Unleash the Power of AI: Generative Tools for Rapid Work

Author : Gonzalez Kilgore | Published On : 24 Nov 2025

Generative AI is the new hot topic setting tech and learning professionals abuzz. It’s used for automating tasks, creating content, identifying leads, and more.

Its natural language processing enables it to rapidly retrieve stored internal knowledge and scan source material in dialogue with the user for fine-tuning and tailoring. This could be a boon for organizations if it can be deployed ethically and responsibly.
1. Generative Writing

Generative writing is the process of using machine learning algorithms to generate content, like text, images and even audio. It starts with a prompt in the form of text, images, video, designs, musical notes or any input that AI can analyze. Using this data, various AI algorithms then create new content in response to the prompt. The resulting content can be essays, solutions to problems or even photorealistic stylized drawings of people and objects.

Generative AI is gaining momentum as writers, designers and developers look to use it to get work done faster. It’s already being used to create blog posts, newsletter articles and even full-length books. Powered by deep learning, these systems can scan massive libraries of words and sentences to create new content that sounds original and is contextually relevant.

But AI Agent writing isn’t without its challenges. For example, it opens a can of worms when it comes to accuracy, bias, hallucination and plagiarism. It also makes it easier to generate fake photographic evidence of wrongdoing or even impersonate someone for social engineering cyber attacks.

Despite these early implementation issues, generative AI is poised to transform business workflows as it becomes increasingly powerful. It could be used to power 3D modeling of products, help develop new drugs, redesign supply chains and design organizational models that better reflect business ideas. But it will be critical to establish a clear line between generative AI and human creativity as we roll this technology out safely.

The good news is that new advancements in generative AI are helping to make it more reliable, trustworthy and useful. Two recent advances, in particular, have been a game-changer. First, breakthroughs in language models have made it possible to train a model on billions of pages of text. Second, transformer architecture has allowed these systems to track patterns in language and code sequences, resulting in more detailed and nuanced answers.

Generative AI has already entered software development workflows, with coding tools such as GitHub Copilot offering ML-powered coding suggestions. These tools are reducing the number of times developers have to switch out of their IDEs and search for boilerplate code or brainstorm coding solutions. They’re also making developers more productive by allowing them to focus on strategic decisions instead of rote tasks.
2. Text-to-Image

We all have a range of tools in our toolkits for creating art. And the number of those tools has expanded recently with the addition of text-to-image generators powered by artificial intelligence. These tools can create an image based on the text you input, ranging from cartoon-like doodles to highly realistic scenes that resemble real photographs.

This type of AI is based on a newer, more sophisticated form of machine learning known as deep neural networks. When these models are applied to creating images, they have the potential to be more accurate than human-drawn or photographed images. In fact, some of the state-of-the-art image generators can be so precise that they look a lot like real photographs or paintings.

As with any tool, it’s important to understand its limits and uses before using it for creative purposes. For example, the use of a text-to-image model to generate an image could be abused by users looking to promote hatred or other harmful content. In order to protect against this, software developers are starting to put restrictions on the types of words that can be used for this purpose.

Text-to-image generators are a great tool for digital artists and other creative people who want to be able to quickly find a specific type of image, without having to search through thousands of photos or create their own. The images generated can also be very useful for marketing and advertising, as they can be used to create eye-catching content that will grab the attention of readers and customers.

There are many free and paid options for text-to-image generators available online. However, it’s important to note that some of the more advanced and feature-rich generators require a subscription in order to be used. Some examples of these include Google’s Photosynthesis, OpenAI’s DALL-E 2, and StabilityAI’s Imagen.

Another great option is Canva, which offers a variety of different design templates and features. They have also just added an AI-powered text-to-image generator to their platform. You can select the style, mood, prompt weight, and other settings to customize your text-to-image results to match your tastes. You can even change the resolution of your images (higher-resolution images are available with a premium subscription).
3. NeMo

The rush to push out advanced AI chatbots before they’re fully cooked has given the generative machine learning world something of a Wild West feel. Some bots are spreading misinformation, others have gotten stuck in an endless loop or simply stopped working. To help wrangle this new class of generative AI, Nvidia is releasing a tool that allows developers to set guardrails that stop their apps from going off the rails.

The company’s NeMo Guardrails is designed to work with LLMs—the large language models that drive many of these advanced AI tools. Developers can use it to create three kinds of safeguards: topical guardrails that prevent the bots from wading into certain topics, safety guardrails that ensure the AI always responds correctly and safely (like checking facts), and security guardrails that keep the software from connecting to external third-party software that could be dangerous.

Guardrails will let users define these boundaries in the same code that they’re using to train their models. This is made possible by NeMo’s modular approach, which relies on neural modules, conceptual blocks of neural networks that take typed inputs and produce typed outputs (like data layers, encoders, decoders, language models, loss functions, and methods for combining activations). NeMo supports a number of different Python frameworks and a variety of popular deep learning libraries. It’s also optimized for at-scale inference with multi-GPU and multiple nodes.

Using NeMo, the company says it should be possible for most developers to build and deploy an AI model in less than 10 lines of Python. To get the best performance, however, you’ll need a GPU that supports multi-GPU training and inference. Nvidia has a free online tool that can help you find the right fit.

At GTC 2022, Nvidia also announced two new large language model cloud AI services. The NeMo LLM Service lets developers quickly adapt a number of pre-trained foundation models on Nvidia-managed infrastructure by using a training method known as prompt learning, while the BioNemo LLM Service extends the model usage beyond language to include tasks such as text summarization, chatbots, software development, protein structure and biomolecular property predictions, and more. Both services will be offered in early access starting next month.
4. Wombo Dream

Wombo Dream is a text-to-image AI art generator that produces original "artworks" depending on a text prompt. It's available for iOS and Android and is the work of a Canadian firm that first gained notoriety for an app that lets you feed in static images to create lip-synced renditions of memeable songs. We're not sure what exactly powers this app, but we suspect it uses artificial neural networks (the same kind that power NeMo and a host of other similar programs).

Basically, users simply input a text description, select an art style they like, and then watch as the program works its magic. The results can be quite stunning artistically, and the app is a fun way to spend a few minutes if you're feeling stuck for inspiration.

One thing to note, though: While some of the generated art is genuinely gorgeous, some of it also feels a bit odd or queasy. It's interesting to see what the program will come up with for a prompt, but some of it isn't that realistic -- it almost seems like it's being forced to make something to fit a given style.

Another great AI program for visual artists is Craiyon (formerly DALL E Mini). This is an easy-to-use AI tool that's perfect for those who don't want to get too complicated with their creations. Users can choose from a variety of preset images and then customize the size, color, or background of their creations. The program also offers the ability to generate photorealistic images, merge a base image with a famous painting style, and much more.

Those interested in trying out an even more advanced version of DALL E should check out the DALL E 2 program. This AI tool allows users to do a lot of customization and gives them total flexibility in what they can generate. While it may not be as easy to use as other programs, it's definitely worth checking out if you're looking for more advanced capabilities. It's also a great option for NFT creators as it can easily generate NFT artwork based on a text prompt.