https://promptperfect.jina.ai/

https://lilianweng.github.io/posts/2023-03-15-prompt-engineering/

https://github.com/microsoft/guidance

https://lilianweng.github.io/posts/2023-06-23-agent/

Vector Database

Qdrant

Reading: https://qdrant.tech/documentation/concepts/collections/

Pinecone

Reading: https://www.pinecone.io/learn/vector-database/

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^^ !!!! A camera that takes no photograph, but records geolocation and describes the scene. Generates an image based on the description. 😍

https://bjoernkarmann.dk/project/paragraphica

Paragraphica is a camera that uses location data and artificial intelligence to visualize a “photo” of a specific place and moment. The camera exists both as a physical prototype and a virtual camera that you can try.

https://www.rephrase.ai/

https://www.blings.io/ (ooh - mp5(?) JSON with layers… nothing in docs or specs on what this is, really, but is intriguing for CWT)

https://zapier.com/blog/best-ai-video-generator/#invideo

Mind to Image

Mind reading hats on the way! https://medarc-ai.github.io/mindeye/

Text to Image Personalization

https://skybox.blockadelabs.com/

Start with an image; personalize it to a new image based on the prompt + starter image

Text to Video

https://www.kapwing.com/ai-video-generator

https://imagen.research.google/video/

https://fliki.ai/ - Blog Posts to Videos

Video Diffusion Model

https://video-diffusion.github.io/

Video to Video

https://stable-diffusion-art.com/video-to-video/

Sound

Narration

https://google-research.github.io/seanet/soundstorm/examples/

https://github.com/lucidrains/soundstorm-pytorch

Jarvis

Jarvis is probably close to what I’m thinking with automated CWT tooling. But, I’m not completely certain I want to trust everything to AI. Automated AI agents seem to have to reason about their actions multiple over cycles to refine their output. It feels like more granular control will be less expensive. Orchestration tools like Langchain or Semantic Kernel would probably be my first choice over agents. @mojombo’s specialty is in seeing simplistic, obvious solutions to technical problems like this. ::waiting:: for him to get interested in AI tooling connectivity :grinning:

https://github.com/microsoft/JARVIS

Semantic Kernel

https://learn.microsoft.com/en-us/semantic-kernel/media/kernel-flow.png

Each ‘Joyride’ video relates the unique origin story of how an owner ‘met’ their car

https://adage.com/article/digital-marketing-ad-tech-news/carvana-gifts-ai-generated-video-histories-car-owning-customers/2493301

From twitter, showing a tiktok by ‘ElectronicBert’

Worth watching this whole video, pretty wild showcase of real world generative video.

Carvana created 1.3 million hyper-personalized videos.

Script, voice and video personalized to the specific user and their vehicle.

Customized based on details from user purchase: names, dates, addresses & created all of the videos using this information. Created a 2 minutes video script.

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Posting a simple wardley map. I often feel that wardley maps illustrate an obvious situation. However, a primary goal is to get everyone on common ground by looking at the same things. With only verbal discussion, people can easily lose context, their mind can wander, and they can drift in focus. With a graph, position sometimes has no meaning and is often vague because of no anchor point. With charts there is no space to maneuver. A map like this shows the landscape of a product or idea, the adjacent space to maneuver within, and is anchored to a common point - usually the User. Positional changes affect the map completely. Just like a military map, it is essential to show everyone the landscape which a situation is unfolding within, so that discussion and strategy stem from the same point.

Lastly, even if things are not true on a wardley map, or are up for debate (which they are!), it helps to know where others on your team believe things stand. It helps because it gets everyone talking and thinking about the space around the map. It helps to move pieces around, which brings challenge to the strategy, because the position does matter. For instance, moving something along the evolution axis impacts project management style, among other things. Product visibility (Y-Axis) to the customer helps to know what the customer will see, or not see, and can also influence decisions or direction. With a map, discussion and challenge is the goal.

Discussion

As AI Tooling evolves, it opens up new areas for those tools to be used. One area will be writing tools. The map could have shaded areas, but for now the colors represent old/new.

• The old, established writing tools are blue. These are ubiquitous, and are in a stable, basically unchanging state. These are a commodity. Pen and paper. blog platforms, journals, etc.

• The new, evolving writing tools are red. These are evolving and in a custom state. They are still finding their market, and the market will change as the tools evolve. This is where generative AI is opening the landscape.

CWTs (Cinematic Writing Tools) fall into the Genesis/Custom state. Very visible to the customer. Very new. Still evolving. Generative AI is part of them, but does not encompass everything yet. Many of the pieces are there, ready to be connected. How they will evolve, and what role they will play, remains to be seen. If there is competition, evolution will happen. As with many evolving products, the markets will change as the product evolves. Initial potential markets are: Journaling Apps, Writing Apps, Directing/Storyboard Apps. These are just the obvious areas that I know about.

Looking for music soundtrack generation also. MusicLM from google https://google-research.github.io/seanet/musiclm/examples/

So the idea is to create layers of audio. Have an underlying soundtrack, have the scene related sounds, and then possibly narration overlaid.

Example prompt from the above link:

The main soundtrack of an arcade game. It is fast-paced and upbeat, with a catchy electric guitar riff. The music is repetitive and easy to remember, but with unexpected sounds, like cymbal crashes or drum rolls.

This can be one shot to the scene generator as an example output.

Also, bookmarking this: https://vcai.mpi-inf.mpg.de/projects/DragGAN/ because it looks amazing!

Need to think of how to mash everything together into some viewable format. I thought an HTML slideshow would be slick, with the music/sounds playing and images auto scrolling. MP4 makes more sense in my head though and seems easier to tackle for some reason. If mp4 - how to mash things together, in order, and have the sounds come in at the right time, have the images transition, etc. programatically.