Generative AI is a type of Artificial Intelligence that can create a wide variety of data such as images, video, text, audio and 3D models. Generative AI has potential applications across a wide range of industries, including fashion, software development and fashion.
In today’s world, Generative AI is used to gain a competitive edge in many – if not all – industries. Generative AI is also a set of algorithms, that are capable of generating seemingly new, realistic content (audio, images or text) from the training data.
Most of the powerful generative AI programs or algorithms are built on top of foundation models that are trained on a vast quality of unlabelled data in a self-supervised way to identify underlying patterns for a wide range of tasks.
Some use cases of Generative AI can be applied in the following instances:
1. Conversational AI: With the rise and awareness of ChatGPT, Generative AI can be used to generate responses to users in the form of natural languages. The commonly used conversational AI comes in the form of virtual assistants and chatbots. They can be used to perform tasks, provide information and answer questions.
2. Fraud Detection: Generative AI provides banks with algorithms to leverage real-life examples. For example, Swedbank makes use of GAN (Generative Adversarial Networks) to detect fraudulent transactions. They are trained to learn legal and illegal transactions in order to detect fraudulent ones by creating graphs that reveal their patterns.
Another instance is an expense platform, Brex, which partnered with OpenAI to launch chat-powered spend benchmarks insights for customers; Hedge fund Citadel is in talks for an enterprise-wide ChatGPT license that will be used for software development and information analysis.
3. Image Generation: Users can use generative AI to transform texts into images and also generate photos based on a setting, style, theme or location that they specify.
4. Image-to-Image Conversion: This involves changing, altering or transforming external elements of an image such as its form, shape, colour or medium while preserving its constitutive elements. An example of image conversion could be turning a cloudy day image into a rainy-day image or a facial manipulation.
5. Player behaviour analysis: In gaming, generative AI can be used in analysing a character or player’s data – preference and gameplay patterns. It helps in providing personalized game experiences and helps game developers increase player retention and engagement.
6. Writing product guidelines and descriptions: Generative AI like ChatGPT helps create compelling and informative product descriptions that can resonate with your target audience. Product descriptions are a major (crucial) part of marketing, as they provide potential customers with information about the features, benefits and value of a product.
Importance of Generative AI Tools (In Various Fields)
Generative AI has shown significant potential for use in creative industries including fashion, music or art.
1. In media and entertainment, generative AI helps media companies engage and retain their audience. It could go from enabling more recommendations on their digital content platforms.
2. In healthcare, generative AI can generate personalised treatment plans based on a patient’s medical history. It can also help improve the accuracy and efficiency of using machine learning in combination with medical imaging techniques – MRI and CT scans. Generative AI can also help speed up the process of drug discovery and development.
3. In education, generative AI can help design or organise course materials including assessments, syllabi and lesson plans. Course materials can be personalized based on students’ knowledge gaps, learning styles and skills.
4. In fashion, generative AI can be used to enrich product and design ideas by collaborating with AI (agents) that will generate creative options from data.
Examples of Popular Generative AI Tools
Generative AI tools have been around for a long time and it applied in a lot of industries. In this section, we’ll look at some popular AI generative tools.
1. Unity for game development
Its programming language is in C and C++ and it’s a cross-platform game engine that’s developed by Unity Technologies. It was first announced and released in June 2025 at Apple Worldwide Developers Conference as a Mac OSX game engine.
Unity is highly considered easy to use for beginner developers and also popular for indie game development. Unity is used to create three-dimensional (3D) and two-dimensional (2D) games as well as interactive simulations.
2. GPT-3 for text generation
Generative Pre-trained Transformer 3 was released in 2020 and it’s an autoregressive language model that uses deep learning to produce human-like text.
3. DeepDream for Image Processing
Founded by Alexander Mordvintsev, DeepDream uses a convolutional neural network to find and enhance patterns in images via algorithmic pareidolia. DeepDream is designed to work in a way to detect faces and other patterns in images with the aim of automatically classifying images.
4. Amber Music for Music Composition
This platform makes use of an Artificial Intelligence composer that creates unique music tailored to any content instantly.
5. Artbreeder for Creative Art Generation
Formerly known as Ganbreeder, this art generation platform makes use of BigGAN and StyleGAN models and lets (website) users generate and modify their images ranging from faces, landscapes and or paintings.
Categories Of Generative AI Tools
A. Image and Video Generative AI Tools
These tools are used to generate realistic images from texts. It’s based on a deep learning algorithm which has been trained on a large dataset of images and their corresponding descriptions.
This multi-platform photo editing software was launched in 2012 and BBC dubbed it Photoshop Lite. It has a full suite tool collection that covers major image editing needs. It’s available on mobile devices, as a web app and on desktop computers. Fotor has a Fotor AI Image Generator that let users make art with words.
An OpenAI system that creates realistic images and art from just a description of natural languages. It also has a combination of styles, concepts and attributes. DALLE-E-2 is a deep learning model that’s developed by OpenAI to generate digital images from natural language descriptions called prompts. OpenAI announced DALLE-E-2 in April 2022 (it’s a successor to DALLE-E) which was revealed by OpenAI in a blog in January 2021).
DALLE-E-2 is designed to generate more realistic images at higher resolutions. The images have a combination of attributes, styles and concepts. DALL-E is a portmanteau of the names of an animated Pixar character WALL-E and the Spanish surrealist artist, Salvador Dali.
Founded by Angus Russell, NightCafe was created in November 2019 and it has created over 35 million AI-generated artworks. It was originally a neural-style transfer app and launched on Reddit. When creating artwork, you can choose styles ranging from Anime, Cubist V2, NightCafe and a long list of other styles.
Daily challenges are held with a chance to share in some prizes and you can explore other AI-generated artworks that have been created with NightCafe. The image platform comes with two conversion models – Style Transfer and Text to Image.
Similar to Stable Diffusion and OpenAI’s DALLE-E, Midjourney is an AI program and service that’s hosted by a San-Franciso-based independent research lab – Midjourney. The platform is currently in open beta mode (since July 12, 2022) and it’s led by David Holz (the founder of Leap Motion).
This image generator creates images from scratch from a text description. The generated images can also be used for NFT and its model is based on Stable Diffusion. The image quality is not as photorealistic as other AI image generators; however, a developer can use it to connect to another software project.
Formerly known as the DALLE-E mini, this AI model can draw images from any text prompt. It was developed as a lighter version of OpenAI’s DALLE-E; hence the name DALL-E mini.
Craiyon was initially trained on millions of images from the internet and captions that accompanied them – this is how it creates its images from just a text prompt. The platform was/is developed by Boris Dayma at JAX/FLAX Community Week in June 2021. Craiyon usually takes 2 and a half minutes to generate images from the interactive web demo.
7. Stable Diffusion
It was released in 2022 and the deep learning, text-to-image model is primarily used to generate detailed images that have been conditioned based on text descriptions. Stable Diffusion is not yet just limited to text descriptions, it’s applied to tasks such as generating image-to-image translations, inpainting and outpainting guided by a text prompt. Stable Diffusion was developed by StabilityAI.
Stable Diffusion, a latent diffusion, can run on most consumer hardware that’s equipped with a modest GPY with at least 8GB VRAM. The latent text-to-image diffusion model is capable of generating photo-realistic images given any text input and cultivates autonomous freedom to produce incredible stunning art within seconds.
It was formerly known as Ganbreeder and it’s a collaborative, machine learning-based art website. Artbreeder makes use of BigGAN and StyleGAN models that lets the website allow users to generate and modify images of faces, paintings and landscapes among others. It was launched in 2018 and users use the tool to remix (breeding other users’ images) found in the public database of images.
It’s done by tweaking parts (genes) and they range from facial hair, gender, glasses and colour. Images can also be crossbred and Artbreeder was created by Joel Simon.
9. Deep Dream AI Generator
Alexander Mordvintsev created this program and it uses a conventional neural network to find and enhance patterns in images via algorithmic pareidolia. In other words, Deep Dream creates a psychedelic image or concept from overprocessed images.
Although you need to have an account on the platform, Deep Dream is free to use.
10. Runway ML
Founded by Cristobal Valenzuela, this image generator allows you to generate images by using machine learning models. Runway tools include relative motion analysis and out-of-the-box object recognition that helps you easily identify objects in images or videos.
The first prototype was built in Seattle in 2019 and the first version of the product was launched in July 2020. The video generator ai tool is cloud-based and it automatically converts long-form text and video content into short videos for social sharing using AI. It automatically finds matching stock videos for your text.
With this tool, you can create professional AI videos from a text in over 120+ languages. They are based in London, England and the software algorithm mimics facial movements and speech based on video recordings of an individual’s speech and phonetic pronunciations.
Synthesia was developed by Matthias Niessner and Lourdes Agapito and co-founded by Steffen Tjerrild, Victor Riparbelli, Lourdes Agapito and Mattias Niessner.
13. Deep Brain AI
The private company provides a range of AI-powered customer service products. DeepBrain AI helps you create AI-generated videos just using simple text. With over 80+ languages, AI avatars can speak any language with text-to-speech. There are also prebuilt video templates on a range of videos including – social media templates for Instagram, YouTube, TikTok, news videos, marketing videos, explainer videos, and how-to-videos.
It was founded in 2021 and the deep tech startup company is a global team of AI technology devotees. The platform is beneficial for users looking to create training videos without post-production, actors or voiceovers. There are over 60 languages available with more than 25 avatars to choose from.
The cloud-based video-making platform is designed or built to assist businesses and manage steps, actions & processes for creating and editing video content. It’s powered by AI and machine learning, it automatically converts text, images and social content into engaging marketing videos.
This is an easy-to-use- AI-backed video generative tool. It offers 5000+ designed templates for social media, corporate, birthday, education, business, promo & sales, festivals and special events. It was founded by Lin Xiao and developed by Pearl Mountain.
With InVideo, you can create professional quality social media ads, promo videos and much more for your industries and businesses. It has a variety of video templates ranging from slideshow templates, social media video templates, outro/intro video templates, business video templates, and marketing video templates among others. You create videos from input text.
The private company functions as a mock-up maker, design maker, video maker, AI-powered logo maker and a SaaS platform. With more than 20 languages, you can use the platform’s text-to-video technology to transform articles, posts or scripts into fully edited videos.
This platform is an online automatic video editing software that makes use of AI and voice recognition that edits videos for you. With this platform, you easily turn your long-form (talking) videos into short clips with subtitles, auto frames and music. You can also improve your video engagement with generated subtitles.
This AI-powered innovative platform empowers teams to generate videos in minutes. The platform has automatic text summarization branded theme and abundant media resources.
B. Natural Language Processing Tools
Natural language processing tools help you discover insights in scattered and unstructured texts and then solve a variety of text analysis problems like topic classification and sentiment analysis.
Natural Language Processing refers to an interdisciplinary subfield that consists of Artificial Intelligence, Linguistics and Computer Science – they are concerned with the interactions between computers and human language. The goal is to understand the contents of documents including the contextual nuances of the language within them.
This software is developed and implemented in Python and Cython for performance. It’s designed to handle large text collections using data streaming and incremental online algorithms. It was founded by Radim Rehufek in 2021. Gensim is a tool for extracting semantic concepts from documents and it handles extensive text collections.
The platform can perform various complex tasks using contemporary models and statistical machine learning including the identification of a topic, the creation of word or document vectors. It’s used in a large number of applications including Latent Semantic Analysis (LSA), Word2vec, FastText, Latent Dirichlet Allocation (LDA), and Term Frequency-Inverse Document Frequency (TF-IDF).
This private platform is a Text Analysis platform that uses Machine Learning to automate business workflows and in doing so, save hours of manual data processing.
MonkeyLearn makes it simple to clean, label and visualize a customer’s feedback – in one place. It is equipped with pre-made templates, dashboards and templates that are tailored to business scenarios.
This software/platform is an open-source software library for advanced natural language processing, written in the programming languages – Cython and Python. It’s published under the MIT license and was developed by Ines Montani and Matthew Honnibal.
SpaCy focuses on providing software for production usage and the platform also supports deep learning workflows that allow connecting statistical models trained by popular machine learning libraries like MXNet, PyTorch or TensorFlow through its own machine learning library Thinc.
SpaCy has statistical models for over 23 languages including Chinese, English, Portuguese, Russian and Spanish.
TextBlob is a Python (2 and 3) library for processing textual data and it provides a simple API for diving into common natural language processing (NLP) tasks such as noun phrase extraction, sentiment analysis, and part-of-speech tagging.
25. IBM Watson
This tool was named after IBM’s founder and the first CEO – Thomas J. Watson. The question-answering software is capable of answering questions posed in natural language, developed in IBM’s project by a team led by principal investigator David Ferrucci.
Also known as Generative Pre-trained Transformer 3, the autoregressive language model was released in 2020 and it uses deep learning to produce human-like text. Over 300 apps are using GPT-3 across varying industries and categories ranging from games to productivity to education to creativity.
GPT-3 generates an average of 4.5 billion words per day.
This is a Java Machine Learning for Language Toolkit. It was developed by Andrew McCallum (with contributions from several graduate students and staff) in May 2016. Mallet is an integrated collection of Java code and its use for statistical natural language processing, topic modelling, cluster analysis, document classification and other machine learning applications to text.
28. Intel NLP Architect
It’s designed to be flexible for adding new models, data handling methods, and neural network components for easy training and running models. It’s an open-source Python library for exploring state-of-the-art deep learning technologies and techniques for optimising Natural Language understanding neural networks.
29. Standard NLP Group
They provide statistical NLP, rule-based NLP for major computational linguistics problems, and statistical NLP and they can be incorporated into applications with human language technology needs. Standard NLP Group is widely used in government, industry and academia.
The platform removes the guesswork from understanding brand, product, employee and customer experiences. The private company empowers you with deep insights for your team(s) and leadership and also improves your company’s bottom line.
Also known as the Natural Language Toolkit, it’s a suite of programs and libraries for symbolic and statistical natural language processing (NLP) for English written in the Python programming language.
NLTK was developed by Edward Loper and Steven Bind, it also includes sample data and graphical demonstrations. The toolkit is also developed to support teaching and research in NLP or closely related areas including artificial intelligence, information retrieval, cognitive science, machine learning and empirical linguistics.
David Cournapeau developed it and it’s a free software machine-learning library used for the Python programming language. It has simple and efficient tools for predictive analysis and it’s built on SpiCy, NumPy and Matplotlib.
This machine learning framework is based and built on the Torch library and it’s used for applications such as natural language processing (NLP) and computer vision. It was originally developed by Meta AI and is now part of the Linux Foundation umbrella.
34. Apache OpenNLP
This is a free and open-source cross-platform web server software which was released under the terms of Apache License 2.0. It’s originally authored by Robert McCool and it’s written in C and XML. Apache is capable of handling static files, auto-indexing, index files and content negotiation.
35. Google Cloud
This platform helps meet your industry and business challenges with Cloud Computing services from Google including data management, artificial intelligence, machine learning, and multi and hybrid cloud. It offers several pre-trained models for entity extraction sentiment analysis and content categories.
Published in 2013m word2vec uses a neural network model to learn word associations from a large body of text. It’s one of the most popular implementations of word embedding and it’s used to create distributed representations of words into numerical vectors.
This is an artificial intelligence startup that focuses on creating technologies that help machines understand human languages better. AYLIEN leverages artificial intelligence to empower thousands of forward-thinking enterprises and developers to collect, analyse and understand vast amounts of human-generated content.
38. Rapid Miner
This is a data science platform designed for enterprises that analyses the collective impact of organisations’ employees, expertise and data. It was formerly known as YAE (Yet Another Learning Environment) and was developed starting 2011 by Simon Fischer, Ingo Mierswa and Ralf Klinkenberg.
Rapid Miner is an enterprise-ready data science platform that amplifies the collective impact of your expertise and data.
39. Amazon Comprehend
This is a natural-language processing (NLP) service that uses machine learning to uncover valuable insights and connections in text. It helps you detect customer sentiment and analyse customer interactions and automatically inbound support requests.
You as a user, can extract your customer’s survey to improve your products.
Known for Bidirectional Encoder Representations from Transformers, it was introduced in 2018 by researchers at Google. BERT is an open-source machine learning framework for Natural Language Processing (NLP).
C. Music and Sound Generative Tools
These are tools that work when you feed large amounts of data to AI algorithms that study tracks, chords and other data to determine patterns for creating music.
41. Amper Music
This private company is an artificial intelligence composer, producer and performer that creates unique music tailored to any content instantly. It was founded by Drew Silverstein and the platform provides musical individuals (and non-musical individuals) the ability to take their idea and turn it into music. It’s also designed to require a minimum amount of input to create a unique piece of music and every piece of music is created from scratch.
This is an AI-powered music creation platform that enables creators and artists to analyse, create and monetize music. You have the ability to generate unique, royalty-free tracks at the click of a button.
43. Ecrett Music
It enables anyone (creative or not) to generate and create clips of music by training on hundred hours of existing songs. Structures and instruments can be custom-made with a few clicks. Ecrett Music allows you to compose music for any game or video, and it comes with a royalty-free music generator to avoid issues with listening.
This platform creates infinite streams of artificial intelligence music for gamers. It also composes of an infinite stream of original, emotionally variable music in real-time.
It was created in February 2016 and the platform/tool specializes in symphonic music and classical composition. AIVA became the world’s first virtual composer to be recognised by a music society – SACEM. AIVA also has the ability to detect regularities in music; it’s based on deep learning and reinforcement learning architecture.
It’s created by OpenAI and it’s a deep neural network that can generate 4-minute musical compositions with 10 different instruments. It can also combine styles from country to the Beatles to Mozart.
The platform operates by using a deep neural network that has been trained on a dataset of MIDI files gathered from a range of online sources that cover Arabic, Jazz, and Pop styles of music.
It’s based in Tokyo, Japan and the private company is an AI royalty-free music generator for video creators. With SoundRaw, you don’t spend hours searching for the music you need, rather the AI creates it for you in seconds.
This platform offers high-quality natural-sounding AI voices for your (creative) projects. Murf gives you a selection of 100% natural-sounding AI voices in 20 languages that can make professional voices for your videos and presentations. You can also use a text-to-video converter that sounds like studio-quality voiceovers.
If you are in the corporate or entertainment sphere, there is a voice for every sector.
You are able to make music with your voice. It’s powered by Web3 and it’s used to create studio-quality music on your phone by just using your natural voice with the help of AI.
The created or generated music can be accompanied by vocals and it’s adjusted with 5 different effects.
This music generator generates fully produced music at your command. You don’t have to be a music professional or a producer to get started. Boomy makes use of AI-powered algorithms that help emulate musical styles.
This is an AI-driven software engine that generates music. It also reacts to code, other sounds, gestures and movements. Musico uses its engine to blend traditional and modern machine learning algorithms to generate endless streams of copyright-free music in a wide variety of styles.
Musico has a semi-generated and fully automatic composition generative approach that empowers creators with music with new ways of producing sounds. It can also generate beats, harmonies, and melodies by blending, autonomy and responsiveness.
52. Chrome Music Lab
This is a website that makes learning music more accessible through fun and animated hands-on experiments. The Chrome Music Lab is built on technologies like Tone.js, Web Audio API, WebMIDI and more. Chrome Music Lab is not an AI music composer hence it’s just designed to make anyone compose a piece of music.
This is a cutting-edge generative AI music platform that facilitates innovative music content, interactive music experiences and digital collectables. It’s purposely built for gaming and streaming applications and the platform also composes songs note-by-note and also creates original music limitlessly. Warpsound is trained in music theory and song structure.
This platform uses advanced AI music generator techniques for composing unique mood-based music to suit each and every part of your videos or podcast.
This is a royalty-free music platform/ecosystem for developers, content creators and brands. Mubert is also designed for app builders, filmmakers and streamers. You have the ability to create a soundtrack that fits your content’s mood and duration. You can also use personalized audio experiences to grow your business(es).
With this platform, you have the ability to create music with the power of AI that fits the mood and theme of your video game, Twitch stream, podcast or YouTube. It also has built-in mixing and mastering tools that help you tweak the sounds until it’s right. Strofe is for newbies exploring music for the first time or a seasoned producers.
57. Magenta Studio
This platform is a collection of music plugins which is built on Magneta’s open-source tools and models. They make use of cutting-edge machine-learning techniques for music generation.
This platform has its roots in the fields of digital signal processing, artificial intelligence, mathematical optimization and machine learning. The goal is to make working with videos and audio easier for journalists, sound producers, translators, video bloggers, streamers, transcribers and other audio/musical creatives.
Lalal.ai is enhanced with the capability to extract musical instruments – pianos, synthesizers, drums, acoustic guitar and bass. When the platform became upgraded, it was the world’s first 8-stem splitter.
59. Emergent Drums
This innovative music plugin utilizes state-of-the-art AI to generate an array of unique drum samples. No sound recordings are used to generate hence each sample is original.
Emergent Drums is trained on a massive database of drums and percussive sounds.
This platform is developed by OpenAI and it’s a neural net that generates music including rudimentary singing. It’s an open-source solution that produces music in various artistic styles and genres.
D. Game Development Tools
These tools are specialised software application that assists and facilitates the making of a video game. They include:
This supports the whole 3D pipeline – rigging, modelling, video editing, game creation, composition and motion tracking. Blender is cross-platform and runs well on Windows, Linux and Macintosh computers.
Even though Blender is the best open-source 3D modelling package, the software’s best-kept secret is its game engine.
It’s written in C++ and C languages and it’s used to create 3D and 2D games. Unity is a cross-platform game engine that’s developed by Unity Technologies. Unity has been around since 2005 and it was made in order to provide developers access to game development tools. It has virtual reality and augmented reality capabilities.
Developed by Incredibuild Limited, this is a grid computing software start-up based in Tel Aviv, Israel. You are able to build amazing games faster with smarter development cycles and it accelerates your game development tasks by up to 30x for indie studios, AAA game empires and everything in between,
64. Unreal Engine
This tool is developed by Epic Games and it’s a 3D graphics games engine written in C++. It features a wide range of mobile, virtual reality, console and desktop platforms. Unreal Engine has robust Blueprint, API and C++ visual scripts, source code and everything you need to build and ship successful multi-platform games and location-based entertainment for any genre.
This is a no-code development platform that’s focused on game creation without programming, scripting or coding. Buildbox allows game developers to easily create 2D and 3D mobile games in a short time.
Buildbox happens to be one of the most accessible game engines and also the best game development platforms for creating Android games. It’s suitable and recommended for beginners with no coding experience and doesn’t require any scripting and programming skills.
This is an easy-to-learn game development engine that’s ideal for Indie developers, beginners and hobbyists. The platform has drag-and-drop assets that help visualize your scenes and you can easily browse app media assets. It’s also used to develop 2D games with some essential elements of 3D.
Its programming language is built on Objective – C, C++ and Python. It’s a cross-platform and open-source free 2D game engine, used for mobile game developers. It’s also known for its game development known for its speed, ease and stability.
68. Fusion 2.5
Fusion 2.5 is created by Clickteam which is a French software development company founded by Yves Lamoureux, Francois Lionet and Francis Poulain. Fusion is a script-free programming tool that allows users to create video games or other interactive software.
Fusion also fully supports the development of 2D mobile games and it is more suitable for static game development. Fusion 2.5 is available for MacOS, XNA, Adobe Flas, Android Flash, UWP and HTML5.
This is a free and open-source C framework used by game developers to make games for multiple platforms and other systems. It has the ability to make Windows and Windows phone games run smoothly on other systems.
MonoGame implements the Microsoft XNA for application programming interface and supports Xbox One, Linux, iOS, Nintendo Switch, tvOS, PlayStation 4 and PlayStation Vita. MonoGame uses .Net and C languages to write modern, reliable and fast game code.
This is an open-source and cross-platform developing language used to create games and apps. The platform has world-class libraries to write high-performance games and masterpieces.
71. Construct 3
Developed by Scirra Limited and is an HTML5-based 2D video game engine. This game engine is used for developing and creating 2D mobile games. Most times, Construct is used for puzzle games, role-playing games and racing games.
72. GameMaker Studio
This game engine is developed by YoYo Games. It provides cross-platform game development with a drag-and-drop programming language called Gamemaker language.
GameMaker was developed to primarily make games with 2D graphics, and 2D skeletal animations and allows out-of-the-box use of vector graphics and master graphics. It also has a large use of the standard library for drawing graphics and 2D primitives.
73. Godot Engine
This free and open-source platform was released under the MIT License. It’s written in C++ and it allows developers to create games needing no other tools beyond the basic used for content creation – music and visual assets.
Godot engine also boasts of UI editing and beginner developers can benefit from its node-based interface.
Originally called StencylWorks, this video game development tool allows users to create 2D video games for the web, mobile devices and computers. It has an intuitive toolset that accelerates your workflow and it has a simple block-snapping interface with hundreds of ready-to-use blocks.
The programming language is built on Lua and it’s a free open-source, cross-platform software development kit. It was originally developed by Corona Labs Inc.
It allows game developers to build 2D mobile apps and focuses on ease of usage and iterations.
This is a 2D game framework used for making HTML5 games for mobile and desktop. The free software is developed by Photon Storms and it operates with the MIT License. It enables fast rendering for desktop and mobile platforms because it internally uses WebGL and Canvas renders.
This tool comes with excellent technical documentation and the game engine is free; it’s used for the development of games for mobile, console, web and desktop platforms. Defold is used by professional game developers and hobbyists. It’s a proven tool for games of all genres.
78. Startling Framework
This is an open-source game framework used to create 2D games that run on both desktop and mobile platforms. It makes use of Adobe’s AITtm technology and it can be run on iOS, web browser and Android.
This is mainly aimed at non-programmers and game developers of all skill sets. The 2D cross-platform is a free and open-source game engine which mainly focuses on creating mobile games and PC, as well as HTML5 games playable in the browser.
With GDevelop, you easily create objects and drop them in your scene to use them – you choose from texts, particle emitters, sprites and many more.
Marmalade lets you make projects or games from single-player 2D games to multiplayer 3D titles. It requires C++ knowledge but it’s the quickest way to create cross-platform C++ games for several platforms.
E. Art and Design Tools
These are software tools that make use of Artificial Intelligence to create unique and creative images and artworks from pre-existing data or text prompts.
As a user, you don’t need to know (complex) design software or technical skills to create high-quality images. AI art generators take advantage of deep learning algorithms to analyse vast amounts of data such as drawings, paintings, photographs and patterns to develop new images based on the user’s input and descriptions.
This is an AI art generator that allows users to create unique, creative and customisable images. It requires no technical skills and it can generate various images of anime figures, landscapes, portraits and more.
This platform has a fully integrated suite of image-generation tools. You have the flexibility of creating any type of art to widen your creativity and get different art styles.
This platform was initially launched on Reddit and you can choose artwork styles ranging from Anime, Cubist V2 and NightCafe to
This is a free multilingual and open-source AI image or art generator that uses Stable Diffusion.
This AI art generator app works by you entering or inputting a text prompt and the AI turns your work into a work of art. It’s free to use and offers the latest state-of-the-art methods in your art creation. You can also create NFT art with StarryAI.
86. Dream by WOMBO
This AI art generator works by entering/inputting a prompt, choosing an art style (could be analogue, realistic, comic or paint) and then turning your prompt/idea into an AI-powered painting. It’s also an AI NFT creator platform and it’s been considered by a lot of users to be the best all-round NFT creator app.
87. DALL-E 2
DALL-E 2 creates realistic artwork from a text description in natural language.
88. Bing Image Creator
You generate AI images based on your prompts or texts. All you need to do is to visit the website and then sign in with a Microsoft account.
Midjourney is used to create unique pieces of artwork. It works by inputting text-based prompts and the tool provides you with an original image by the use of AI and machine learning.
90. Hotpot AI
This AI art generator helps you turn your imagination into art; it produces stunning illustrations, photos and artwork in seconds. You enter your prompts and let Hotpot transform them from text to art.
When choosing your art style, there’s a plethora of styles to choose from – Isometric, Japanese/Line art, 3D, Minecraft, Portrait, Roblox, Voxel, Acrylic art, Animation, Anime, Charcoal, and Comic, among others. You select the number of images to make and rations.
91. Lexica Art
This platform is created with Stable Diffusion and it’s a search engine and art gallery for artwork. It was created by Sharif Shameem and it has indexed over 10 million Stable Diffusion images. Lexica comes in handy as it has an excellent way of checking out what’s possible with AI artwork especially if you have struggled with previous AI generators.
This platform is an AI art curation website; it has over 3 million AI-generated images for gaining inspiration. Enterprix also has a free Discord server where AI artists and AI art lovers (worldwide) gather and connect with each other.
Apart from this tool being an image generator, Fotor doubles as an impressive art generator that generates art in seconds. It operates by you inputting a text prompt that describes the image(s) you want. There are a variety of (art) styles to choose from ranging from oil painting, illustration, anime 3D, photorealistic and much more.
As a user, you can turn your personal photos into an AI-generated AI.
94. Adobe Firefly
This is in the beta phase, generating art and images from text effects from descriptions.
95. Waifu Labs
This tool makes use of Artificial Intelligence to generate custom anime portraits. It was launched at Anime Expo 2019.
96. Playground AI
With this platform, you need to get started with your Google account and you are able to work on 1000 free images per day. You can work on various categories including landscapes, anime, food, vehicles, sci-fi, fashion and animals.
Playground AI also provides a neatly designed UI and it also has an inpainting and outpainting feature that stands as the platform’s major strength.
97. Stable Diffusion
This latent diffusion AI tool generates aesthetically pleasing artwork.
98. Photo Sonic
This tool helps you create/generate artistic and realistic artwork from your text prompt or description. The generated images can be adjusted via the quality, diversity and style by editing your text description.
With Photo Sonic, you don’t get a design template option but you have the opportunity to mix and match styles by adding your own keywords to refine the artwork.
99. Wonder AI
This platform also requires you to input a text prompt and then you are free to choose the art style (personal preferences) in the likes of Cinematic, Pen and Ink, Magic, Novelistic and much more.
It’s known as DALL-E 2 mini and it doubles as both an image and art generative tool. You get artwork from simple text prompts and descriptions.
Functions of Generative AI Tools
Generative AI tools, also known as generative models, are referred to as a class of artificial intelligence algorithms that are designed to create or generate new content – irrespective of the field or industry applied.
Some of the functions of generative AI tools include:
1. In the image and video sector, generative AI can help create new images or videos that resemble real-world events or objects. An instance, image-generative AI tools can be used to create or generate scenes, realistic faces and landscapes.
2. In the music and audio sector, generative AI can create new music and audio sounds based on pre-existing models, patterns and styles. This comes in handy in areas such as sound design or composition.
3. In the text generation sector, generative AI can create new pieces of text such as outlines, poetry, articles and even stories. It also comes in handy in the development of virtual assistants.
4. In the creative sector, generative AI creates new works of art which comes in handy in game design, paintings, sculptures and also in the creation of interactive experiences.
5. In the data augmentation sector, generative AI comes in handy as it creates synthetic data to supplement existing datasets. This helps in improving the performance of machine learning models, especially in cases where the amount of training data is very limited.
As we come to the end of this article, it’s beneficial to be aware that the emergence of generative AI tools has (without a doubt) revolutionised the field of artificial intelligence by enabling machines to create new content that tends to resemble real-world events and objects.
Of the 100 generative AI tools that have been highlighted and available, each of them falls into unique categories and performs several functions and the tools have opened up new avenues for innovation and creativity.
As this technology continues to evolve, it has the potential to drive even greater advancements in AI and also unlock new possibilities for human-machine interaction.