{"id":3257,"date":"2026-05-29T14:28:21","date_gmt":"2026-05-29T12:28:21","guid":{"rendered":"https:\/\/science-x.net\/?p=3257"},"modified":"2026-05-29T14:28:22","modified_gmt":"2026-05-29T12:28:22","slug":"moravecs-paradox-why-chess-is-easy-for-ai-but-baby-talk-is-hard","status":"publish","type":"post","link":"https:\/\/science-x.net\/?p=3257","title":{"rendered":"Moravec\u2019s Paradox: Why Chess Is Easy for AI but Baby Talk Is Hard"},"content":{"rendered":"\n<p>At first glance, artificial intelligence seems astonishingly smart.<\/p>\n\n\n\n<p>Modern AI systems can:<\/p>\n\n\n\n<ul>\n<li>Defeat chess champions<\/li>\n\n\n\n<li>Solve complex equations<\/li>\n\n\n\n<li>Analyze massive datasets<\/li>\n\n\n\n<li>Write computer code<\/li>\n\n\n\n<li>Simulate human conversation<\/li>\n<\/ul>\n\n\n\n<p>Yet surprisingly, many tasks that feel effortless to humans remain extremely difficult for machines.<\/p>\n\n\n\n<p>For example:<\/p>\n\n\n\n<ul>\n<li>Walking through a crowded room<\/li>\n\n\n\n<li>Recognizing emotions<\/li>\n\n\n\n<li>Understanding sarcasm<\/li>\n\n\n\n<li>Grabbing objects naturally<\/li>\n\n\n\n<li>Learning language like a small child<\/li>\n<\/ul>\n\n\n\n<p>This strange contradiction is known as:<\/p>\n\n\n\n<ul>\n<li>Moravec\u2019s Paradox<\/li>\n<\/ul>\n\n\n\n<p>The paradox reveals that:<\/p>\n\n\n\n<ul>\n<li>High-level reasoning tasks may actually be easier for computers than basic human sensory and motor skills.<\/li>\n<\/ul>\n\n\n\n<p>In other words:<\/p>\n\n\n\n<ul>\n<li>A machine can beat grandmasters in chess<br>while still struggling with abilities possessed by:<\/li>\n\n\n\n<li>Toddlers<\/li>\n\n\n\n<li>Animals<\/li>\n\n\n\n<li>Ordinary humans<\/li>\n<\/ul>\n\n\n\n<p>Understanding Moravec\u2019s Paradox helps explain:<\/p>\n\n\n\n<ul>\n<li>The strengths of AI<\/li>\n\n\n\n<li>The weaknesses of AI<\/li>\n\n\n\n<li>The incredible complexity of the human brain<\/li>\n<\/ul>\n\n\n\n<p>and why true human-like intelligence remains one of science\u2019s greatest challenges.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">What Is Moravec\u2019s Paradox?<\/h3>\n\n\n\n<p>Moravec\u2019s Paradox is the observation that:<\/p>\n\n\n\n<ul>\n<li>Tasks humans find difficult are often easy for computers<br>while:<\/li>\n\n\n\n<li>Tasks humans find effortless are often extremely difficult for AI.<\/li>\n<\/ul>\n\n\n\n<p>The paradox was described by researchers including:<\/p>\n\n\n\n<ul>\n<li>Hans Moravec<\/li>\n\n\n\n<li>Marvin Minsky<\/li>\n\n\n\n<li>Rodney Brooks<\/li>\n<\/ul>\n\n\n\n<p>during the 1980s.<\/p>\n\n\n\n<p>The central idea is simple:<\/p>\n\n\n\n<ul>\n<li>Human evolution spent millions of years optimizing sensory and motor abilities.<\/li>\n<\/ul>\n\n\n\n<p>As a result:<\/p>\n\n\n\n<ul>\n<li>Basic human perception is incredibly sophisticated.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Why Chess Is Relatively Easy for AI<\/h3>\n\n\n\n<p>Chess appears extremely intelligent because it involves:<\/p>\n\n\n\n<ul>\n<li>Strategy<\/li>\n\n\n\n<li>Planning<\/li>\n\n\n\n<li>Calculation<\/li>\n\n\n\n<li>Logic<\/li>\n<\/ul>\n\n\n\n<p>However, chess also follows:<\/p>\n\n\n\n<ul>\n<li>Clear rules<\/li>\n\n\n\n<li>Predictable structure<\/li>\n\n\n\n<li>Defined possibilities<\/li>\n<\/ul>\n\n\n\n<p>Computers are excellent at:<\/p>\n\n\n\n<ul>\n<li>Searching possibilities<\/li>\n\n\n\n<li>Calculating moves<\/li>\n\n\n\n<li>Evaluating positions rapidly<\/li>\n<\/ul>\n\n\n\n<p>AI systems can analyze millions of chess positions per second.<\/p>\n\n\n\n<p>This makes games like:<\/p>\n\n\n\n<ul>\n<li>Chess<\/li>\n\n\n\n<li>Checkers<\/li>\n\n\n\n<li>Go<\/li>\n<\/ul>\n\n\n\n<p>well suited for:<\/p>\n\n\n\n<ul>\n<li>Computational brute force<\/li>\n\n\n\n<li>Pattern recognition<\/li>\n\n\n\n<li>Statistical optimization<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Why Human Perception Is Much Harder<\/h3>\n\n\n\n<p>Now consider something seemingly simple:<\/p>\n\n\n\n<ul>\n<li>Recognizing a face in poor lighting<\/li>\n\n\n\n<li>Understanding a child\u2019s emotional tone<\/li>\n\n\n\n<li>Catching a falling object<\/li>\n\n\n\n<li>Walking on uneven ground<\/li>\n<\/ul>\n\n\n\n<p>Humans perform these tasks:<\/p>\n\n\n\n<ul>\n<li>Instantly<\/li>\n\n\n\n<li>Automatically<\/li>\n\n\n\n<li>Unconsciously<\/li>\n<\/ul>\n\n\n\n<p>But for AI, these abilities require enormous computational complexity.<\/p>\n\n\n\n<p>The brain continuously processes:<\/p>\n\n\n\n<ul>\n<li>Vision<\/li>\n\n\n\n<li>Sound<\/li>\n\n\n\n<li>Balance<\/li>\n\n\n\n<li>Spatial awareness<\/li>\n\n\n\n<li>Movement<\/li>\n\n\n\n<li>Context<\/li>\n\n\n\n<li>Emotion<\/li>\n<\/ul>\n\n\n\n<p>all simultaneously.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Evolution Built the Human Brain for Survival<\/h3>\n\n\n\n<p>Hans Moravec explained the paradox partly through:<\/p>\n\n\n\n<ul>\n<li>Evolutionary history<\/li>\n<\/ul>\n\n\n\n<p>Humans and animals spent hundreds of millions of years evolving:<\/p>\n\n\n\n<ul>\n<li>Perception<\/li>\n\n\n\n<li>Movement<\/li>\n\n\n\n<li>Reflexes<\/li>\n\n\n\n<li>Sensory processing<\/li>\n<\/ul>\n\n\n\n<p>These abilities became deeply optimized biologically.<\/p>\n\n\n\n<p>In contrast:<\/p>\n\n\n\n<ul>\n<li>Abstract mathematics<\/li>\n\n\n\n<li>Logic<\/li>\n\n\n\n<li>Chess<\/li>\n<\/ul>\n\n\n\n<p>are relatively recent human inventions.<\/p>\n\n\n\n<p>The brain performs ancient survival tasks extraordinarily efficiently because evolution refined them over vast timescales.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Baby Talk Is Surprisingly Complex<\/h3>\n\n\n\n<p>One famous example involves:<\/p>\n\n\n\n<ul>\n<li>Human language acquisition<\/li>\n<\/ul>\n\n\n\n<p>A small child learns language through:<\/p>\n\n\n\n<ul>\n<li>Observation<\/li>\n\n\n\n<li>Social interaction<\/li>\n\n\n\n<li>Context<\/li>\n\n\n\n<li>Emotional cues<\/li>\n\n\n\n<li>Environmental feedback<\/li>\n<\/ul>\n\n\n\n<p>Children understand:<\/p>\n\n\n\n<ul>\n<li>Tone<\/li>\n\n\n\n<li>Intention<\/li>\n\n\n\n<li>Facial expression<\/li>\n\n\n\n<li>Ambiguity<\/li>\n<\/ul>\n\n\n\n<p>long before mastering formal grammar.<\/p>\n\n\n\n<p>For AI systems:<\/p>\n\n\n\n<ul>\n<li>Natural language understanding remains enormously difficult despite major advances.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Human Vision Is Incredibly Advanced<\/h3>\n\n\n\n<p>Humans often underestimate how complicated:<\/p>\n\n\n\n<ul>\n<li>Vision<\/li>\n<\/ul>\n\n\n\n<p>really is.<\/p>\n\n\n\n<p>The brain instantly recognizes:<\/p>\n\n\n\n<ul>\n<li>Objects<\/li>\n\n\n\n<li>Faces<\/li>\n\n\n\n<li>Motion<\/li>\n\n\n\n<li>Distance<\/li>\n\n\n\n<li>Shadows<\/li>\n\n\n\n<li>Context<\/li>\n<\/ul>\n\n\n\n<p>under changing conditions.<\/p>\n\n\n\n<p>Computer vision systems improved dramatically in recent years, yet they still struggle with situations humans solve effortlessly.<\/p>\n\n\n\n<p>For example:<\/p>\n\n\n\n<ul>\n<li>A toddler can identify a cat from unusual angles more reliably than many older AI systems.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Movement and Robotics Are Hard Problems<\/h3>\n\n\n\n<p>Walking appears simple for humans because the brain controls:<\/p>\n\n\n\n<ul>\n<li>Muscles<\/li>\n\n\n\n<li>Balance<\/li>\n\n\n\n<li>Reflexes<\/li>\n\n\n\n<li>Spatial coordination<\/li>\n<\/ul>\n\n\n\n<p>automatically.<\/p>\n\n\n\n<p>But robots struggle greatly with:<\/p>\n\n\n\n<ul>\n<li>Uneven surfaces<\/li>\n\n\n\n<li>Stairs<\/li>\n\n\n\n<li>Dexterous hand movement<\/li>\n\n\n\n<li>Object manipulation<\/li>\n<\/ul>\n\n\n\n<p>Robotic movement requires extremely complicated:<\/p>\n\n\n\n<ul>\n<li>Sensor integration<\/li>\n\n\n\n<li>Real-time adjustment<\/li>\n\n\n\n<li>Environmental interpretation<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Why AI Seems Smart but Limited<\/h3>\n\n\n\n<p>Modern AI excels in:<\/p>\n\n\n\n<ul>\n<li>Narrow specialized tasks<\/li>\n<\/ul>\n\n\n\n<p>These systems can become:<\/p>\n\n\n\n<ul>\n<li>Superhuman in specific domains<\/li>\n<\/ul>\n\n\n\n<p>Yet they often lack:<\/p>\n\n\n\n<ul>\n<li>Common sense<\/li>\n\n\n\n<li>Flexible reasoning<\/li>\n\n\n\n<li>Deep contextual understanding<\/li>\n<\/ul>\n\n\n\n<p>An AI might solve advanced equations while failing at:<\/p>\n\n\n\n<ul>\n<li>Understanding ordinary social situations.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">The Human Brain Is Massively Parallel<\/h3>\n\n\n\n<p>One reason humans handle perception so well is that the brain processes information through:<\/p>\n\n\n\n<ul>\n<li>Massive parallel neural systems<\/li>\n<\/ul>\n\n\n\n<p>Billions of neurons simultaneously analyze:<\/p>\n\n\n\n<ul>\n<li>Vision<\/li>\n\n\n\n<li>Sound<\/li>\n\n\n\n<li>Touch<\/li>\n\n\n\n<li>Body position<\/li>\n\n\n\n<li>Memory<\/li>\n\n\n\n<li>Emotions<\/li>\n<\/ul>\n\n\n\n<p>Modern computers process information differently from:<\/p>\n\n\n\n<ul>\n<li>Biological brains<\/li>\n<\/ul>\n\n\n\n<p>which helps explain why human sensory intelligence remains difficult to reproduce.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">AI Learned Games Before Common Sense<\/h3>\n\n\n\n<p>One fascinating consequence of Moravec\u2019s Paradox is that AI mastered:<\/p>\n\n\n\n<ul>\n<li>Chess<\/li>\n\n\n\n<li>Complex calculations<\/li>\n\n\n\n<li>Data analysis<\/li>\n<\/ul>\n\n\n\n<p>before achieving reliable:<\/p>\n\n\n\n<ul>\n<li>Human-like perception<\/li>\n\n\n\n<li>Common sense reasoning<\/li>\n\n\n\n<li>Everyday understanding<\/li>\n<\/ul>\n\n\n\n<p>This surprised many early AI researchers.<\/p>\n\n\n\n<p>People assumed:<\/p>\n\n\n\n<ul>\n<li>\u201cHard intellectual tasks\u201d<\/li>\n<\/ul>\n\n\n\n<p>would be the greatest challenge.<\/p>\n\n\n\n<p>In reality:<\/p>\n\n\n\n<ul>\n<li>Basic perception turned out far more difficult.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Deep Learning Improved AI Dramatically<\/h3>\n\n\n\n<p>Modern:<\/p>\n\n\n\n<ul>\n<li>Deep learning systems<\/li>\n<\/ul>\n\n\n\n<p>greatly improved:<\/p>\n\n\n\n<ul>\n<li>Image recognition<\/li>\n\n\n\n<li>Speech recognition<\/li>\n\n\n\n<li>Language models<\/li>\n<\/ul>\n\n\n\n<p>These advances partially reduced some aspects of:<\/p>\n\n\n\n<ul>\n<li>Moravec\u2019s Paradox<\/li>\n<\/ul>\n\n\n\n<p>However, AI still struggles with:<\/p>\n\n\n\n<ul>\n<li>General understanding<\/li>\n\n\n\n<li>Physical reasoning<\/li>\n\n\n\n<li>Flexible adaptation<\/li>\n<\/ul>\n\n\n\n<p>compared to humans.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Expert Opinion on the Paradox<\/h3>\n\n\n\n<p>Robotics researcher Rodney Brooks explained:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>\u201cThe world is its own best model.\u201d<\/p>\n<\/blockquote>\n\n\n\n<p>This means humans interact naturally with reality because biological brains evolved directly inside:<\/p>\n\n\n\n<ul>\n<li>Complex physical environments<\/li>\n<\/ul>\n\n\n\n<p>AI systems still lack much of this:<\/p>\n\n\n\n<ul>\n<li>Embodied experience.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">The Paradox Reveals Human Complexity<\/h3>\n\n\n\n<p>Moravec\u2019s Paradox demonstrates that:<\/p>\n\n\n\n<ul>\n<li>Human intelligence is not mainly about formal logic.<\/li>\n<\/ul>\n\n\n\n<p>Instead, much of intelligence involves:<\/p>\n\n\n\n<ul>\n<li>Perception<\/li>\n\n\n\n<li>Context<\/li>\n\n\n\n<li>Motor coordination<\/li>\n\n\n\n<li>Social understanding<\/li>\n\n\n\n<li>Emotional interpretation<\/li>\n<\/ul>\n\n\n\n<p>These abilities are deeply rooted in:<\/p>\n\n\n\n<ul>\n<li>Evolutionary biology.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Why Common Sense Is Difficult for AI<\/h3>\n\n\n\n<p>Humans possess enormous amounts of:<\/p>\n\n\n\n<ul>\n<li>Implicit knowledge<\/li>\n<\/ul>\n\n\n\n<p>For example, humans automatically understand:<\/p>\n\n\n\n<ul>\n<li>Gravity<\/li>\n\n\n\n<li>Object permanence<\/li>\n\n\n\n<li>Social behavior<\/li>\n\n\n\n<li>Physical danger<\/li>\n\n\n\n<li>Emotional tone<\/li>\n<\/ul>\n\n\n\n<p>AI systems often lack this broad intuitive understanding unless specifically trained.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Could AI Eventually Overcome the Paradox?<\/h3>\n\n\n\n<p>Scientists continue improving AI through:<\/p>\n\n\n\n<ul>\n<li>Robotics<\/li>\n\n\n\n<li>Neural networks<\/li>\n\n\n\n<li>Reinforcement learning<\/li>\n\n\n\n<li>Multimodal systems<\/li>\n<\/ul>\n\n\n\n<p>Some experts believe future AI may eventually approach:<\/p>\n\n\n\n<ul>\n<li>Human-like sensory intelligence<\/li>\n<\/ul>\n\n\n\n<p>However, replicating the full flexibility of the human brain remains extremely difficult.<\/p>\n\n\n\n<p>Moravec\u2019s Paradox still highlights one important truth:<\/p>\n\n\n\n<ul>\n<li>The abilities humans take for granted are often the most extraordinary.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Why Moravec\u2019s Paradox Matters<\/h3>\n\n\n\n<p>The paradox changes how people think about:<\/p>\n\n\n\n<ul>\n<li>Intelligence itself<\/li>\n<\/ul>\n\n\n\n<p>It reveals that:<\/p>\n\n\n\n<ul>\n<li>Human cognition is deeply shaped by evolution and embodiment.<\/li>\n<\/ul>\n\n\n\n<p>Tasks humans consider \u201ceasy\u201d are often actually:<\/p>\n\n\n\n<ul>\n<li>Computational miracles<\/li>\n<\/ul>\n\n\n\n<p>performed effortlessly by the brain.<\/p>\n\n\n\n<p>Meanwhile:<\/p>\n\n\n\n<ul>\n<li>Logic and calculation<\/li>\n<\/ul>\n\n\n\n<p>which humans perceive as difficult:<\/p>\n\n\n\n<ul>\n<li>Fit naturally into computer architecture.<\/li>\n<\/ul>\n\n\n\n<p>Moravec\u2019s Paradox therefore reminds humanity that the ordinary abilities of:<\/p>\n\n\n\n<ul>\n<li>Children<\/li>\n\n\n\n<li>Animals<\/li>\n\n\n\n<li>Everyday human perception<\/li>\n<\/ul>\n\n\n\n<p>may represent some of the most advanced forms of intelligence found in nature.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Interesting Facts<\/h3>\n\n\n\n<ul>\n<li>AI mastered chess long before reliable robotic walking.<\/li>\n\n\n\n<li>Toddlers outperform many machines in flexible learning.<\/li>\n\n\n\n<li>Human vision requires enormous neural processing power.<\/li>\n\n\n\n<li>Moravec\u2019s Paradox was proposed during the 1980s.<\/li>\n\n\n\n<li>Evolution optimized sensory skills over hundreds of millions of years.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Glossary<\/h3>\n\n\n\n<ul>\n<li><strong>Moravec\u2019s Paradox<\/strong> \u2014 Observation that human-like perception is harder for AI than logic tasks.<\/li>\n\n\n\n<li><strong>Deep Learning<\/strong> \u2014 AI method using multi-layer neural networks.<\/li>\n\n\n\n<li><strong>Computer Vision<\/strong> \u2014 AI field focused on image and visual interpretation.<\/li>\n\n\n\n<li><strong>Neural Network<\/strong> \u2014 Computational model inspired by biological brains.<\/li>\n\n\n\n<li><strong>Embodied Intelligence<\/strong> \u2014 Intelligence shaped by interaction with the physical world.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>At first glance, artificial intelligence seems astonishingly smart. Modern AI systems can: Yet surprisingly, many tasks that feel effortless to humans remain extremely difficult for machines. For example: This strange&hellip;<\/p>\n","protected":false},"author":2,"featured_media":3258,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_sitemap_exclude":false,"_sitemap_priority":"","_sitemap_frequency":"","footnotes":""},"categories":[62,58,65,60],"tags":[],"_links":{"self":[{"href":"https:\/\/science-x.net\/index.php?rest_route=\/wp\/v2\/posts\/3257"}],"collection":[{"href":"https:\/\/science-x.net\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/science-x.net\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/science-x.net\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/science-x.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3257"}],"version-history":[{"count":1,"href":"https:\/\/science-x.net\/index.php?rest_route=\/wp\/v2\/posts\/3257\/revisions"}],"predecessor-version":[{"id":3259,"href":"https:\/\/science-x.net\/index.php?rest_route=\/wp\/v2\/posts\/3257\/revisions\/3259"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/science-x.net\/index.php?rest_route=\/wp\/v2\/media\/3258"}],"wp:attachment":[{"href":"https:\/\/science-x.net\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3257"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/science-x.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3257"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/science-x.net\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3257"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}