{"id":13005,"date":"2026-08-29T14:26:24","date_gmt":"2026-08-29T05:26:24","guid":{"rendered":"https:\/\/www.ibs.re.kr\/bimag\/?post_type=tribe_events&p=13005"},"modified":"2026-08-29T18:26:57","modified_gmt":"2026-08-29T09:26:57","slug":"physical-reservoir-computing-and-beyond-kohei-nakajima","status":"publish","type":"tribe_events","link":"https:\/\/www.ibs.re.kr\/bimag\/event\/physical-reservoir-computing-and-beyond-kohei-nakajima\/","title":{"rendered":"Physical reservoir computing and beyond – Kohei Nakajima"},"content":{"rendered":"

Modern computing has been fundamentally built upon the separation of hardware and software. This separation has enabled programs to be replicated and executed on interchangeable hardware, making computation effectively \u201cimmortal.\u201d In contrast, recent approaches to physical computing seek to exploit the intrinsic dynamics of physical systems as computational resources, thereby crossing the abstraction layers that traditionally separate hardware from computation. Such computation is inherently tied to its physical substrate and can therefore be regarded as \u201cmortal computation\u201d (Hinton, 2022).<\/span><\/p>\n

In this talk, I will introduce physical reservoir computing (PRC) as a representative framework for mortal computation, in which the intrinsic dynamics of physical systems perform information processing (Nakajima 2020). I will discuss how diverse physical substrates\u2014including soft robots, neuromorphic devices, and living systems\u2014can serve as computational resources, and how their embodiment can be exploited for sensing, computation, and control. I will then extend this perspective beyond reservoir computing to physicalizing deep learning, where not only inference but also learning processes are implemented in physical substrates. In particular, I will introduce a gradient-free approach to physical deep learning and discuss recent efforts to physicalize learning in neuromorphic devices and soft robots.<\/p>\n

Through these examples, I will argue that physicalizing computation is not merely a strategy for developing energy-efficient and task-specific computing systems. It also provides a new perspective on intelligence and learning in systems whose physical dynamics are intrinsically time-varying, adaptive, and ultimately mortal.<\/p>\n

 <\/p>\n

Zoom : 997 8258 4700 (pw : 1234)<\/p>\n","protected":false},"excerpt":{"rendered":"

Modern computing has been fundamentally built upon the separation of hardware and software. This separation has enabled programs to be replicated and executed on interchangeable hardware, making computation effectively \u201cimmortal.\u201d … <\/p>\n

Continue reading “Physical reservoir computing and beyond – Kohei Nakajima”<\/span><\/a><\/p>\n","protected":false},"author":13,"featured_media":13006,"template":"","meta":{"_editorskit_title_hidden":false,"_editorskit_reading_time":0,"_editorskit_is_block_options_detached":false,"_editorskit_block_options_position":"{}","_uag_custom_page_level_css":"","_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[221],"class_list":["post-13005","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-biomedical-mathematics-colloquium","cat_biomedical-mathematics-colloquium"],"yoast_head":"\nPhysical reservoir computing and beyond - Kohei Nakajima - Biomedical Mathematics Group<\/title>\n<meta name=\"description\" content=\""Modern computing has been fundamentally built upon the separation of hardware and software. This separation has enabled programs to be replicated and executed on interchangeable hardware, making computation effectively \u201cimmortal.\u201d In contrast, recent approaches to physical computing seek to exploit the intrinsic dynamics of physical systems as computational resources, thereby crossing the abstraction layers that traditionally separate hardware from computation. Such computation is inherently tied to its physical substrate and can therefore be regarded as \u201cmortal computation\u201d (Hinton, 2022).In this talk, I will introduce physical reservoir computing (PRC) as a representative framework for mortal computation, in which the intrinsic dynamics of physical systems perform information processing (Nakajima 2020). I will discuss how diverse physical substrates\u2014including soft robots, neuromorphic devices, and living systems\u2014can serve as computational resources, and how their embodiment can be exploited for sensing, computation, and control. I will then extend this perspective beyond reservoir computing to physicalizing deep learning, where not only inference but also learning processes are implemented in physical substrates. In particular, I will introduce a gradient-free approach to physical deep learning and discuss recent efforts to physicalize learning in neuromorphic devices and soft robots.Through these examples, I will argue that physicalizing computation is not merely a strategy for developing energy-efficient and task-specific computing systems. It also provides a new perspective on intelligence and learning in systems whose physical dynamics are intrinsically time-varying, adaptive, and ultimately mortal."\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.ibs.re.kr\/bimag\/event\/physical-reservoir-computing-and-beyond-kohei-nakajima\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Physical reservoir computing and beyond - Kohei Nakajima - Biomedical Mathematics Group\" \/>\n<meta property=\"og:description\" content=\""Modern computing has been fundamentally built upon the separation of hardware and software. This separation has enabled programs to be replicated and executed on interchangeable hardware, making computation effectively \u201cimmortal.\u201d In contrast, recent approaches to physical computing seek to exploit the intrinsic dynamics of physical systems as computational resources, thereby crossing the abstraction layers that traditionally separate hardware from computation. Such computation is inherently tied to its physical substrate and can therefore be regarded as \u201cmortal computation\u201d (Hinton, 2022).In this talk, I will introduce physical reservoir computing (PRC) as a representative framework for mortal computation, in which the intrinsic dynamics of physical systems perform information processing (Nakajima 2020). I will discuss how diverse physical substrates\u2014including soft robots, neuromorphic devices, and living systems\u2014can serve as computational resources, and how their embodiment can be exploited for sensing, computation, and control. I will then extend this perspective beyond reservoir computing to physicalizing deep learning, where not only inference but also learning processes are implemented in physical substrates. In particular, I will introduce a gradient-free approach to physical deep learning and discuss recent efforts to physicalize learning in neuromorphic devices and soft robots.Through these examples, I will argue that physicalizing computation is not merely a strategy for developing energy-efficient and task-specific computing systems. It also provides a new perspective on intelligence and learning in systems whose physical dynamics are intrinsically time-varying, adaptive, and ultimately mortal."\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.ibs.re.kr\/bimag\/event\/physical-reservoir-computing-and-beyond-kohei-nakajima\/\" \/>\n<meta property=\"og:site_name\" content=\"Biomedical Mathematics Group\" \/>\n<meta property=\"article:modified_time\" content=\"2026-08-29T09:26:57+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-e1787995608534.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"300\" \/>\n\t<meta property=\"og:image:height\" content=\"300\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/physical-reservoir-computing-and-beyond-kohei-nakajima\\\/\",\"url\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/physical-reservoir-computing-and-beyond-kohei-nakajima\\\/\",\"name\":\"Physical reservoir computing and beyond - Kohei Nakajima - Biomedical Mathematics Group\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/physical-reservoir-computing-and-beyond-kohei-nakajima\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/physical-reservoir-computing-and-beyond-kohei-nakajima\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/cms\\\/wp-content\\\/uploads\\\/2026\\\/08\\\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-e1787995608534.jpg\",\"datePublished\":\"2026-08-29T05:26:24+00:00\",\"dateModified\":\"2026-08-29T09:26:57+00:00\",\"description\":\"\\\"Modern computing has been fundamentally built upon the separation of hardware and software. This separation has enabled programs to be replicated and executed on interchangeable hardware, making computation effectively \u201cimmortal.\u201d In contrast, recent approaches to physical computing seek to exploit the intrinsic dynamics of physical systems as computational resources, thereby crossing the abstraction layers that traditionally separate hardware from computation. Such computation is inherently tied to its physical substrate and can therefore be regarded as \u201cmortal computation\u201d (Hinton, 2022).In this talk, I will introduce physical reservoir computing (PRC) as a representative framework for mortal computation, in which the intrinsic dynamics of physical systems perform information processing (Nakajima 2020). I will discuss how diverse physical substrates\u2014including soft robots, neuromorphic devices, and living systems\u2014can serve as computational resources, and how their embodiment can be exploited for sensing, computation, and control. I will then extend this perspective beyond reservoir computing to physicalizing deep learning, where not only inference but also learning processes are implemented in physical substrates. In particular, I will introduce a gradient-free approach to physical deep learning and discuss recent efforts to physicalize learning in neuromorphic devices and soft robots.Through these examples, I will argue that physicalizing computation is not merely a strategy for developing energy-efficient and task-specific computing systems. It also provides a new perspective on intelligence and learning in systems whose physical dynamics are intrinsically time-varying, adaptive, and ultimately mortal.\\\"\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/physical-reservoir-computing-and-beyond-kohei-nakajima\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/physical-reservoir-computing-and-beyond-kohei-nakajima\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/physical-reservoir-computing-and-beyond-kohei-nakajima\\\/#primaryimage\",\"url\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/cms\\\/wp-content\\\/uploads\\\/2026\\\/08\\\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-e1787995608534.jpg\",\"contentUrl\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/cms\\\/wp-content\\\/uploads\\\/2026\\\/08\\\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-e1787995608534.jpg\",\"width\":300,\"height\":300},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/physical-reservoir-computing-and-beyond-kohei-nakajima\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Events\",\"item\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/events\\\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Physical reservoir computing and beyond – Kohei Nakajima\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/#website\",\"url\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/\",\"name\":\"Biomedical Mathematics Group\",\"description\":\"\uae30\ucd08\uacfc\ud559\uc5f0\uad6c\uc6d0 \uc758\uc0dd\uba85\uc218\ud559\uadf8\ub8f9\",\"publisher\":{\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/#organization\",\"name\":\"IBS Biomedical Mathematics Group\",\"url\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/#\\\/schema\\\/logo\\\/image\\\/\",\"url\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/cms\\\/wp-content\\\/uploads\\\/2021\\\/02\\\/ibs-circle-1.png\",\"contentUrl\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/cms\\\/wp-content\\\/uploads\\\/2021\\\/02\\\/ibs-circle-1.png\",\"width\":250,\"height\":250,\"caption\":\"IBS Biomedical Mathematics Group\"},\"image\":{\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/#\\\/schema\\\/logo\\\/image\\\/\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Physical reservoir computing and beyond - Kohei Nakajima - Biomedical Mathematics Group","description":"\"Modern computing has been fundamentally built upon the separation of hardware and software. This separation has enabled programs to be replicated and executed on interchangeable hardware, making computation effectively \u201cimmortal.\u201d In contrast, recent approaches to physical computing seek to exploit the intrinsic dynamics of physical systems as computational resources, thereby crossing the abstraction layers that traditionally separate hardware from computation. Such computation is inherently tied to its physical substrate and can therefore be regarded as \u201cmortal computation\u201d (Hinton, 2022).In this talk, I will introduce physical reservoir computing (PRC) as a representative framework for mortal computation, in which the intrinsic dynamics of physical systems perform information processing (Nakajima 2020). I will discuss how diverse physical substrates\u2014including soft robots, neuromorphic devices, and living systems\u2014can serve as computational resources, and how their embodiment can be exploited for sensing, computation, and control. I will then extend this perspective beyond reservoir computing to physicalizing deep learning, where not only inference but also learning processes are implemented in physical substrates. In particular, I will introduce a gradient-free approach to physical deep learning and discuss recent efforts to physicalize learning in neuromorphic devices and soft robots.Through these examples, I will argue that physicalizing computation is not merely a strategy for developing energy-efficient and task-specific computing systems. It also provides a new perspective on intelligence and learning in systems whose physical dynamics are intrinsically time-varying, adaptive, and ultimately mortal.\"","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.ibs.re.kr\/bimag\/event\/physical-reservoir-computing-and-beyond-kohei-nakajima\/","og_locale":"en_US","og_type":"article","og_title":"Physical reservoir computing and beyond - Kohei Nakajima - Biomedical Mathematics Group","og_description":"\"Modern computing has been fundamentally built upon the separation of hardware and software. This separation has enabled programs to be replicated and executed on interchangeable hardware, making computation effectively \u201cimmortal.\u201d In contrast, recent approaches to physical computing seek to exploit the intrinsic dynamics of physical systems as computational resources, thereby crossing the abstraction layers that traditionally separate hardware from computation. Such computation is inherently tied to its physical substrate and can therefore be regarded as \u201cmortal computation\u201d (Hinton, 2022).In this talk, I will introduce physical reservoir computing (PRC) as a representative framework for mortal computation, in which the intrinsic dynamics of physical systems perform information processing (Nakajima 2020). I will discuss how diverse physical substrates\u2014including soft robots, neuromorphic devices, and living systems\u2014can serve as computational resources, and how their embodiment can be exploited for sensing, computation, and control. I will then extend this perspective beyond reservoir computing to physicalizing deep learning, where not only inference but also learning processes are implemented in physical substrates. In particular, I will introduce a gradient-free approach to physical deep learning and discuss recent efforts to physicalize learning in neuromorphic devices and soft robots.Through these examples, I will argue that physicalizing computation is not merely a strategy for developing energy-efficient and task-specific computing systems. It also provides a new perspective on intelligence and learning in systems whose physical dynamics are intrinsically time-varying, adaptive, and ultimately mortal.\"","og_url":"https:\/\/www.ibs.re.kr\/bimag\/event\/physical-reservoir-computing-and-beyond-kohei-nakajima\/","og_site_name":"Biomedical Mathematics Group","article_modified_time":"2026-08-29T09:26:57+00:00","og_image":[{"width":300,"height":300,"url":"https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-e1787995608534.jpg","type":"image\/jpeg"}],"twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"2 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/www.ibs.re.kr\/bimag\/event\/physical-reservoir-computing-and-beyond-kohei-nakajima\/","url":"https:\/\/www.ibs.re.kr\/bimag\/event\/physical-reservoir-computing-and-beyond-kohei-nakajima\/","name":"Physical reservoir computing and beyond - Kohei Nakajima - Biomedical Mathematics Group","isPartOf":{"@id":"https:\/\/www.ibs.re.kr\/bimag\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.ibs.re.kr\/bimag\/event\/physical-reservoir-computing-and-beyond-kohei-nakajima\/#primaryimage"},"image":{"@id":"https:\/\/www.ibs.re.kr\/bimag\/event\/physical-reservoir-computing-and-beyond-kohei-nakajima\/#primaryimage"},"thumbnailUrl":"https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-e1787995608534.jpg","datePublished":"2026-08-29T05:26:24+00:00","dateModified":"2026-08-29T09:26:57+00:00","description":"\"Modern computing has been fundamentally built upon the separation of hardware and software. This separation has enabled programs to be replicated and executed on interchangeable hardware, making computation effectively \u201cimmortal.\u201d In contrast, recent approaches to physical computing seek to exploit the intrinsic dynamics of physical systems as computational resources, thereby crossing the abstraction layers that traditionally separate hardware from computation. Such computation is inherently tied to its physical substrate and can therefore be regarded as \u201cmortal computation\u201d (Hinton, 2022).In this talk, I will introduce physical reservoir computing (PRC) as a representative framework for mortal computation, in which the intrinsic dynamics of physical systems perform information processing (Nakajima 2020). I will discuss how diverse physical substrates\u2014including soft robots, neuromorphic devices, and living systems\u2014can serve as computational resources, and how their embodiment can be exploited for sensing, computation, and control. I will then extend this perspective beyond reservoir computing to physicalizing deep learning, where not only inference but also learning processes are implemented in physical substrates. In particular, I will introduce a gradient-free approach to physical deep learning and discuss recent efforts to physicalize learning in neuromorphic devices and soft robots.Through these examples, I will argue that physicalizing computation is not merely a strategy for developing energy-efficient and task-specific computing systems. It also provides a new perspective on intelligence and learning in systems whose physical dynamics are intrinsically time-varying, adaptive, and ultimately mortal.\"","breadcrumb":{"@id":"https:\/\/www.ibs.re.kr\/bimag\/event\/physical-reservoir-computing-and-beyond-kohei-nakajima\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.ibs.re.kr\/bimag\/event\/physical-reservoir-computing-and-beyond-kohei-nakajima\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.ibs.re.kr\/bimag\/event\/physical-reservoir-computing-and-beyond-kohei-nakajima\/#primaryimage","url":"https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-e1787995608534.jpg","contentUrl":"https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-e1787995608534.jpg","width":300,"height":300},{"@type":"BreadcrumbList","@id":"https:\/\/www.ibs.re.kr\/bimag\/event\/physical-reservoir-computing-and-beyond-kohei-nakajima\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.ibs.re.kr\/bimag\/"},{"@type":"ListItem","position":2,"name":"Events","item":"https:\/\/www.ibs.re.kr\/bimag\/events\/"},{"@type":"ListItem","position":3,"name":"Physical reservoir computing and beyond – Kohei Nakajima"}]},{"@type":"WebSite","@id":"https:\/\/www.ibs.re.kr\/bimag\/#website","url":"https:\/\/www.ibs.re.kr\/bimag\/","name":"Biomedical Mathematics Group","description":"\uae30\ucd08\uacfc\ud559\uc5f0\uad6c\uc6d0 \uc758\uc0dd\uba85\uc218\ud559\uadf8\ub8f9","publisher":{"@id":"https:\/\/www.ibs.re.kr\/bimag\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.ibs.re.kr\/bimag\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/www.ibs.re.kr\/bimag\/#organization","name":"IBS Biomedical Mathematics Group","url":"https:\/\/www.ibs.re.kr\/bimag\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.ibs.re.kr\/bimag\/#\/schema\/logo\/image\/","url":"https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2021\/02\/ibs-circle-1.png","contentUrl":"https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2021\/02\/ibs-circle-1.png","width":250,"height":250,"caption":"IBS Biomedical Mathematics Group"},"image":{"@id":"https:\/\/www.ibs.re.kr\/bimag\/#\/schema\/logo\/image\/"}}]}},"uagb_featured_image_src":{"full":["https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-e1787995608534.jpg",300,300,false],"thumbnail":["https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-150x150.jpg",150,150,true],"medium":["https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-300x300.jpg",300,300,true],"medium_large":["https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-e1787995608534.jpg",300,300,false],"large":["https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-e1787995608534.jpg",300,300,false],"1536x1536":["https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-e1787995608534.jpg",300,300,false],"2048x2048":["https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-e1787995608534.jpg",300,300,false],"dimag-thumbnail":["https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-400x400.jpg",400,400,true],"twentyseventeen-featured-image":["https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-e1787995608534.jpg",300,300,false],"twentyseventeen-thumbnail-avatar":["https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2026\/08\/artworks-OxsgF0kW6Jd7athY-T73SEA-t500x500-100x100.jpg",100,100,true]},"uagb_author_info":{"display_name":"Hyeong Jun Jang","author_link":"https:\/\/www.ibs.re.kr\/bimag\/author\/hyeong-jun-jang\/"},"uagb_comment_info":0,"uagb_excerpt":"Modern computing has been fundamentally built upon the separation of hardware and software. This separation has enabled programs to be replicated and executed on interchangeable hardware, making computation effectively \u201cimmortal.\u201d … Continue reading \"Physical reservoir computing and beyond – Kohei Nakajima\"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.ibs.re.kr\/bimag\/wp-json\/wp\/v2\/tribe_events\/13005","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ibs.re.kr\/bimag\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.ibs.re.kr\/bimag\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.ibs.re.kr\/bimag\/wp-json\/wp\/v2\/users\/13"}],"version-history":[{"count":2,"href":"https:\/\/www.ibs.re.kr\/bimag\/wp-json\/wp\/v2\/tribe_events\/13005\/revisions"}],"predecessor-version":[{"id":13024,"href":"https:\/\/www.ibs.re.kr\/bimag\/wp-json\/wp\/v2\/tribe_events\/13005\/revisions\/13024"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.ibs.re.kr\/bimag\/wp-json\/wp\/v2\/media\/13006"}],"wp:attachment":[{"href":"https:\/\/www.ibs.re.kr\/bimag\/wp-json\/wp\/v2\/media?parent=13005"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ibs.re.kr\/bimag\/wp-json\/wp\/v2\/tags?post=13005"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.ibs.re.kr\/bimag\/wp-json\/wp\/v2\/tribe_events_cat?post=13005"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}