{"id":10155,"date":"2023-06-02T16:46:52","date_gmt":"2023-06-02T16:46:52","guid":{"rendered":"https:\/\/andrewdoran.uk\/blog\/?p=10155"},"modified":"2023-06-02T16:46:56","modified_gmt":"2023-06-02T16:46:56","slug":"trying-to-understand-how-chatgpt-works","status":"publish","type":"post","link":"https:\/\/andrewdoran.uk\/blog\/2023\/06\/02\/trying-to-understand-how-chatgpt-works\/","title":{"rendered":"Trying to understand how ChatGPT works"},"content":{"rendered":"<div class='e-content'>I finally got around to reading the Stephen Wolfram essay on <em><a title=\"Stephen Wolfram: Writings: What Is ChatGPT Doing \u2026 and Why Does It Work?\" href=\"https:\/\/writings.stephenwolfram.com\/2023\/02\/what-is-chatgpt-doing-and-why-does-it-work\/\">What Is ChatGPT Doing \u2026 and Why Does It Work?<\/a><\/em> Despite being written in relatively simple terms, the article still pushed the boundaries of my comprehension. Parts of it landed on my brain like an impressionist painting.<\/p>\n<p>Things that stuck out for me:<\/p>\n<ul>\n<li>In order to improve the output, a deliberate injection of randomness (called \u2018<a title=\"Stack Exchange: Artificial Intelligence: What is the &quot;temperature&quot; in the GPT models?\" href=\"https:\/\/ai.stackexchange.com\/questions\/32477\/what-is-the-temperature-in-the-gpt-models\">temperature<\/a>\u2019) is required, which means that \u2018lower-probability\u2019 words get added as text is generated. Without this, the output seems to be \u201cflatter\u201d, \u201cless interesting\u201d and doesn\u2019t \u201cshow any creativity\u201d.<\/li>\n<li>Neural networks are better at more complex problems than on simple ones. Doing arithmetic via a neural network-based AI is very difficult as there is no sequence of operations as you would find in a traditional procedural computer program. Humans can do lots of complicated tasks, but we use computers for calculations because they are better at doing this type of work than we are. Now that <a title=\"OpenAI: ChatGPT plugins\" href=\"https:\/\/openai.com\/blog\/chatgpt-plugins\">plugins are available for ChatGPT<\/a>, it can itself \u2018<a title=\"Stratechery: ChatGPT Gets a Computer\" href=\"https:\/\/stratechery.com\/2023\/chatgpt-learns-computing\/\">use a computer<\/a>\u2019 in a similar way that we do, offloading this type of traditional computational work.<\/li>\n<li>Many times, Wolfram says something along the lines of \u201cwe don\u2019t know why this works, it just does\u201d. The whole field of AI using neural networks seems to be trial and error, as the models are too complex for us to fathom and reason about.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-10154 size-full\" src=\"https:\/\/andrewdoran.uk\/blog\/wp-content\/uploads\/2023\/06\/0118AF5A-F89B-456E-A5B9-6270EC1C44AF.png\" alt=\"Particularly over the past decade, there\u2019ve been many advances in the art of training neural nets. And, yes, it is basically an art. Sometimes\u2014especially in retrospect\u2014one can see at least a glimmer of a \u201cscientific explanation\u201d for something that\u2019s being done. But mostly things have been discovered by trial and error, adding ideas and tricks that have progressively built a significant lore about how to work with neural nets.\" width=\"1200\" height=\"675\" srcset=\"https:\/\/andrewdoran.uk\/blog\/wp-content\/uploads\/2023\/06\/0118AF5A-F89B-456E-A5B9-6270EC1C44AF.png 1200w, https:\/\/andrewdoran.uk\/blog\/wp-content\/uploads\/2023\/06\/0118AF5A-F89B-456E-A5B9-6270EC1C44AF-300x169.png 300w, https:\/\/andrewdoran.uk\/blog\/wp-content\/uploads\/2023\/06\/0118AF5A-F89B-456E-A5B9-6270EC1C44AF-1024x576.png 1024w, https:\/\/andrewdoran.uk\/blog\/wp-content\/uploads\/2023\/06\/0118AF5A-F89B-456E-A5B9-6270EC1C44AF-768x432.png 768w, https:\/\/andrewdoran.uk\/blog\/wp-content\/uploads\/2023\/06\/0118AF5A-F89B-456E-A5B9-6270EC1C44AF-700x394.png 700w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/p>\n<ul>\n<li>People do seem to be looking at the output from ChatGPT and then quickly drawing conclusions of where things are headed from a \u2018general intelligence\u2019 point of view. <a title=\"Matt Ballantine: The Halo Effect of ChatGPT\" href=\"https:\/\/mmitii.mattballantine.com\/2023\/05\/30\/the-halo-effect-of-chatgpt\/\">As Matt Ballantine puts it<\/a>, this may be a kind of \u2018<a title=\"Wikipedia: Halo effect\" href=\"https:\/\/en.wikipedia.org\/wiki\/Halo_effect\">Halo effect<\/a>\u2019, where we are projecting our hopes and fears onto the technology. However, just because it is good at one type of task \u2014 generating text \u2014 doesn\u2019t necessarily mean that it is good at other types of tasks. From Wolfram\u2019s essay:<\/li>\n<\/ul>\n<blockquote><p>But there\u2019s something potentially confusing about all of this. In the past there were plenty of tasks\u2014including writing essays\u2014that we\u2019ve assumed were somehow \u201cfundamentally too hard\u201d for computers. And now that we see them done by the likes of ChatGPT we tend to suddenly think that computers must have become vastly more powerful\u2014in particular surpassing things they were already basically able to do [\u2026]<\/p>\n<p>But this isn\u2019t the right conclusion to draw. Computationally irreducible processes are still computationally irreducible, and are still fundamentally hard for computers\u2014even if computers can readily compute their individual steps. And instead what we should conclude is that tasks\u2014like writing essays\u2014that we humans could do, but we didn\u2019t think computers could do, are actually in some sense computationally easier than we thought.<\/p><\/blockquote>\n<ul>\n<li>So my last big takeaway is that \u2014 maybe \u2014 human language is much less complex than we thought it was.<\/li>\n<\/ul>\n<\/div>\n<p><span hidden class=\"__iawmlf-post-loop-links\" data-iawmlf-links=\"[{&quot;id&quot;:2380,&quot;href&quot;:&quot;https:\\\/\\\/writings.stephenwolfram.com\\\/2023\\\/02\\\/what-is-chatgpt-doing-and-why-does-it-work&quot;,&quot;archived_href&quot;:&quot;http:\\\/\\\/web-wp.archive.org\\\/web\\\/20260203002742\\\/https:\\\/\\\/writings.stephenwolfram.com\\\/2023\\\/02\\\/what-is-chatgpt-doing-and-why-does-it-work\\\/&quot;,&quot;redirect_href&quot;:&quot;&quot;,&quot;checks&quot;:[{&quot;date&quot;:&quot;2026-02-04 02:44:18&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-02-20 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19:56:47&quot;,&quot;http_code&quot;:200}],&quot;broken&quot;:false,&quot;last_checked&quot;:{&quot;date&quot;:&quot;2026-06-22 19:56:47&quot;,&quot;http_code&quot;:200},&quot;process&quot;:&quot;done&quot;}]\"><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<a href=\"https:\/\/andrewdoran.uk\/blog\/2023\/06\/02\/trying-to-understand-how-chatgpt-works\/\" rel=\"bookmark\" title=\"Permalink to Trying to understand how ChatGPT works\"><div class='e-content p-summary'>I finally got around to reading the Stephen Wolfram essay on What Is ChatGPT Doing \u2026 and Why Does It Work? Despite being written in relatively simple terms, the article still pushed the boundaries of my comprehension. Parts of it landed on my brain like an impressionist painting. Things that stuck out for me: In [&hellip;]<\/div>\n<\/a>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"webmentions_disabled_pings":false,"webmentions_disabled":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"activitypub_content_warning":"","activitypub_content_visibility":"","activitypub_max_image_attachments":3,"activitypub_interaction_policy_quote":"anyone","activitypub_status":"","footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[37,16],"tags":[],"class_list":{"0":"post-10155","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-science","7":"category-technology","8":"h-entry","10":"hentry"},"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack-related-posts":[{"id":12704,"url":"https:\/\/andrewdoran.uk\/blog\/2025\/11\/18\/chatgpt-image-weirdness\/","url_meta":{"origin":10155,"position":0},"title":"ChatGPT image weirdness","author":"Andrew Doran","date":"18 November 2025","format":false,"excerpt":"About a year ago, I asked ChatGPT \u201cBased on what you know about me, draw a picture what my current\u00a0life\u00a0is.\u201d It came up with this: Aside from the fact that it has that typical AI feel about it, I was intrigued by the elements it contained. 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Having such a stark example of this on a mainstream TV\u2026","rel":"","context":"In &quot;News&quot;","block_context":{"text":"News","link":"https:\/\/andrewdoran.uk\/blog\/category\/news\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/img.youtube.com\/vi\/7fej5XgfBYQ\/0.jpg?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":10131,"url":"https:\/\/andrewdoran.uk\/blog\/2023\/05\/24\/book-summaries-with-and-without-ai\/","url_meta":{"origin":10155,"position":2},"title":"\ud83d\udcda Book summaries \u2014 with and without AI","author":"Andrew Doran","date":"24 May 2023","format":false,"excerpt":"This is an excellent blog post on working with ChatGPT to generate insightful book summaries. It\u2019s long, but it covers a lot of ground in terms of what the technology does well and what it struggles with right now. Jumping to the conclusion, it seems that you get much better\u2026","rel":"","context":"In &quot;Books&quot;","block_context":{"text":"Books","link":"https:\/\/andrewdoran.uk\/blog\/category\/books\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":11007,"url":"https:\/\/andrewdoran.uk\/blog\/2024\/07\/16\/11007\/","url_meta":{"origin":10155,"position":3},"title":"Generative AI just doing its\u2026","author":"Andrew Doran","date":"16 July 2024","format":"status","excerpt":"Generative AI just doing its thing. Simple question, two \u2018market leading\u2019 models from the same vendor, opposite answers.","rel":"","context":"In &quot;Snippets&quot;","block_context":{"text":"Snippets","link":"https:\/\/andrewdoran.uk\/blog\/category\/snippets\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/andrewdoran.uk\/blog\/wp-content\/uploads\/2024\/07\/img_2629-1.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/andrewdoran.uk\/blog\/wp-content\/uploads\/2024\/07\/img_2629-1.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/andrewdoran.uk\/blog\/wp-content\/uploads\/2024\/07\/img_2629-1.jpg?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/andrewdoran.uk\/blog\/wp-content\/uploads\/2024\/07\/img_2629-1.jpg?resize=700%2C400&ssl=1 2x, https:\/\/i0.wp.com\/andrewdoran.uk\/blog\/wp-content\/uploads\/2024\/07\/img_2629-1.jpg?resize=1050%2C600&ssl=1 3x, https:\/\/i0.wp.com\/andrewdoran.uk\/blog\/wp-content\/uploads\/2024\/07\/img_2629-1.jpg?resize=1400%2C800&ssl=1 4x"},"classes":[]},{"id":10225,"url":"https:\/\/andrewdoran.uk\/blog\/2023\/06\/27\/10225\/","url_meta":{"origin":10155,"position":4},"title":"Interesting video showing some of\u2026","author":"Andrew Doran","date":"27 June 2023","format":"status","excerpt":"Interesting video showing some of the 'failure modes' of large language models such as ChatGPT. On the one hand it is comforting to recognise that these tools can reveal themselves to be fallible machines. On the other, I fear that despite this, people won't heed these flaws and they will\u2026","rel":"","context":"In &quot;Snippets&quot;","block_context":{"text":"Snippets","link":"https:\/\/andrewdoran.uk\/blog\/category\/snippets\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/img.youtube.com\/vi\/PAVeYUgknMw\/0.jpg?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":12468,"url":"https:\/\/andrewdoran.uk\/blog\/2025\/09\/10\/weeknotes-341-just-the-three-of-us\/","url_meta":{"origin":10155,"position":5},"title":"Weeknotes #341 \u2014 Just the three of us","author":"Andrew Doran","date":"10 September 2025","format":false,"excerpt":"A busy, beavering kind of week. It\u2019s still strange with just three of us at home. I\u2019m grateful that both of the boys seem to be settling into their next thing, with our eldest seeming to be very happy in Texas and our youngest enjoying the start of sixth form.\u2026","rel":"","context":"In &quot;Weeknotes&quot;","block_context":{"text":"Weeknotes","link":"https:\/\/andrewdoran.uk\/blog\/category\/weeknotes\/"},"img":{"alt_text":"\u201cAbrams observed the effects of the post-war baby and economic booms. By mid-1958, there were 6,450,000 young people aged between fifteen and twenty-five. In this period, unemployment was low and the young could command good wages: Abrams estimated that they were earning about \u00a31,480,000,000 a year in total, which, after taxes and deductions, ended up at a figure of '\u00a3900 millions a year to be spent by teenagers at their own discretion' - which was double their spending power in 1939. 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