Max Cooper's Ascent — Making of the Music video
Enter the 5th dimension
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We know you're Yearning for the Infinite, but do you yearn for dimensions too?
Welcome to Ascent from Max Cooper's latest album Unspoken Words.
So, go ahead — ascend to higher dimensions. You may forget to come back.
An early version of the Ascent video premiered at Max's Live at the Acropolis show.
The video expands on visual elements first presented at the And& festival in Leuven.
The “Ascent” digital art collection by Max Cooper and Martin Krzywinski comprises vast images of transcendence in 75 million pixels on billboards in NYC, LA, Miami, London, Berlin and Leuven.
The collection is the latest of the NFT collections curated by Mesh Lab.
They look superb in print.
buy artwork
The video builds on work I did with Max for Transcendence from the Yearning for the Infinite, which itself was based on my 2015 Pi Day art.
In 5 minutes and 55 seconds (8,520 frames), the video takes you from zero to 5 dimensions and back again.
To help you interpret what you are seeing, I walk you through the video. I also present the animation system I built for the video, which was coded from scratch.
The entire animation is built up from about 170 keyframes. Each keyframe defines (a) which objects are shown (b) the dimensionality, size and rotation of each object and (c) the zoom and rotation of the camera itself.
The walkthrough will take you through some of the important keyframes in the video — where new elements are introduced or interesting things happen.
c c0 s [w] 0.815
c c0 s [xyz] 0.15
The keyframe definitions are shown in yellow boxes under the frame — these are commands that the animation system parses as it builds the scene over time. The grey boxes show position and zoom of the camera and the actual angles and sizes of objects.
Right now, all this looks confusing — not to worry, it will all be explained in the walkthrough!
If you like math to a heavy beat and a lot of screen flashing, check out Aleph, our 6 minute video on the story of transfinite numbers.
The video is unique in that it demonstrates Cantor's diagnoal argument to proove that rationals are countable and that reals are not countable.
Mesh was founded in 2016 to explore the intersection of music, science and art. With a growing global audience and engaged community of practitioners and activists, the platform has conceived work by leading creatives in the fields of music, digital art, film, installation, code, architecture, developing collaborations and commissions with business, arts and science institutions.
Typically, Mesh projects begin with a scientific stimulus which leads to a creative expression, incorporating a variety of digital media including AR, AI, VR, NFT, spatial audio as well as physical structures and live experiences. Collaborators and commissioners include The Babraham Institute, Zaha Hadid Architects, Dolby, L-Acoustics and PepsiCo, and have been exhibited and performances at Barbican Arts Centre, Odeon of Herodes Atticus at the Acropolis and will host an interactive art installation during Art Basel in Miami from 1—2 December.
Convolutional neural networks
Nature uses only the longest threads to weave her patterns, so that each small piece of her fabric reveals the organization of the entire tapestry. – Richard Feynman
Following up on our Neural network primer column, this month we explore a different kind of network architecture: a convolutional network.
The convolutional network replaces the hidden layer of a fully connected network (FCN) with one or more filters (a kind of neuron that looks at the input within a narrow window).
Even through convolutional networks have far fewer neurons that an FCN, they can perform substantially better for certain kinds of problems, such as sequence motif detection.
Derry, A., Krzywinski, M & Altman, N. (2023) Points of significance: Convolutional neural networks. Nature Methods 20:.
Background reading
Derry, A., Krzywinski, M. & Altman, N. (2023) Points of significance: Neural network primer. Nature Methods 20:165–167.
Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Logistic regression. Nature Methods 13:541–542.
Neural network primer
Nature is often hidden, sometimes overcome, seldom extinguished. —Francis Bacon
In the first of a series of columns about neural networks, we introduce them with an intuitive approach that draws from our discussion about logistic regression.
Simple neural networks are just a chain of linear regressions. And, although neural network models can get very complicated, their essence can be understood in terms of relatively basic principles.
We show how neural network components (neurons) can be arranged in the network and discuss the ideas of hidden layers. Using a simple data set we show how even a 3-neuron neural network can already model relatively complicated data patterns.
Derry, A., Krzywinski, M & Altman, N. (2023) Points of significance: Neural network primer. Nature Methods 20:165–167.
Background reading
Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Logistic regression. Nature Methods 13:541–542.
Cell Genomics cover
Our cover on the 11 January 2023 Cell Genomics issue depicts the process of determining the parent-of-origin using differential methylation of alleles at imprinted regions (iDMRs) is imagined as a circuit.
Designed in collaboration with with Carlos Urzua.
Akbari, V. et al. Parent-of-origin detection and chromosome-scale haplotyping using long-read DNA methylation sequencing and Strand-seq (2023) Cell Genomics 3(1).
Browse my gallery of cover designs.
Science Advances cover
My cover design on the 6 January 2023 Science Advances issue depicts DNA sequencing read translation in high-dimensional space. The image showss 672 bases of sequencing barcodes generated by three different single-cell RNA sequencing platforms were encoded as oriented triangles on the faces of three 7-dimensional cubes.
More details about the design.
Kijima, Y. et al. A universal sequencing read interpreter (2023) Science Advances 9.
Browse my gallery of cover designs.
Regression modeling of time-to-event data with censoring
If you sit on the sofa for your entire life, you’re running a higher risk of getting heart disease and cancer. —Alex Honnold, American rock climber
In a follow-up to our Survival analysis — time-to-event data and censoring article, we look at how regression can be used to account for additional risk factors in survival analysis.
We explore accelerated failure time regression (AFTR) and the Cox Proportional Hazards model (Cox PH).
Dey, T., Lipsitz, S.R., Cooper, Z., Trinh, Q., Krzywinski, M & Altman, N. (2022) Points of significance: Regression modeling of time-to-event data with censoring. Nature Methods 19:1513–1515.
Music video for Max Cooper's Ascent
My 5-dimensional animation sets the visual stage for Max Cooper's Ascent from the album Unspoken Words. I have previously collaborated with Max on telling a story about infinity for his Yearning for the Infinite album.
I provide a walkthrough the video, describe the animation system I created to generate the frames, and show you all the keyframes
The video recently premiered on YouTube.
Renders of the full scene are available as NFTs.