to acquaint themselves with a specialized tool and write applications using programming languages like Python. Some of the recent and fully operational generative AIs are Gen Expert, Google Bard, Dalle-2, openAI ChatGPT, Microsoft Bing, Midjourney, Claude, vertex, and many more.

Generative AI Models: Large Language Models

Over the past couple of months, large language models, or LLMs, such as chatGPT, have taken the world by storm. Large language models are a part of a different class of models called foundation models. Where before AI applications were being built by training, using a library of different AI models, where each AI model was trained on very task-specific data to perform very specific tasks. The foundation model can drive all these same use cases and applications. So the same exact applications that we were envisioning before with conventional AI, the same model can drive any number of additional applications.

The point is that this model could be transferred to any number of tasks. What gives this model the superpower to be able to transfer to multiple different tasks and perform multiple different functions is that it's been trained on a huge amount of data, in an unsupervised manner, on unstructured data.

In the language domain, it means that I will feed a bunch of sentences--terabytes of data-- to train this model, and the start of my sentence might be "no use crying over spilled" and the end of my sentence might be "milk". I'm trying to get my model to predict the last word of the sentence based on the words that it saw before. And it's this generative capability of the model-- predicting and generating the next word --based on previous words that it's seen beforehand. That is why foundation models are actually a part of the field of AI called Generative AI as we're generating something new, in this case, the next word in a sentence.

Diverse Applications of Generative AI

In recent years, Generative AI has taken the world by storm, and in 2023, its applications have become more diverse and fascinating than ever before. Let's uncover the incredible ways Generative AI is changing the game in various content generation domains.

Text Generation: A Personal AI Tutor

Generative AI, especially models like ChatGPT and GenExpert, has revolutionized text generation. These models not only answer your questions but also assist in writing blog posts, social media posts, and emails. However, one of the most exciting applications of Generative AI in text generation is in education. Imagine having a personal AI assistant designed for your learning needs. Khan Academy's "Con Migo" is a great example of this concept, where students have their personal AI tutor to provide quick answers, ensure understanding, and adapt to individual strengths and weaknesses. This technology has the potential to transform the traditional classroom model into AI classrooms and teachers.

Code Generation: Revolutionizing Software Development

GitHub's Copilot, powered by OpenAI's Codex, is a prominent example of Generative AI in code generation. It's a game-changer for software developers, as it helps reduce errors, speeds up the coding process, and makes it more accessible for beginners. With these AI tools, engineering teams can be more productive, create complex applications more easily, and revolutionize the coding world. New and enhanced AI products like GenExpert are also making its part in code generation and many users from software backgrounds are taking advantage in many ways.

Sound Generation: A World of Music and Speech Generation

Generative AI is also making its mark in sound generation, providing creators with copyright-free music. Algorithms like WaveNet and Audio LM are shaping the way for sound generation. Additionally, there are applications like Start AI that synthesize realistic speech. This technology is opening up new possibilities in the world of media, advertising, and content creation. AI-generated content, including audio and speech, is becoming increasingly prevalent.

Video Generation: Faster Social Media Content Generation

Generative AI algorithms are improving video creation through mock-ups and text input. These advancements are leading to faster publishing of social media content. As AI-generated content blends with original creations, it becomes challenging to distinguish what's real and what's AI-generated on platforms like Instagram and Facebook. Content creators can produce more content rapidly, and AI tools for video editing will further smooth the process.

Image Generation: New Way of Advertising

Models like DALL-E, Mid-Journey, and Stable Diffusion are setting the bar high for AI-generated images. These AI models are capable of producing creative and innovative images, often incomparable to human capabilities. One of the most exciting applications of image generation is in advertising. AI-generated images can be used in product marketing, eliminating the need for costly agencies and models. This not only saves costs but also enables businesses to create stunning, timeless, and creative visuals for their products.

Generative AI Trends For 2024

Generative AI has been a hot topic, and as we look forward to 2024, it's going to keep making waves. let's dive into what's happening with generative AI next year 2024.

AI in Politics and Campaigns

In 2024, AI will play a big role in politics. It's not all good news, though. AI will be used to spread false info and mess with political stuff. But on the bright side, politicians will also use it to create personalized campaign messages and emails.

AI Redefining Product Design

AI is shaking up how products are designed. Platforms like Autodesk are using generative AI, which means designers can quickly make lots of prototypes and test them. This helps make better, more eco-friendly products.

Easy-Peasy Video Creation

Everybody loves videos, and AI is making it even easier to make them. You'll be able to create professional-looking videos without spending a ton of money. Plus, AI will make voices sound more natural. The future of AI is all about blending visuals, sounds, and language seamlessly. You'll be able to talk to AI about art and videos just like you chat with it through text. It's all coming together to give us a more immersive experience.

AI Whisperers

As AI gets fancier, we need experts to guide it. These folks are sometimes called AI Whisperers. They'll help AI systems work their best. If you're looking for a cool job in tech, this is one to consider.

AI in Schools

AI is finding its way into classrooms, and that's got people talking. Some folks worry we'll rely on it too much, while others see it as a chance for students to explore complex subjects with a little AI help. It's an ongoing chat that will keep evolving.

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