An in-progress list of clickable AI resources & tools to play with – more coming soon!
💡General Creative AI / Multimodal
- ChatGPT
- Microsoft Copilot
- Perplexity (bonus vs ChatGPT: Perplexity mentions its citations/sources)
- Claude
- Gemini
- Hugging Face
- Vercel
- Gamma (presentations, slides, websites)
- Artlist
- Adobe Firefly
- Granola AI (note-taking)
- PiAPI
- Freepik (all-in-one creative suite)
- n8n (workflow automation)
- MeshyAI (3D modeling)
- Poly.Cam (3D modeling)
- Tripo (3D design and animation)
- Base44 (app design)
🎬 Video Generation, Editing & Post-Production
- Sora (OpenAI) – not yet publicly available
- Runway
- Pika Labs
- Luma & Luma Dream Machine
- Kling AI
- LTX Studio
- Synthesia
- Topaz Labs
- FinerCut
- Google Veo & Flow
- 3D AI Studio
- Hailuo AI
- Koyal AI
- Heygen
🧩 Motion, Film & Creative Coding
🖼️ Image Generation & Visual Art
- Midjourney
- Nano Banana
- SeaArt / SeaDream 4.0
- Krea
- OpenArt
- Stable Diffusion
- Magnific
- Freepik AI Image Generator
- Meshy AI (3D models, textures, animations, and scenes)
🎧 Audio, Music & Voice
📦 Production & Stock IMAGES/ Videos
🧠MORE RESOURCES & DATABASES:
Creative AI Lab: https://creative-ai.org/
Machine Cinema https://machinecinema.ai/
Aideo tools database: https://aideo.pro/
PlaylabAI – easy software creation for educators: https://www.playlab.ai/
Curious Refuge: https://curiousrefuge.com/
Generative AI Track Tutorial Video: https://youtu.be/QdExCik6sww
Open Source Image Software (from tutorial): https://github.com/TheLastBen/fast-stable-diffusion/
Projects & Tools – Berkman Klein Center: https://cyber.harvard.edu/projects-tools
Transfer Data Trust – a decentralized artist-owned archive: https://transfer.art/trust (read this relevant article for more future affordances of such data co-op initiatives)
Gemini API step-by-step tutorials (image, video, image, etc) and vibe coding https://ai.google.dev/gemini-api/docs/video?example=realism
LexicaArt: https://lexica.art
AR Track AR Art Creation: https://artivive.com
NFT Track NFT Contract Templates w/@thirdweb : https://portal.thirdweb.com/pre-built-cont – thanks to Chris Johnston @cjohndesign for the twitter links
More to check out (under review):
Dream Machine (by Luma Labs) — A text-to-video model capable of creating short scenes with compelling motion sequences.
Veo (by Google DeepMind) — Generative video model that pairs video and audio, supporting multimodal storytelling.
Synthesia — AI platform for creating videos from text using avatars and multilingual voices.
Neural Frames — AI animation generator with frame-by-frame control, works for music videos & abstract visuals.
Artlist AI Video Generator — Tool to turn still images into dynamic short videos using AI.
Veed.io AI Video Generator — Streamlined web tool for turning text → video with automated narration and scenes. .
Runway Gen-3 / Gen-4 Video Model — Generative video model platform with advanced video creation capabilities.
Adobe Firefly Video & Mixed-Media Generator — Adobe’s generative AI platform, now including video generation.
Hedra Video Generation Platform — Startup making character-based AI video/voice/motion; viral “baby interviewing dog” clip example.
Check out the AI Pedagogy section for more suggestions, and use the comments below to add your own suggestions. We welcome partnerships with creators and ed tech companies – contact mh193[at]nyu[dot]edu for more info.
Header image: Luke Conroy and Anne Fehres & AI4Media / https://betterimagesofai.org / https://creativecommons.org/licenses/by/4.0/ | Alt text: An array of colorful, fossil-like data imprints representing the static nature of AI models, laden with outdated contexts and biases. | Message: This image uses the metaphor of the ‘fossil’ to represent the data which AI models are constructed of. The idea of fossil data helps to capture the contextless nature of many AI models. AI models draw upon millions of data imprints, from specific times and places. Such contexts are then stripped away when this data is then used in new ways. In using these ‘fossils’ to create new ideas and imagery, it is important to recognise the old prejudices and contextless ideas held within. Engaging with an AI dataset should therefore be seen as sorting through these old ideas (similarly to an archive) rather than presenting it as some kind of active learning superintelligence.