{"id":614,"date":"2026-03-22T15:00:00","date_gmt":"2026-03-22T19:00:00","guid":{"rendered":"https:\/\/laeka.org\/blog\/archives\/614"},"modified":"2026-03-23T11:50:56","modified_gmt":"2026-03-23T15:50:56","slug":"your-brain-is-a-neural-network","status":"publish","type":"post","link":"https:\/\/laeka.org\/blog\/your-brain-is-a-neural-network\/","title":{"rendered":"Your Brain Is a Neural Network. So Is ChatGPT."},"content":{"rendered":"<p>When scientists invented artificial neural networks in the 1950s, they were inspired by the human brain. Not to copy it \u2014 to steal a good idea.<\/p>\n<p>Your brain contains roughly 86 billion neurons. Each neuron is connected to thousands of others. When you recognize your mother&#8217;s face in a crowd, it&#8217;s not a single neuron doing the work. It&#8217;s a <strong>network<\/strong> of neurons firing together.<\/p>\n<p>AI works on the same principle. Except its neurons are lines of code and its connections are numbers.<\/p>\n<h2>How it works in your head<\/h2>\n<p>Imagine you&#8217;re learning to recognize a dog. The first time you see a dog, your brain activates certain neurons. The second time, the same neurons fire a bit stronger. After 100 dogs, the connections between those neurons are so reinforced that you recognize a dog instantly \u2014 even one you&#8217;ve never seen before.<\/p>\n<p>That&#8217;s called <strong>learning through connection reinforcement<\/strong>. The more a connection is used, the stronger it gets. It&#8217;s like a trail in the woods: the more you walk it, the easier it is to follow.<\/p>\n<h2>How it works in ChatGPT<\/h2>\n<p>An artificial neural network does exactly the same thing. It has &#8220;neurons&#8221; (small math calculations) connected by &#8220;weights&#8221; (numbers). When you show it data, it adjusts its weights to better recognize patterns.<\/p>\n<p>ChatGPT has around 175 billion parameters. Each parameter is a connection weight. It&#8217;s like 175 billion trails in the woods, each with a different width.<\/p>\n<p>When you type &#8220;What is the capital of Canada?&#8221;, the information passes through those billions of connections, each neuron contributes a small piece, and at the end of the path, the word &#8220;Ottawa&#8221; comes out with the highest probability.<\/p>\n<h2>The differences (they&#8217;re huge)<\/h2>\n<p>Your brain and ChatGPT share a basic principle, but the differences are enormous.<\/p>\n<p>Your brain uses about <strong>20 watts<\/strong> of energy. Like a small light bulb. ChatGPT uses thousands to answer your questions. Your brain is incredibly efficient.<\/p>\n<p>Your brain learns continuously. Every experience changes it a little. ChatGPT is frozen after training \u2014 it doesn&#8217;t learn from your conversation (unless it&#8217;s retrained). It&#8217;s like the difference between a musician who improvises and a jukebox playing recorded songs.<\/p>\n<p>And most importantly: your brain is connected to a body. It knows what cold feels like, what hunger is, what fatigue is. ChatGPT has never been cold in its life. This <strong>embodied experience<\/strong> fundamentally changes how you understand the world.<\/p>\n<h2>Why this is useful to know<\/h2>\n<p>Understanding that AI is inspired by the brain \u2014 without being a brain \u2014 helps you use it better. You know why it&#8217;s good at pattern recognition. You know why it&#8217;s bad at common sense. You know it doesn&#8217;t &#8220;learn&#8221; from you in real time.<\/p>\n<p>It&#8217;s like understanding your car&#8217;s engine. You don&#8217;t become a mechanic, but you know when something sounds off.<\/p>\n<p>At <a href='https:\/\/laeka.org\/lab\/'>Laeka Research<\/a>, we study these parallels between human and artificial cognition. And with <a href='https:\/\/sherpa.live'>Sherpa<\/a>, we give you the tools to interact with AI while understanding how it works \u2014 not just hoping it does.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>When scientists invented artificial neural networks in the 1950s, they were inspired by the human brain. Not to copy it&#8230;<\/p>\n","protected":false},"author":1,"featured_media":13,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_kad_post_transparent":"","_kad_post_title":"","_kad_post_layout":"","_kad_post_sidebar_id":"","_kad_post_content_style":"","_kad_post_vertical_padding":"","_kad_post_feature":"","_kad_post_feature_position":"","_kad_post_header":false,"_kad_post_footer":false,"_kad_post_classname":"","footnotes":""},"categories":[190],"tags":[],"class_list":["post-614","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-understanding-ai"],"_links":{"self":[{"href":"https:\/\/laeka.org\/blog\/wp-json\/wp\/v2\/posts\/614","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/laeka.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/laeka.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/laeka.org\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/laeka.org\/blog\/wp-json\/wp\/v2\/comments?post=614"}],"version-history":[{"count":1,"href":"https:\/\/laeka.org\/blog\/wp-json\/wp\/v2\/posts\/614\/revisions"}],"predecessor-version":[{"id":700,"href":"https:\/\/laeka.org\/blog\/wp-json\/wp\/v2\/posts\/614\/revisions\/700"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/laeka.org\/blog\/wp-json\/wp\/v2\/media\/13"}],"wp:attachment":[{"href":"https:\/\/laeka.org\/blog\/wp-json\/wp\/v2\/media?parent=614"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/laeka.org\/blog\/wp-json\/wp\/v2\/categories?post=614"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/laeka.org\/blog\/wp-json\/wp\/v2\/tags?post=614"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}