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3 Survivors : 1397 Models, 16,548 txt files, 8+ hrs of video (& no poems yet): Wavenet for Poem Generation: Secondary Results (After training for 6+ weeks continuously)
From 26-10-2016 to 11-12-2016, Wavenet-for-Poem-Generation (code on github) trained on an 11k poem corpus simultaneously in 7 different tabs of a terminal window (on a 8-core G5 each tab occupied a core of the CPU) — each tab was using different parameter settings. In the end only 3 settings exceeded 100k training epochs before succumbing to…
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T-SNE Animator
Same Data, Same Code (Different Parameters) Jhave (2016) Python code, T-SNE algorithm, 6689 poems Cloud support by Karteek Addanki Information visualizations normally change as the data changes. In this demo, the data (6689 poems) stays the same, but visualizations change as the parameters change. HD video generated from Python script. Project Code on Github: https://github.com/jhave/TSNE-animator Exhibited…
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Wavenet for Poem Generation: preliminary results
For the past week, I’ve been running a port of the Wavenet algorithm to generate poems. A reasonable training result emerges in about 24 hours, — a trained model that can generate immense amounts of text relatively quickly. On a laptop. (Code: github). By reasonable I mean the poems do not have any real sense, no sentient self, no…
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2-layer 256-cell LSTM neural net trained on a source text of moderate size
Yesterday, sitting in Hong Kong, I launched a cluster of GPUs in North Carolina and ran a neural net for 9 hours to generate proto-language. Using modified code from the Keras example on LSTM text generation (and aided by a tutorial on aws-keras-theano-tensorflow integration), the cluster produced 76,976 words. Many of these words are new…
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LSTM CHARRNN: blossoming acronyms
Machine learning hacks. Building poetic nonsense with neural nets. mules and the technology, the created and the tractions and the tractional artically of the traction of the tractical processe of the prectional and and and structured the entional the eractions of the the tractions and the tractions of the termore the the creative of…
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ELO Performance (Brief Reproduction)
Read a screen where code is rapidly producing poems. Find a path through the words: construct a poem from machinic intuition. The following recreates a performance made at the Electronic Literature Organization conference in Bergen, Norway on Aug. 4th 2015. Details: http://bdp.glia.ca/smaller-words-shrink-gapped Code: https://github.com/jhave/Big-Data-Poetry Technical process: the following poems were produced using a 10,000+ corpus…
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ELO 2015 — Bergen – Performance
One of the ends of digital literature is an external intuition. External intuition is an engineering problem. Intuition in this case is me. Skidding thru the generated poems as they augment my imagination. I call this act of augmented imagination: cyborg/ skid/ spreedr poetry. #### For the performance, at ELO conference performance in Bergen, Norway…
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Spreeder: the feature film (EPC 20th Anniversary Celebration)
Loss Pequeño Glazier is celebrating the 20th anniversary of the Electronic Poetry Centre along with Charles Bernstein, cris cheek, Tony Conrad, Steve McCaffery, Myung Mi Kim, Tammy McGovern, Joan Retallack, Laura Shackelford, Danny Snelson, Dennis Tedlock, Cecilia Vicuña, Elizabeth Willis, & Wooden Cities with Ethan Hayden. Along with exhibitions by: “Abra” (Amaranth Borsuk, Kate Durbin…
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t-SNE: Classification of 10,557 poems
Once again: there is much magic in the math. The era of numeration discloses a field of stippled language. Songlines, meridians, tectonics, the soft shelled crab, a manta ray, a flock of starlings. In the image below, each dot is a poem. It’s position is calculated based on an algorithm called t-SNE (Distributed Stochastic Neighbour…
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SPREED : Speed Screen Reading : One Hour Real-Time Poetry Generation ScreenGrab
Using Python (Anaconda), NLTK, WordNet, Alchemy, pattern.en, and pyenchant to analyze and perform word replacement on a corpus of 10,119 poems scraped from the PoetryFoundation and generate 7,769 poems in approx. 2 hours and 30 minutes. This is a real-time hour-long screen-grab output of the trace window in SublimeText as the poetry-gen program runs. 8:40-9am: 1097 Poems…