{"id":25208,"date":"2026-06-23T11:42:57","date_gmt":"2026-06-23T15:42:57","guid":{"rendered":"https:\/\/carleton.ca\/scs\/?p=25208"},"modified":"2026-06-23T12:17:57","modified_gmt":"2026-06-23T16:17:57","slug":"categorizing-ai-from-a-computer-science-perspective","status":"publish","type":"post","link":"https:\/\/carleton.ca\/scs\/2026\/categorizing-ai-from-a-computer-science-perspective\/","title":{"rendered":"Categorizing AI from a Computer Science Perspective"},"content":{"rendered":"\n<section class=\"w-screen px-6 cu-section cu-section--white ml-offset-center md:px-8 lg:px-14\">\n    <div class=\"space-y-6 cu-max-w-child-5xl  md:space-y-10 cu-prose-first-last\">\n\n            <div class=\"cu-textmedia flex flex-col lg:flex-row mx-auto gap-6 md:gap-10 my-6 md:my-12 first:mt-0 max-w-5xl\">\n        <div class=\"justify-start cu-textmedia-content cu-prose-first-last\" style=\"flex: 0 0 100%;\">\n            <header class=\"font-light prose-xl cu-pageheader md:prose-2xl cu-component-updated cu-prose-first-last\">\n                                    <h1 class=\"cu-prose-first-last font-semibold !mt-2 mb-4 md:mb-6 relative after:absolute after:h-px after:bottom-0 after:bg-cu-red after:left-px text-3xl md:text-4xl lg:text-5xl lg:leading-[3.5rem] pb-5 after:w-10 text-cu-black-700 not-prose\">\n                        Categorizing AI from a Computer Science Perspective\n                    <\/h1>\n                \n                                \n                                    \n\n<p>Education is the most effective tool we have for separating fact from fiction, and fostering genuine AI literacy is a vital step toward a more informed and discerning society. <\/p>\n\n\n                            <\/header>\n\n                    <\/div>\n\n            <\/div>\n\n    <\/div>\n<\/section>\n\n\n\n<p>While AI has only recently captured widespread public attention, it has been a serious and evolving field of computer science research for many decades. This distinction matters more than ever, a well informed public is essential to navigating the AI landscape responsibly. Understanding what AI actually is, rather than relying on sensationalized portrayals, empowers people to think critically about AI tech.<\/p>\n\n\n\n<p>The University of Toronto&#8217;s CANHEIT 2023 conference brought together leading voices in technology, including Dr. Hod Lipson of Columbia University, who delivered a keynote address over the course of the event. A prominent figure in computer science, Dr. Lipson&#8217;s work centers on robotics and artificial intelligence, and his talk offered attendees a compelling, Computer Science grounded framework for understanding and categorizing AI.<\/p>\n\n\n\n<p>Dr. Lipson\u2019s waves organizes the AI tech in an order they are invented.<\/p>\n\n\n\n<section class=\"w-screen px-6 cu-section cu-section--white ml-offset-center md:px-8 lg:px-14\">\n    <div class=\"space-y-6 cu-max-w-child-5xl  md:space-y-10 cu-prose-first-last\">\n\n        \n    \n    <dl class=\"cu-description cu-component-updated\">\n        \n    <div class=\"grid pt-4 pb-3 border-b accordion border-cu-black-100 md:pt-6 md:pb-5 first:border-t\">\n        <dt class=\"font-semibold not-prose\">\n            <button class=\"flex items-center justify-between w-full text-left accordion__button\" aria-expanded=\"false\" aria-controls=\"accordion-wave-1-rules-based-symbolic-ai\">\n                <span class=\"flex-1 ml-auto text-left break-words whitespace-normal cu-icon\">\n                    Wave 1: Rules Based \/ Symbolic AI\n                <\/span>\n                <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" fill=\"none\" viewbox=\"0 0 24 24\" stroke-width=\"1.5\" stroke=\"currentColor\" aria-hidden=\"true\" data-slot=\"icon\" class=\"w-5 h-5 ml-auto transition-transform rotate-0 accordion__icon text-cu-black-500\">\n                    <path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M8.25 4.5l7.5 7.5-7.5 7.5\"><\/path>\n                <\/svg>\n            <\/button>\n        <\/dt>\n        <dd class=\"p-0 mt-0 cu-prose cu-prose-first-last accordion__content md:p-0 md:mt-0\" hidden=\"\" id=\"accordion-wave-1-rules-based-symbolic-ai\">\n            \n\n<p><\/p>\n\n\n\n<p><strong>Timeframe<\/strong>: 1950&#8217;s\u20131980&#8217;s<br><br><strong class=\"myprefix-text-bold\">Core idea<\/strong><br>Hand\u2011crafted rules and logic. Systems do exactly what experts encode: if\u2011then rules, symbolic reasoning, decision trees, early planners.<br><br><strong class=\"myprefix-text-bold\">Classic tech\/achievements<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Early chess engines (Turing\u2011style algorithms, pre\u2011learning engines, even Deep Blue\u2019s core search + handcrafted eval).<\/li>\n\n\n\n<li>Expert systems like MYCIN and DENDRAL.<\/li>\n\n\n\n<li>Classic game \u201cAI\u201d: Pac\u2011Man ghosts, early FPS bots, RTS scripts, finite\u2011state machines, behavior trees.<\/li>\n\n\n\n<li>Limits: No learning; brittle outside predefined situations; cannot improve from data.<\/li>\n<\/ul>\n\n\n\n<p><\/p>\n\n\n        <\/dd>\n    <\/div>\n\n\n    <div class=\"grid pt-4 pb-3 border-b accordion border-cu-black-100 md:pt-6 md:pb-5 first:border-t\">\n        <dt class=\"font-semibold not-prose\">\n            <button class=\"flex items-center justify-between w-full text-left accordion__button\" aria-expanded=\"false\" aria-controls=\"accordion-wave-2-analytical-predictive-ai-big-data\">\n                <span class=\"flex-1 ml-auto text-left break-words whitespace-normal cu-icon\">\n                    Wave 2: Analytical \/ Predictive AI \/ Big Data\n                <\/span>\n                <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" fill=\"none\" viewbox=\"0 0 24 24\" stroke-width=\"1.5\" stroke=\"currentColor\" aria-hidden=\"true\" data-slot=\"icon\" class=\"w-5 h-5 ml-auto transition-transform rotate-0 accordion__icon text-cu-black-500\">\n                    <path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M8.25 4.5l7.5 7.5-7.5 7.5\"><\/path>\n                <\/svg>\n            <\/button>\n        <\/dt>\n        <dd class=\"p-0 mt-0 cu-prose cu-prose-first-last accordion__content md:p-0 md:mt-0\" hidden=\"\" id=\"accordion-wave-2-analytical-predictive-ai-big-data\">\n            \n\n<p><\/p>\n\n\n\n<p><strong>Timeframe<\/strong>: 1990&#8217;s\u20132000&#8217;s<br><\/p>\n\n\n\n<p><strong class=\"myprefix-text-bold\">Core idea<\/strong><br>Statistical learning on large datasets to predict or rank<br><\/p>\n\n\n\n<p><strong class=\"myprefix-text-bold\">Tech Examples<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Web searches, credit scoring, fraud detection, ad click\u2011through prediction.<\/li>\n\n\n\n<li>Classic Google Search core ranking and query understanding: heavy ML on logs and click data.<\/li>\n\n\n\n<li>Big\u2011data stacks: Hadoop\/HDFS\/MapReduce\/YARN powering data lakes, offline feature generation, large\u2011scale ETL.<\/li>\n\n\n\n<li><strong>\u201cBig data\u201d connection<\/strong>: The term <em>big data<\/em> became mainstream in this era, cheap storage + distributed compute + huge logs = feeding predictive models.<\/li>\n\n\n\n<li><strong>Limits<\/strong>: Great at prediction, weak at perception or open ended content generation; mostly works on structured or engineered features.<\/li>\n<\/ul>\n\n\n        <\/dd>\n    <\/div>\n\n\n    <div class=\"grid pt-4 pb-3 border-b accordion border-cu-black-100 md:pt-6 md:pb-5 first:border-t\">\n        <dt class=\"font-semibold not-prose\">\n            <button class=\"flex items-center justify-between w-full text-left accordion__button\" aria-expanded=\"false\" aria-controls=\"accordion-wave-3-cognitive-perceptual\">\n                <span class=\"flex-1 ml-auto text-left break-words whitespace-normal cu-icon\">\n                    Wave 3: Cognitive \/ Perceptual\n                <\/span>\n                <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" fill=\"none\" viewbox=\"0 0 24 24\" stroke-width=\"1.5\" stroke=\"currentColor\" aria-hidden=\"true\" data-slot=\"icon\" class=\"w-5 h-5 ml-auto transition-transform rotate-0 accordion__icon text-cu-black-500\">\n                    <path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M8.25 4.5l7.5 7.5-7.5 7.5\"><\/path>\n                <\/svg>\n            <\/button>\n        <\/dt>\n        <dd class=\"p-0 mt-0 cu-prose cu-prose-first-last accordion__content md:p-0 md:mt-0\" hidden=\"\" id=\"accordion-wave-3-cognitive-perceptual\">\n            \n\n<p><\/p>\n\n\n\n<p><strong class=\"myprefix-text-bold\">Core idea<\/strong><br>Deep learning for perception, recognizing patterns in unstructured data: images, audio, video, sensor streams.<br><\/p>\n\n\n\n<p><strong class=\"myprefix-text-bold\">Tech Examples<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Image classification, object detection, speech recognition, medical imaging diagnostics. Enables applications like driverless cars and general \u201cunderstand what I\u2019m seeing\u201d capabilities.<\/li>\n\n\n\n<li>Systems can recognize objects and patterns in unstructured data like images, audio, and video (distinguishing cats vs dogs, pedestrians vs road, cancerous vs benign lesions).<br><\/li>\n<\/ul>\n\n\n\n<p><strong>Limits<\/strong>: Perceives well but doesn\u2019t inherently plan, act, or create still largely task\u2011specific.<\/p>\n\n\n        <\/dd>\n    <\/div>\n\n\n    <div class=\"grid pt-4 pb-3 border-b accordion border-cu-black-100 md:pt-6 md:pb-5 first:border-t\">\n        <dt class=\"font-semibold not-prose\">\n            <button class=\"flex items-center justify-between w-full text-left accordion__button\" aria-expanded=\"false\" aria-controls=\"accordion-wave-4-generative-creative-ai\">\n                <span class=\"flex-1 ml-auto text-left break-words whitespace-normal cu-icon\">\n                    Wave 4: Generative \/ Creative AI\n                <\/span>\n                <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" fill=\"none\" viewbox=\"0 0 24 24\" stroke-width=\"1.5\" stroke=\"currentColor\" aria-hidden=\"true\" data-slot=\"icon\" class=\"w-5 h-5 ml-auto transition-transform rotate-0 accordion__icon text-cu-black-500\">\n                    <path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M8.25 4.5l7.5 7.5-7.5 7.5\"><\/path>\n                <\/svg>\n            <\/button>\n        <\/dt>\n        <dd class=\"p-0 mt-0 cu-prose cu-prose-first-last accordion__content md:p-0 md:mt-0\" hidden=\"\" id=\"accordion-wave-4-generative-creative-ai\">\n            \n\n<p><\/p>\n\n\n\n<p><strong>Timeframe<\/strong>: Late 2010&#8217;s &#8211; 2020&#8217;s<br><\/p>\n\n\n\n<p><strong class=\"myprefix-text-bold\">Core idea<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Models that can <em>generate<\/em> new content by learning high\u2011dimensional distributions: text, images, code, audio, video, designs.<\/li>\n\n\n\n<li>Systems can generate new artifacts, text, code, images, video, designed by learning to \u201cfill in the blank\u201d in the media its working on.<\/li>\n<\/ul>\n\n\n\n<p><strong class=\"myprefix-text-bold\">Tech Examples<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Large language models, diffusion models, and other generative architectures.<\/li>\n\n\n\n<li>Modern \u201cAI answers\u201d in search: Gemini\/LLM\u2011powered AI Mode summarizing and synthesizing results on top of classic retrieval.<\/li>\n<\/ul>\n\n\n\n<p><\/p>\n\n\n\n<p><strong>Impact<\/strong>: Enables creative workflows, code generation, and AI designed artifacts.<br><strong>Limits<\/strong>: Still often ungrounded, can hallucinate, can lack robust physical\/causal understanding without embodiment.<\/p>\n\n\n        <\/dd>\n    <\/div>\n\n\n    <div class=\"grid pt-4 pb-3 border-b accordion border-cu-black-100 md:pt-6 md:pb-5 first:border-t\">\n        <dt class=\"font-semibold not-prose\">\n            <button class=\"flex items-center justify-between w-full text-left accordion__button\" aria-expanded=\"false\" aria-controls=\"accordion-wave-5-embodied-ai-robots\">\n                <span class=\"flex-1 ml-auto text-left break-words whitespace-normal cu-icon\">\n                    Wave 5: Embodied AI\u00a0 \/ Robots\n                <\/span>\n                <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" fill=\"none\" viewbox=\"0 0 24 24\" stroke-width=\"1.5\" stroke=\"currentColor\" aria-hidden=\"true\" data-slot=\"icon\" class=\"w-5 h-5 ml-auto transition-transform rotate-0 accordion__icon text-cu-black-500\">\n                    <path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M8.25 4.5l7.5 7.5-7.5 7.5\"><\/path>\n                <\/svg>\n            <\/button>\n        <\/dt>\n        <dd class=\"p-0 mt-0 cu-prose cu-prose-first-last accordion__content md:p-0 md:mt-0\" hidden=\"\" id=\"accordion-wave-5-embodied-ai-robots\">\n            \n\n<p><\/p>\n\n\n\n<p><strong>Timeframe<\/strong>: 2010&#8217;s &#8211; 2020&#8217;s+<br><\/p>\n\n\n\n<p><strong class=\"myprefix-text-bold\">Core idea<\/strong><br>Intelligence connected to bodies operating in the physical world, robots that sense, plan, and act in messy, dynamic environments.<br><\/p>\n\n\n\n<p><strong class=\"myprefix-text-bold\">Tech Examples<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Self\u2011driving cars as embodied systems: perception (Wave 3) + prediction (Wave 2) + generative planning (Wave 4) + low\u2011level control on real hardware.<\/li>\n\n\n\n<li>Manipulation robots, legged robots, drones, warehouse and logistics robots.<\/li>\n<\/ul>\n\n\n\n<p><\/p>\n\n\n\n<p><strong>Characteristics<\/strong>: Must handle dynamics, energy limits, safety, and irreversible physical errors; mistakes are expensive and sometimes dangerous.<br><strong>Limits<\/strong>: Hardware is hard: actuators, power, robustness and scaling beyond well structured environments is slow.<\/p>\n\n\n        <\/dd>\n    <\/div>\n\n\n    <div class=\"grid pt-4 pb-3 border-b accordion border-cu-black-100 md:pt-6 md:pb-5 first:border-t\">\n        <dt class=\"font-semibold not-prose\">\n            <button class=\"flex items-center justify-between w-full text-left accordion__button\" aria-expanded=\"false\" aria-controls=\"accordion-wave-6-sentient-agi-like-ai\">\n                <span class=\"flex-1 ml-auto text-left break-words whitespace-normal cu-icon\">\n                    Wave 6: Sentient \/ AGI Like AI\n                <\/span>\n                <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" fill=\"none\" viewbox=\"0 0 24 24\" stroke-width=\"1.5\" stroke=\"currentColor\" aria-hidden=\"true\" data-slot=\"icon\" class=\"w-5 h-5 ml-auto transition-transform rotate-0 accordion__icon text-cu-black-500\">\n                    <path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M8.25 4.5l7.5 7.5-7.5 7.5\"><\/path>\n                <\/svg>\n            <\/button>\n        <\/dt>\n        <dd class=\"p-0 mt-0 cu-prose cu-prose-first-last accordion__content md:p-0 md:mt-0\" hidden=\"\" id=\"accordion-wave-6-sentient-agi-like-ai\">\n            \n\n<p><\/p>\n\n\n\n<p><strong>Timeframe<\/strong>: 2020&#8217;s+<br><\/p>\n\n\n\n<p><strong class=\"myprefix-text-bold\">Core idea<\/strong><br>Systems with explicit self\u2011models that can imagine themselves in the future, reason over those imagined futures, and adapt, taking on \u201cself\u2011awareness\u201d and AGI (Artificial General Intelligence).<br><\/p>\n\n\n\n<p><strong class=\"myprefix-text-bold\">Tech Examples (early\/prototypes)<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Self\u2011modeling robots that infer their own body plan from sensor data and learn to walk by simulating themselves.<\/li>\n\n\n\n<li>\u201cMachine scientists\u201d that infer physical laws from data and autonomously generate and test hypotheses.<br>This is often associated with Artificial General Intelligence (AGI), which excites and alarms many observers.<br><\/li>\n<\/ul>\n\n\n\n<p>Dr. Lipson expects this to be achievable and likely sooner than many think, seeing consciousness as an engineering problem rather than mysticism.<\/p>\n\n\n\n<p><strong>Open questions<\/strong>: Safety, governance, interpretability, and how to \u201csteer\u201d such systems rather than fear them.<\/p>\n\n\n        <\/dd>\n    <\/div>\n\n\n    <\/dl>\n\n\n    <\/div>\n<\/section>\n\n\n\n<p><strong>Author<\/strong>: Andrew Miles, Sr System Administrator, School of Computer Science, Carleton University<\/p>\n\n\n\n<p><strong>Disclaimer<\/strong>: This document does not represent the official views of Dr. Hod Lipson. It is my personal interpretation and summary of his keynote presentation, and any errors or omissions are entirely my own. This posts creation was assisted using generative AI tools.<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>While AI has only recently captured widespread public attention, it has been a serious and evolving field of computer science research for many decades. This distinction matters more than ever, a well informed public is essential to navigating the AI landscape responsibly. Understanding what AI actually is, rather than relying on sensationalized portrayals, empowers people [&hellip;]<\/p>\n","protected":false},"author":46,"featured_media":19072,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[53,65,1],"tags":[],"class_list":["post-25208","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tech-announcements","category-tech-tips","category-uncategorized"],"acf":{"cu_post_thumbnail":""},"_links":{"self":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/posts\/25208","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/users\/46"}],"replies":[{"embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/comments?post=25208"}],"version-history":[{"count":5,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/posts\/25208\/revisions"}],"predecessor-version":[{"id":25216,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/posts\/25208\/revisions\/25216"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/media\/19072"}],"wp:attachment":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/media?parent=25208"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/categories?post=25208"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/tags?post=25208"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}