{"id":77791,"date":"2026-06-18T02:29:15","date_gmt":"2026-06-18T02:29:15","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/77791\/"},"modified":"2026-06-18T02:29:15","modified_gmt":"2026-06-18T02:29:15","slug":"with-latent-terrain-crack-open-ai-and-explore-neural-synthesis-in-max","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/77791\/","title":{"rendered":"With Latent Terrain, crack open AI and explore neural synthesis in Max"},"content":{"rendered":"<p class=\"wp-block-paragraph\">\u201cI\u2019m not particularly interested in typing prompts to make stuff, I\u2019m interested in breaking them and dissecting them,\u201d writes Jasper Shuoyang Zheng as he introduces Latent Terrain. Now using an intuitive, elegantly designed open-source Max external and UI, you can play the weird world of neural audio codecs like an instrument, transforming your own sounds into new textures.<\/p>\n<p class=\"wp-block-paragraph\">There\u2019s really a lot to say about this general area of activity. Unlike the hyped-up AI in music technologies stealing some headlines, the data source is your own sounds. And the processing is running locally, not in a water-sucking data center. And \u2026 well, it\u2019s just beautiful and weird, and you can play using instrumental techniques.<\/p>\n<p class=\"wp-block-paragraph\">Naturally, that is attracting musicians and experimenters, because it brings neural nets back to discovering new sounds instead of making everything sound the same.<\/p>\n<p><a href=\"https:\/\/cdm.link\/app\/uploads\/2026\/06\/web1s-1.jpg\" rel=\"nofollow noopener\" target=\"_blank\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1024\" height=\"379\" src=\"https:\/\/www.europesays.com\/ai\/wp-content\/uploads\/2026\/06\/web1s-1-1024x379.jpg\" alt=\"\" class=\"wp-image-166265\"  \/><\/a><\/p>\n<p class=\"wp-block-paragraph\">Latent Terrain is a beautiful place to start \u2014 not least because it\u2019ll be accessible to Max users, especially those already working with FluCoMa or Data Knot. It produces a visual map, a kind of warped texture, which you can move through however you like, from a mouse to a controller. You can even train your own small neural network directly in Max, and watch timbres shatter, fracture, and meld into new materials. You can carefully construct sound libraries and chart paths through them; it\u2019s deeply personal.<\/p>\n<p class=\"wp-block-paragraph\">Here\u2019s a great example by Keigo Yoshida, just to get a sense of the sound \u2014 this one using the tech to sonify EEG readings.<\/p>\n<p class=\"wp-block-paragraph\">There are also more than just demos, but artistic demos that push the technology as a way to unravel sonic meaning. I love Jiatong Liu\u2019s work here, not least because my first impression of Beijing was being struck by the Hutongs, really wanting to walk forever through them.<\/p>\n<p class=\"wp-block-paragraph\">Would love to hear more, Jasper, so consider this a first look! (The project will also be at NIME \u2013 <a href=\"https:\/\/www.nime.org\/\" rel=\"nofollow noopener\" target=\"_blank\">The International Conference on New Interfaces for Musical Expression<\/a> \u2013 in London later this month.)<\/p>\n<p class=\"wp-block-paragraph\">Jiatong Liu\u2018s nn\/m\u00e9moire is a virtual gallery soundscape built from archival recordings of Beijing\u2019s Hutong neighbourhoods \u2014 a rapidly disappearing urban soundworld. The terrain becomes an ambient archive you move through spatially. Liu described \u201clearning to deal with the unpredictability\u201d as a central design question, not a problem to eliminate.<\/p>\n<p><a href=\"https:\/\/cdm.link\/app\/uploads\/2026\/06\/005-docs.jpg\" rel=\"nofollow noopener\" target=\"_blank\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"381\" src=\"https:\/\/www.europesays.com\/ai\/wp-content\/uploads\/2026\/06\/005-docs-1024x381.jpg\" alt=\"\" class=\"wp-image-166266\"  \/><\/a><\/p>\n<p class=\"wp-block-paragraph\">It\u2019s also all exquisitely well documented, so dive in. There\u2019s this article by Jasper, which is a good guide through the work and its possibilities:<\/p>\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/jasperzheng.cc\/works\/latent-terrain\" rel=\"nofollow noopener\" target=\"_blank\">Latent Terrain: Dissecting Neural Audio Codecs<\/a><\/p>\n<p class=\"wp-block-paragraph\">And a project page, including the research:<\/p>\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/jasper-zheng.github.io\/nn_terrain\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/jasper-zheng.github.io\/nn_terrain\/<\/a><\/p>\n<p class=\"wp-block-paragraph\">Example Max for Live devices are inbound, and you can use different audio autoencoders for different results, with a few popular choices already supported. There\u2019s been a bunch of action on the Stable Audio front, too, more generally, so I\u2019ll try to catch up. <\/p>\n<p class=\"wp-block-paragraph\">Download for Max (and Max for Live), on macOS and Windows. (And yeah, I\u2019m sure someone is thinking about Pure Data, so stay tuned\u2026)<\/p>\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/jasper-zheng.github.io\/nn_terrain\/installation\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/jasper-zheng.github.io\/nn_terrain\/installation<\/a><\/p>\n<p class=\"wp-block-paragraph\">Previously, and very relevant:<\/p>\n<p>    \t  Tags: <a href=\"https:\/\/cdm.link\/tag\/ai\/\" rel=\"tag nofollow noopener\" target=\"_blank\">AI<\/a>, <a href=\"https:\/\/cdm.link\/tag\/autoencoders\/\" rel=\"tag nofollow noopener\" target=\"_blank\">autoencoders<\/a>, <a href=\"https:\/\/cdm.link\/tag\/externals\/\" rel=\"tag nofollow noopener\" target=\"_blank\">externals<\/a>, <a href=\"https:\/\/cdm.link\/tag\/floss\/\" rel=\"tag nofollow noopener\" target=\"_blank\">FLOSS<\/a>, <a href=\"https:\/\/cdm.link\/tag\/free-as-in-freedom\/\" rel=\"tag nofollow noopener\" target=\"_blank\">free as in freedom<\/a>, <a href=\"https:\/\/cdm.link\/tag\/jasper-shuoyang-zheng\/\" rel=\"tag nofollow noopener\" target=\"_blank\">Jasper Shuoyang Zheng<\/a>, <a href=\"https:\/\/cdm.link\/tag\/latent-space\/\" rel=\"tag nofollow noopener\" target=\"_blank\">latent space<\/a>, <a href=\"https:\/\/cdm.link\/tag\/latent-terrain\/\" rel=\"tag nofollow noopener\" target=\"_blank\">latent terrain<\/a>, <a href=\"https:\/\/cdm.link\/tag\/mac\/\" rel=\"tag nofollow noopener\" target=\"_blank\">Mac<\/a>, <a href=\"https:\/\/cdm.link\/tag\/machine-learning-2\/\" rel=\"tag nofollow noopener\" target=\"_blank\">machine learning<\/a>, <a href=\"https:\/\/cdm.link\/tag\/macos\/\" rel=\"tag nofollow noopener\" target=\"_blank\">MacOS<\/a>, <a href=\"https:\/\/cdm.link\/tag\/max\/\" rel=\"tag nofollow noopener\" target=\"_blank\">max<\/a>, <a href=\"https:\/\/cdm.link\/tag\/max-for-live-2\/\" rel=\"tag nofollow noopener\" target=\"_blank\">max for live<\/a>, <a href=\"https:\/\/cdm.link\/tag\/neural-audio\/\" rel=\"tag nofollow noopener\" target=\"_blank\">neural audio<\/a>, <a href=\"https:\/\/cdm.link\/tag\/neural-audio-codecs\/\" rel=\"tag nofollow noopener\" target=\"_blank\">neural audio codecs<\/a>, <a href=\"https:\/\/cdm.link\/tag\/neural-nets\/\" rel=\"tag nofollow noopener\" target=\"_blank\">neural nets<\/a>, <a href=\"https:\/\/cdm.link\/tag\/nime\/\" rel=\"tag nofollow noopener\" target=\"_blank\">nime<\/a>, <a href=\"https:\/\/cdm.link\/tag\/open-source-2\/\" rel=\"tag nofollow noopener\" target=\"_blank\">open source<\/a>, <a href=\"https:\/\/cdm.link\/tag\/research\/\" rel=\"tag nofollow noopener\" target=\"_blank\">research<\/a>, <a href=\"https:\/\/cdm.link\/tag\/software\/\" rel=\"tag nofollow noopener\" target=\"_blank\">Software<\/a>, <a href=\"https:\/\/cdm.link\/tag\/sound-art-2\/\" rel=\"tag nofollow noopener\" target=\"_blank\">sound art<\/a>, <a href=\"https:\/\/cdm.link\/tag\/synthesis\/\" rel=\"tag nofollow noopener\" target=\"_blank\">synthesis<\/a>, <a href=\"https:\/\/cdm.link\/tag\/windows\/\" rel=\"tag nofollow noopener\" target=\"_blank\">Windows<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"\u201cI\u2019m not particularly interested in typing prompts to make stuff, I\u2019m interested in breaking them and dissecting them,\u201d&hellip;\n","protected":false},"author":2,"featured_media":77792,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7],"tags":[24,42476,42477,42478,42479,42480,6619,42481,16244,50,8345,42482,42483,42484,42485,42486,42487,335,157,52,136,42488,42489,3246],"class_list":["post-77791","post","type-post","status-publish","format-standard","has-post-thumbnail","category-openai","tag-ai","tag-autoencoders","tag-externals","tag-floss","tag-free-as-in-freedom","tag-jasper-shuoyang-zheng","tag-latent-space","tag-latent-terrain","tag-mac","tag-machine-learning","tag-macos","tag-max","tag-max-for-live","tag-neural-audio","tag-neural-audio-codecs","tag-neural-nets","tag-nime","tag-open-source","tag-openai","tag-research","tag-software","tag-sound-art","tag-synthesis","tag-windows"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/77791","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=77791"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/77791\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/77792"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=77791"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=77791"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=77791"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}