Now that two thirds of out first collab edition "After Her CalmWafer™ Installation" are sold @presstube and I are trying out a new way of offering the rest of the edition - I call it the "Presstube Method". Let me explain.
We started the edition at a price of 10 tez which makes it very affordable for early birds. But now for the remaining ones we will always just put one of them on the market and with every sale we will raise the price by 10 tez.
The current one is already at 70 tez and if that changes hands the next one will be 80 and so on.
Of course we are playing with a bit with FOMO here, but think that it is still a fair deal that gives everyone a chance according to their budget.
I actually hope that I can convince @hicetnunc2000 to add this as an automatic option where everyone can set their initial set size, the starting price and the subsequent increase.
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@smgstudio@tezos To start collecting you first need a @tezos wallet which is a piece of software that handles all the transactions and logins and which you use to access your funds and collectibles on the blockchain.
@smgstudio@tezos@TempleWallet@KukaiWallet@CryptonomicTech Next you need some $XTZ. If you are planning to start by minting and selling your own art you need very little of it - less than 1 tez and if you post your wallet ID and shout out someone from the community will surely help you out and send you your first tez.
"Here or There" - a quick test for navigating @hicetnunc2000 by a cluster map. This is a temporary url and an absolutely no-comfort UI, but you can scroll and click through to the objects (even browser-zoom). Also not tested on mobile.
Let me know if it does not work on your brower or you get a different image than the one you clicked on - I only tested this on Chrome and I really do not enjoy Javascript.
Also - there are some NSFW images in there since I did not filter the raw IPFS data - I hope that you can ignore them at that size.
Okay, here's my first aggregation clustering based on ResNet features of the current @hicetnunc2000 collection. Note that I use a grid representation for animations and movies which tends to cluster those together. Zooming in recommended.
For those who prefer more of a color-based neighborhood here's an early arrangement of the same data using the thumbnails themselves as the feature vector. It will smooth out some more the longer I boil it.
A slightly further evolved arrangement of this is now available as an edition of 50 for 3 tez here: hicetnunc.xyz/objkt/4202
For an upcoming collaboration I created an algorithm that edits music videos autonomously by selecting the best matching scenes and cuts for a given song. Here's a test with some found glitch material.
Song: Time Traveler (eroded by time mix) by ghosts4hire
CC BY-NC 3.0
Full length version here:
And whilst in the end it does not really matter, just for understanding how this works: the glitches are already in the material and were not added afterward based on the sound.
Another attempt at a longer piece. An imaginary Jerome K. Jerome writes about Twitter. All I seeded was the title, the author's name and the first "It", the rest is done by #gpt3
It's like programming, but with free text. I don't think a five-year old could do that. #gpt3
It took me three attempts to refine my instructions (on the left) until the model understood what I wanted. Output on the right.
There is more...
Talk about generalization. (And playing a nice trick in the second one - at first I thought it was falling in the classic mix-up trap, but did a great save here.)