Generative artificial intelligence (AI) technologies, like ChatGPT, are becoming popular tools that are now easier than ever to access. From text-to-image generators to friendly yet intelligent conversational chatbots, AI is changing the art of content creation, and how we interact with information. You can now use AI to produce blog posts, programming code, poetry, artwork, and even deep fakes. This recent and developing tech trend has the power to change how we approach content in business environments, education, and our everyday lives.
What is Generative AI?
Generative AI is a type of artificial intelligence that uses machine-learning algorithms to generate new, original, and human-like content. These powerful algorithms are trained on large amounts of existing data, such as text, images, videos, and audio. Generative AI models then use this data to generate authentic content in many forms.
These models can answer questions, analyse data, create artwork, generate summaries, produce translations, and more. Essentially, generative AI is a universal content-creation machine with endless possibilities. ChatGPT, a popular conversational AI chatbot released by OpenAI, has introduced many of us to the power of generative AI for a multitude of text-based tasks. But, how does it work, exactly?
How Does Generative AI work?
The magic behind generative AI is a machine-learning framework known as generative adversarial networks (GANs). These are artificial neural networks that can engage in deep learning. This is made possible by two neural networks that make up the GAN.
First, we have the generator, which creates the new data. Second, we have the discriminator, which evaluates the data that was generated. These two neural networks work together in an adversarial loop. The generator network improves its data creation using feedback from the discriminator. This is how generative AIs are able to produce original content that differs from the real training data.
Characteristics of Generative AI
Generative AI differs from traditional machine-learning models in a few key ways. Traditional AI models were predictive and used to recognise patterns in data and make predictions. Unlike these models, generative AI goes beyond predictions and pattern recognition to generate novel content. Generative AI can also engage in:
- Self-learning: This means the AI model can learn by itself. If given data that is unlabelled, it can ‘fill in the blanks’ by looking for patterns in the data. It can learn without being programmed to do so which makes it adaptable to various environments.
- Unsupervised learning: This learning method allows the AI to learn what it should be doing and how to do it. It does this by finding hidden patterns and insights in the data given. For example, if given images of cats and dogs, without labels or instructions, the AI would learn how to discriminate between the different data and categorise them appropriately. Generative AIs also use this kind of learning for anomaly detection which is picking out inconsistencies in data that are different from what we would expect.
The Power of Generative AI
The unsupervised self-learning capabilities of generative AI make it a powerful tool for any domain or industry. Generative AIs can be fine-tuned for specific purposes and current applications have highlighted just how much these AIs are capable of. Below, we’ll dive into some of these interesting AI applications.
First, let’s introduce the friendly ‘thinking’ and writing AI that powers many of these applications. GPT-3 is a famous text-based generative AI that was trained using 45 terabytes of data and 175 billion parameters. It can produce human-like text of all kinds, including programming code. GPT-3, which was developed by the research lab OpenAI, has been used for over 300 applications across a number of industries. A newer version of GPT-3 is also currently being used to power OpenAI’s conversational chatbot known as ChatGPT.
Genei is an intelligent research tool for reading, annotating, and note-taking. Using the power of GPT-3, genei turns PDFs and webpages into smart summaries that include a full breakdown of the reading material. This enables you to get through your reading lists 70% faster and keep all your research, notes, and ideas in one place. Genei can be used as a tool by researchers, students, business professionals, writers, and content creators.
For pro members, genei offers a host of highly powerful AI features to kickstart the writing process.
This includes a multi-document search that will answer your questions using the reading material stored in your folders and projects. Genei produces an AI summary of information to answer the question and pinpoints the resources used. In the notepad, genei has GPT-3 text generation features, including paraphrasing and summarising, and now prompts.
Prompts allow the user to specify their own writing use cases. For example, a prompt that will simplify your writing material, or complete the answer to a question in the notepad. This new feature opens up a world of possibilities for efficient AI-powered research. You can produce writing and seek answers from the most important sources of information - your reading material. Generative AIs like GPT-3 are unable to provide information outside of their training data, which limits how current the information is. However, tools like genei allow you to leverage powerful AIs for your exact informational needs.
Intelligent Writing Assistants
Jasper is a marketing-focused copywriting tool that can generate SEO-optimised and plagiarism-free content. You can prompt Jasper to write blog posts, social media posts, and marketing emails using a range of customisable features. Jasper also allows you to adapt the writing tone and style to generate creative and relevant marketing copy.
But, what if you could use the power of AI in your word processor instead? Lex is a minimalistic Google docs alternative with the GPT-3 built in to help you while you write. Companies like Notion are also seeking to integrate AI writing features into their products. Notion AI will help you to continue writing, brainstorm ideas, and summarise information like a writing assistant.
ChatGPT is a conversational chatbot released by OpenAI in November 2022. For many of us, this chatbot was our first encounter with generative AI. ChatGPT produces human-like responses to questions, tasks, and prompts. It can help you create a meal plan, write an email, generate lists, summarise information, and code. This chatbot can also provide follow-up answers and responses in a conversational thread, which allows you to tailor the information to your liking. It’s like having your own assistant at hand for any text-based task you can think of.
The Endless Possibilities of AI
However, AI is not limited to GPT-3 and text-based generation. There are also text-to-image AI tools, like OpenAI’s DALL-E and Midjourney, that can bring any image to life using a simple description. Researchers have also created specialised models of Google’s BERT for medical (BioBERT) and legal (Legal-BERT) information. For these complex fields, a dedicated machine-learning tool is especially beneficial. There’s also generative AI for audio and video content that makes deep fakes a possibility. As leading companies like OpenAI, Google, and Meta continue to work on generative AIs, we can expect to see more exciting developments and interesting use cases.