{"id":102754,"date":"2026-07-08T19:01:53","date_gmt":"2026-07-08T19:01:53","guid":{"rendered":"https:\/\/youzum.net\/openai-releases-gpt-live-and-gpt-live-1-mini-full-duplex-voice-models-that-delegate-deeper-reasoning-to-gpt-5-5\/"},"modified":"2026-07-08T19:01:53","modified_gmt":"2026-07-08T19:01:53","slug":"openai-releases-gpt-live-and-gpt-live-1-mini-full-duplex-voice-models-that-delegate-deeper-reasoning-to-gpt-5-5","status":"publish","type":"post","link":"https:\/\/youzum.net\/de\/openai-releases-gpt-live-and-gpt-live-1-mini-full-duplex-voice-models-that-delegate-deeper-reasoning-to-gpt-5-5\/","title":{"rendered":"OpenAI Releases GPT-Live and GPT-Live-1 mini: Full-Duplex Voice Models That Delegate Deeper Reasoning to GPT-5.5"},"content":{"rendered":"<p class=\"wp-block-paragraph\">Today, OpenAI released <strong><a href=\"https:\/\/openai.com\/index\/introducing-gpt-live\/\" target=\"_blank\" rel=\"noreferrer noopener\">GPT-Live<\/a><\/strong>. It is a new generation of voice models. GPT-Live now powers the ChatGPT Voice experience. The stated goal is natural, real-time conversation with AI. Two versions ship first: <strong>GPT-Live-1<\/strong> and <strong>GPT-Live-1 mini<\/strong>. Both roll out to ChatGPT users globally today. <\/p>\n<h2 class=\"wp-block-heading\"><strong>TL;DR<\/strong><\/h2>\n<ul class=\"wp-block-list\">\n<li>GPT-Live is a full-duplex voice model family that listens and speaks at once.<\/li>\n<li>It delegates search and reasoning to GPT-5.5 while keeping the conversation flowing.<\/li>\n<li>GPT-Live-1 and mini were strongly preferred over Advanced Voice Mode in human tests.<\/li>\n<li>It ships today to ChatGPT users globally; the API is planned soon.<\/li>\n<li>Video, screen sharing, and full multilingual parity are not available at launch.<\/li>\n<\/ul>\n<h2 class=\"wp-block-heading\"><strong>What is GPT-Live?<\/strong><\/h2>\n<p class=\"wp-block-paragraph\">GPT-Live is built on a <strong>full-duplex architecture<\/strong>. Full-duplex means the model can listen and speak at the same time. During a conversation, it can add short cues like \u2018mhmm\u2019 or \u2018yeah.\u2019 It can engage in quick back-and-forth, or stay quiet when you think. For questions needing web search, deeper reasoning, or complex work, GPT-Live delegates. It hands the task to a frontier model behind the scenes. The result returns to the conversation when it is ready. At launch, that background model is <strong>GPT-5.5<\/strong>. While the frontier model works, GPT-Live keeps the conversation going. <\/p>\n<h2 class=\"wp-block-heading\"><strong>Why Cascaded and Turn-Based Voice Fell Short<\/strong><\/h2>\n<p class=\"wp-block-paragraph\">Earlier voice systems moved toward natural conversation, but with tradeoffs. <strong>Cascaded voice systems<\/strong> chained three separate models per turn. A speech-to-text model transcribed your speech first. A large language model then produced a response. A text-to-speech model converted that text back into audio. This let people talk to frontier models for the first time. But information could be lost across models, and responses were slow and stilted.<\/p>\n<p class=\"wp-block-paragraph\"><strong>Turn-based voice models<\/strong>, like ChatGPT Advanced Voice Mode, processed audio inside one model. That reduced latency and made conversations smoother. They still operated through discrete turns, waiting for the user to stop speaking. Turn detection was based on silence. A brief pause or background noise could be mistaken for the end of a turn. This caused the model to interrupt at unnatural times.<\/p>\n<figure class=\"wp-block-table\">\n<table class=\"has-fixed-layout\">\n<thead>\n<tr>\n<th>Dimension<\/th>\n<th>Cascaded (original ChatGPT Voice)<\/th>\n<th>Turn-based (Advanced Voice Mode)<\/th>\n<th>Full-duplex (GPT-Live)<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Pipeline<\/td>\n<td>STT \u2192 LLM \u2192 TTS, three models<\/td>\n<td>Single model handling audio<\/td>\n<td>Single model, continuous processing<\/td>\n<\/tr>\n<tr>\n<td>Turn handling<\/td>\n<td>Discrete turns<\/td>\n<td>Discrete turns, silence-based<\/td>\n<td>Continuous, decisions many times\/sec<\/td>\n<\/tr>\n<tr>\n<td>Listen while speaking<\/td>\n<td>No<\/td>\n<td>No<\/td>\n<td>Yes<\/td>\n<\/tr>\n<tr>\n<td>Backchannels (\u201cmhmm\u201d)<\/td>\n<td>No<\/td>\n<td>No<\/td>\n<td>Yes<\/td>\n<\/tr>\n<tr>\n<td>Latency feel<\/td>\n<td>Slow, stilted, long pauses<\/td>\n<td>Faster, smoother, still rigid<\/td>\n<td>Fast, natural, expressive<\/td>\n<\/tr>\n<tr>\n<td>Interrupt handling<\/td>\n<td>Not supported<\/td>\n<td>Can misfire on pauses\/noise<\/td>\n<td>Can pause, interrupt, resume<\/td>\n<\/tr>\n<tr>\n<td>Deeper work<\/td>\n<td>In-line LLM<\/td>\n<td>In-line model<\/td>\n<td>Delegates to GPT-5.5 in background<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n<h2 class=\"wp-block-heading\"><strong>The Two Architectural Changes<\/strong><\/h2>\n<p class=\"wp-block-paragraph\"><strong>GPT-Live addresses these limits with two changes:<\/strong><\/p>\n<ul class=\"wp-block-list\">\n<li><strong>Continuous interaction using full-duplex processing<\/strong>: The model processes input while generating output at the same time. It can make interaction decisions many times per second. Those decisions include whether to speak, continue listening, pause, interrupt, or invoke a tool. This supports more natural back-and-forth and a better sense of time. It also enables live translation.<\/li>\n<li><strong>Delegation for deeper work<\/strong>: OpenAI decoupled continuous interaction from heavier reasoning. When a task needs search, reasoning, or more agentic capabilities, GPT-Live delegates it. Another model, such as GPT-5.5, handles that work in the background. Meanwhile, GPT-Live keeps the conversation flowing. This design also lets GPT-Live adopt newer frontier models as they ship.<\/li>\n<\/ul>\n<h2 class=\"wp-block-heading\"><strong>What OpenAI\u2019s Evaluations Show<\/strong><\/h2>\n<p class=\"wp-block-paragraph\">OpenAI built new human evaluations for pleasantness and conversational flow. Evaluators compared models in matched five-to-ten-minute conversations. In these head-to-head tests, GPT-Live-1 and GPT-Live-1 mini were strongly preferred over Advanced Voice Mode. The comparisons measured overall preference, turn-taking, interruptions, flow, and how natural each interaction felt.<\/p>\n<p class=\"wp-block-paragraph\"><strong>On automated benchmarks, GPT-Live-1 also showed gains over Advanced Voice Mode:<\/strong><\/p>\n<ul class=\"wp-block-list\">\n<li><strong>GPQA:<\/strong> GPT-Live-1 substantially outperforms it on expert-level science reasoning.<\/li>\n<li><strong>BrowseComp:<\/strong> GPT-Live-1 shows strong gains on agentic web search.<\/li>\n<li><strong>\u03c4\u00b3-Voice Telecom (internal variant):<\/strong> GPT-Live-1 outperforms it on multi-turn telecom support tasks.<\/li>\n<\/ul>\n<p class=\"wp-block-paragraph\">OpenAI team notes it used a customized user model for the \u03c4\u00b3-Voice Telecom eval. That user model was powered by its latest reasoning models. GPT-Live-1 (instant) and GPT-Live-1 mini use <strong>GPT-5.5 Instant<\/strong> in the background. GPT-Live-1 Medium and GPT-Live-1 High use <strong>GPT-5.5 Thinking<\/strong> with medium and high reasoning effort.<\/p>\n<h2 class=\"wp-block-heading\"><strong>GPT-Live: Full-Duplex Voice Explorer<\/strong><\/h2>\n<p><!-- GPT-Live Full-Duplex Explorer :: Marktechpost embed :: paste into a Custom HTML block --><\/p>\n<p class=\"wp-block-paragraph\">\n<h2 class=\"wp-block-heading\"><strong>Use Cases With Examples<\/strong><\/h2>\n<ul class=\"wp-block-list\">\n<li><strong>Hands-free help:<\/strong> ask for cooking steps or directions without touching a screen.<\/li>\n<li><strong>Language practice:<\/strong> hold a back-and-forth chat with gentle corrections.<\/li>\n<li><strong>Live translation:<\/strong> full-duplex timing supports translating speech during a conversation.<\/li>\n<li><strong>Research on the go:<\/strong> ask a hard question on your commute; GPT-5.5 searches in the background.<\/li>\n<li><strong>Support workflows:<\/strong> multi-turn telecom-style tasks map to the \u03c4\u00b3-Voice Telecom evaluation.<\/li>\n<li><strong>Visual lookups:<\/strong> see weather, stocks, or sports as cards while you talk.<\/li>\n<\/ul>\n<h2 class=\"wp-block-heading\"><strong>A Conceptual Look at the Full-Duplex Loop<\/strong><\/h2>\n<\/p><p class=\"wp-block-paragraph\">The API is not available yet. So this is a runnable, illustrative simulation of the decision loop. It is a teaching model of the architecture, not the actual GPT-Live API. You can run it as plain Python to see the flow.<\/p>\n<div class=\"dm-code-snippet dark dm-normal-version default no-background-mobile\">\n<div class=\"control-language\">\n<div class=\"dm-buttons\">\n<div class=\"dm-buttons-left\">\n<div class=\"dm-button-snippet red-button\"><\/div>\n<div class=\"dm-button-snippet orange-button\"><\/div>\n<div class=\"dm-button-snippet green-button\"><\/div>\n<\/div>\n<div class=\"dm-buttons-right\"><a><span class=\"dm-copy-text\">Copy Code<\/span><span class=\"dm-copy-confirmed\">Copied<\/span><span class=\"dm-error-message\">Use a different Browser<\/span><\/a><\/div>\n<\/div>\n<pre class=\"no-line-numbers\"><code class=\"no-wrap language-php\">\"\"\"Illustrative simulation of the GPT-Live full-duplex decision loop.\nTeaching model of the described architecture, NOT the real API.\"\"\"\nimport random\nrandom.seed(7)  # reproducible output\n\nclass BackgroundModel:                      # stands in for GPT-5.5\n    def run(self, query):\n        return f\"answer to '{query}'\"\n\nclass GPTLive:\n    def __init__(self, background):\n        self.background = background\n        self.pending = None                 # a delegated task, if one is running\n\n    def decide(self, user_speaking, needs_deep_work):\n        # A real model makes this choice many times per second.\n        if self.pending is not None:\n            return \"await_delegate\"\n        if needs_deep_work:\n            return \"delegate\"\n        if user_speaking:\n            return random.choice([\"listen\", \"backchannel\"])\n        return \"speak\"\n\n    def step(self, frame):\n        action = self.decide(frame[\"user_speaking\"], frame[\"needs_deep_work\"])\n        if action == \"delegate\":\n            self.pending = frame[\"query\"]                 # hand off, keep talking\n            return 'speak      -&gt; \"one sec, still with you\"'\n        if action == \"await_delegate\":\n            result = self.background.run(self.pending)     # background result\n            self.pending = None\n            return f'speak      -&gt; \"{result}\"'\n        if action == \"backchannel\":\n            return 'backchannel-&gt; \"mhmm\" (while user talks)'\n        if action == \"listen\":\n            return \"listen     -&gt; (quiet, attending)\"\n        return \"speak      -&gt; (normal reply)\"\n\n# A short scripted stream of audio frames the loop consumes in order.\nstream = [\n    {\"user_speaking\": True,  \"needs_deep_work\": False, \"query\": None},\n    {\"user_speaking\": True,  \"needs_deep_work\": False, \"query\": None},\n    {\"user_speaking\": False, \"needs_deep_work\": True,  \"query\": \"weather at 6pm\"},\n    {\"user_speaking\": False, \"needs_deep_work\": False, \"query\": None},  # result returns\n    {\"user_speaking\": False, \"needs_deep_work\": False, \"query\": None},\n]\n\nlive = GPTLive(BackgroundModel())\nfor i, frame in enumerate(stream):\n    print(f\"frame {i}: {live.step(frame)}\")<\/code><\/pre>\n<\/div>\n<\/div>\n<p class=\"wp-block-paragraph\">Running it prints the loop making one interaction decision per frame:<\/p>\n<div class=\"dm-code-snippet dark dm-normal-version default no-background-mobile\">\n<div class=\"control-language\">\n<div class=\"dm-buttons\">\n<div class=\"dm-buttons-left\">\n<div class=\"dm-button-snippet red-button\"><\/div>\n<div class=\"dm-button-snippet orange-button\"><\/div>\n<div class=\"dm-button-snippet green-button\"><\/div>\n<\/div>\n<div class=\"dm-buttons-right\"><a><span class=\"dm-copy-text\">Copy Code<\/span><span class=\"dm-copy-confirmed\">Copied<\/span><span class=\"dm-error-message\">Use a different Browser<\/span><\/a><\/div>\n<\/div>\n<pre class=\"no-line-numbers\"><code class=\"no-wrap language-php\">frame 0: backchannel-&gt; \"mhmm\" (while user talks)\nframe 1: listen     -&gt; (quiet, attending)\nframe 2: speak      -&gt; \"one sec, still with you\"\nframe 3: speak      -&gt; \"answer to 'weather at 6pm'\"\nframe 4: speak      -&gt; (normal reply)<\/code><\/pre>\n<\/div>\n<\/div>\n<h2 class=\"wp-block-heading\"><strong>What Changes in ChatGPT Voice<\/strong><\/h2>\n<p class=\"wp-block-paragraph\">More than 150 million people use ChatGPT Voice and Dictation each week. Tapping the Voice button now uses the GPT-Live experience. Conversations support interruption, pausing, and requests to slow down. The model acknowledges you with cues like \u2018mhmm\u2019 or \u2018got it.\u2019 OpenAI remastered the nine distinct voices for GPT-Live. You can choose a reasoning level: Instant, Medium, or High. Better listening means it waits instead of jumping into your pauses. It also focuses better in noisy settings. Voice can now show visual cards for weather, stocks, and sports. It still supports search, memory, images, and file uploads.<\/p>\n<p class=\"wp-block-paragraph\">\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n<\/p><p class=\"wp-block-paragraph\">Check out the\u00a0<strong><a href=\"https:\/\/openai.com\/index\/introducing-gpt-live\/\" target=\"_blank\" rel=\"noreferrer noopener\">Technical details here<\/a><\/strong>.<strong>\u00a0<\/strong>Also,\u00a0feel free to follow us on\u00a0<strong><a href=\"https:\/\/x.com\/intent\/follow?screen_name=marktechpost\" target=\"_blank\" rel=\"noreferrer noopener\"><mark>Twitter<\/mark><\/a><\/strong>\u00a0and don\u2019t forget to join our\u00a0<strong><a href=\"https:\/\/www.reddit.com\/r\/machinelearningnews\/\" target=\"_blank\" rel=\"noreferrer noopener\">150k+ML SubReddit<\/a><\/strong>\u00a0and Subscribe to\u00a0<strong><a href=\"https:\/\/www.aidevsignals.com\/\" target=\"_blank\" rel=\"noreferrer noopener\">our Newsletter<\/a><\/strong>. Wait! are you on telegram?\u00a0<strong><a href=\"https:\/\/t.me\/machinelearningresearchnews\" target=\"_blank\" rel=\"noreferrer noopener\">now you can join us on telegram as well.<\/a><\/strong><\/p>\n<p class=\"wp-block-paragraph\">Need to partner with us for promoting your GitHub Repo OR Hugging Face Page OR Product Release OR Webinar etc.?\u00a0<strong><a href=\"https:\/\/forms.gle\/wbash1wF6efRj8G58\" target=\"_blank\" rel=\"noreferrer noopener\"><mark>Connect with us<\/mark><\/a><\/strong><\/p>\n<p>The post <a href=\"https:\/\/www.marktechpost.com\/2026\/07\/08\/openai-releases-gpt-live-and-gpt-live-1-mini-full-duplex-voice-models-that-delegate-deeper-reasoning-to-gpt-5-5\/\">OpenAI Releases GPT-Live and GPT-Live-1 mini: Full-Duplex Voice Models That Delegate Deeper Reasoning to GPT-5.5<\/a> appeared first on <a href=\"https:\/\/www.marktechpost.com\/\">MarkTechPost<\/a>.<\/p>","protected":false},"excerpt":{"rendered":"<p>Today, OpenAI released GPT-Live. It is a new generation of voice models. GPT-Live now powers the ChatGPT Voice experience. The stated goal is natural, real-time conversation with AI. Two versions ship first: GPT-Live-1 and GPT-Live-1 mini. Both roll out to ChatGPT users globally today. TL;DR GPT-Live is a full-duplex voice model family that listens and speaks at once. It delegates search and reasoning to GPT-5.5 while keeping the conversation flowing. GPT-Live-1 and mini were strongly preferred over Advanced Voice Mode in human tests. It ships today to ChatGPT users globally; the API is planned soon. Video, screen sharing, and full multilingual parity are not available at launch. What is GPT-Live? GPT-Live is built on a full-duplex architecture. Full-duplex means the model can listen and speak at the same time. During a conversation, it can add short cues like \u2018mhmm\u2019 or \u2018yeah.\u2019 It can engage in quick back-and-forth, or stay quiet when you think. For questions needing web search, deeper reasoning, or complex work, GPT-Live delegates. It hands the task to a frontier model behind the scenes. The result returns to the conversation when it is ready. At launch, that background model is GPT-5.5. While the frontier model works, GPT-Live keeps the conversation going. Why Cascaded and Turn-Based Voice Fell Short Earlier voice systems moved toward natural conversation, but with tradeoffs. Cascaded voice systems chained three separate models per turn. A speech-to-text model transcribed your speech first. A large language model then produced a response. A text-to-speech model converted that text back into audio. This let people talk to frontier models for the first time. But information could be lost across models, and responses were slow and stilted. Turn-based voice models, like ChatGPT Advanced Voice Mode, processed audio inside one model. That reduced latency and made conversations smoother. They still operated through discrete turns, waiting for the user to stop speaking. Turn detection was based on silence. A brief pause or background noise could be mistaken for the end of a turn. This caused the model to interrupt at unnatural times. Dimension Cascaded (original ChatGPT Voice) Turn-based (Advanced Voice Mode) Full-duplex (GPT-Live) Pipeline STT \u2192 LLM \u2192 TTS, three models Single model handling audio Single model, continuous processing Turn handling Discrete turns Discrete turns, silence-based Continuous, decisions many times\/sec Listen while speaking No No Yes Backchannels (\u201cmhmm\u201d) No No Yes Latency feel Slow, stilted, long pauses Faster, smoother, still rigid Fast, natural, expressive Interrupt handling Not supported Can misfire on pauses\/noise Can pause, interrupt, resume Deeper work In-line LLM In-line model Delegates to GPT-5.5 in background The Two Architectural Changes GPT-Live addresses these limits with two changes: Continuous interaction using full-duplex processing: The model processes input while generating output at the same time. It can make interaction decisions many times per second. Those decisions include whether to speak, continue listening, pause, interrupt, or invoke a tool. This supports more natural back-and-forth and a better sense of time. It also enables live translation. Delegation for deeper work: OpenAI decoupled continuous interaction from heavier reasoning. When a task needs search, reasoning, or more agentic capabilities, GPT-Live delegates it. Another model, such as GPT-5.5, handles that work in the background. Meanwhile, GPT-Live keeps the conversation flowing. This design also lets GPT-Live adopt newer frontier models as they ship. What OpenAI\u2019s Evaluations Show OpenAI built new human evaluations for pleasantness and conversational flow. Evaluators compared models in matched five-to-ten-minute conversations. In these head-to-head tests, GPT-Live-1 and GPT-Live-1 mini were strongly preferred over Advanced Voice Mode. The comparisons measured overall preference, turn-taking, interruptions, flow, and how natural each interaction felt. On automated benchmarks, GPT-Live-1 also showed gains over Advanced Voice Mode: GPQA: GPT-Live-1 substantially outperforms it on expert-level science reasoning. BrowseComp: GPT-Live-1 shows strong gains on agentic web search. \u03c4\u00b3-Voice Telecom (internal variant): GPT-Live-1 outperforms it on multi-turn telecom support tasks. OpenAI team notes it used a customized user model for the \u03c4\u00b3-Voice Telecom eval. That user model was powered by its latest reasoning models. GPT-Live-1 (instant) and GPT-Live-1 mini use GPT-5.5 Instant in the background. GPT-Live-1 Medium and GPT-Live-1 High use GPT-5.5 Thinking with medium and high reasoning effort. GPT-Live: Full-Duplex Voice Explorer Use Cases With Examples Hands-free help: ask for cooking steps or directions without touching a screen. Language practice: hold a back-and-forth chat with gentle corrections. Live translation: full-duplex timing supports translating speech during a conversation. Research on the go: ask a hard question on your commute; GPT-5.5 searches in the background. Support workflows: multi-turn telecom-style tasks map to the \u03c4\u00b3-Voice Telecom evaluation. Visual lookups: see weather, stocks, or sports as cards while you talk. A Conceptual Look at the Full-Duplex Loop The API is not available yet. So this is a runnable, illustrative simulation of the decision loop. It is a teaching model of the architecture, not the actual GPT-Live API. You can run it as plain Python to see the flow. Copy CodeCopiedUse a different Browser &#8220;&#8221;&#8221;Illustrative simulation of the GPT-Live full-duplex decision loop. Teaching model of the described architecture, NOT the real API.&#8221;&#8221;&#8221; import random random.seed(7) # reproducible output class BackgroundModel: # stands in for GPT-5.5 def run(self, query): return f&#8221;answer to &#8216;{query}'&#8221; class GPTLive: def __init__(self, background): self.background = background self.pending = None # a delegated task, if one is running def decide(self, user_speaking, needs_deep_work): # A real model makes this choice many times per second. if self.pending is not None: return &#8220;await_delegate&#8221; if needs_deep_work: return &#8220;delegate&#8221; if user_speaking: return random.choice([&#8220;listen&#8221;, &#8220;backchannel&#8221;]) return &#8220;speak&#8221; def step(self, frame): action = self.decide(frame[&#8220;user_speaking&#8221;], frame[&#8220;needs_deep_work&#8221;]) if action == &#8220;delegate&#8221;: self.pending = frame[&#8220;query&#8221;] # hand off, keep talking return &#8216;speak -&gt; &#8220;one sec, still with you&#8221;&#8216; if action == &#8220;await_delegate&#8221;: result = self.background.run(self.pending) # background result self.pending = None return f&#8217;speak -&gt; &#8220;{result}&#8221;&#8216; if action == &#8220;backchannel&#8221;: return &#8216;backchannel-&gt; &#8220;mhmm&#8221; (while user talks)&#8217; if action == &#8220;listen&#8221;: return &#8220;listen -&gt; (quiet, attending)&#8221; return &#8220;speak -&gt; (normal reply)&#8221; # A short scripted stream of audio frames the loop consumes in order. stream = [ {&#8220;user_speaking&#8221;: True, &#8220;needs_deep_work&#8221;: False, &#8220;query&#8221;: None}, {&#8220;user_speaking&#8221;: True, &#8220;needs_deep_work&#8221;: False,<\/p>","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"pmpro_default_level":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"_pvb_checkbox_block_on_post":false,"footnotes":""},"categories":[52,5,7,1],"tags":[],"class_list":["post-102754","post","type-post","status-publish","format-standard","hentry","category-ai-club","category-committee","category-news","category-uncategorized","pmpro-has-access"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.3 - 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