<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0">
  <channel>
    <title>links.lmorchard.com - #compsci</title>
    <link>/tags/compsci/</link>
    <description>Recent bookmarks tagged #compsci</description>
    <lastBuildDate>Mon, 02 Nov 2026 08:24:45 +0000</lastBuildDate>
    <item>
      <title>Margaret Hamilton, computing pioneer who led software development for the Apollo program, dies at 90 | MIT News | Massachusetts Institute of Technology</title>
      <link>https://news.mit.edu/2026/margaret-hamilton-computing-pioneer-dies-1007</link>
      <description>Over two decades at MIT, Hamilton forged new paths in computer science and engineering. Her groundbreaking work included leading the team that programmed the first computers that took humans to the moon.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #compsci #history #mit #nasa&lt;/p&gt;</description>
      <pubDate>Wed, 07 Oct 2026 22:04:01 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:38799</guid>
      <category>compsci</category>
      <category>history</category>
      <category>mit</category>
      <category>nasa</category>
      <enclosure url="https://links.lmorchard.com/static/4b5537308716f1d5fdaf56e430c550fc.jpg" type="image/jpeg"></enclosure>
    </item>
    <item>
      <title>davidbau.com Does Computer Science Still Exist?</title>
      <link>https://davidbau.com/archives/2026/03/20/does_computer_science_still_exist.html</link>
      <description>But my NetHack experience suggests something different. The skills that matter at scale are somehow still about programming, but they are not coding skills. They are: deciding what to build. Figuring out what to test and how to know if the tests are honest. Building tools that make invisible things visible. Managing coordination across agents. Knowing when a metric is a figleaf. Recognizing where the real complexity lives in a system, and routing attention there instead of everywhere else.&#xA;&#xA;These are the conceptual skills that have always been underneath large-scale programming. They are the hard part that the mechanical craft obscured. The reality is that CS has never really been about writing code. Underneath coding is critical thinking about algorithms, engineering principles, analytical methods. It is the science of managing complexity, and code is just the medium we manage it in. In the era of AI code generation, the field does not die. It transforms.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #ai #career #codegen #compsci #llms&lt;/p&gt;</description>
      <pubDate>Mon, 23 Mar 2026 17:02:30 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:38420</guid>
      <category>ai</category>
      <category>career</category>
      <category>codegen</category>
      <category>compsci</category>
      <category>llms</category>
    </item>
    <item>
      <title>LLMs Can Get &#34;Brain Rot&#34;!</title>
      <link>https://llm-brain-rot.github.io/</link>
      <description>We propose and test the LLM Brain Rot Hypothesis: continual exposure to junk web text induces lasting cognitive decline in large language models (LLMs). To causally isolate data quality, we run controlled experiments on real Twitter/X corpora, constructing junk and reversely controlled datasets via two orthogonal operationalizations: M1 (engagement degree) and M2 (semantic quality), with matched token scale and training operations across conditions.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #ai #compsci #genai #llms&lt;/p&gt;</description>
      <pubDate>Sat, 25 Oct 2025 19:12:32 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:37864</guid>
      <category>ai</category>
      <category>compsci</category>
      <category>genai</category>
      <category>llms</category>
    </item>
    <item>
      <title>Phrase origin: Why do we &#34;call&#34; functions? – Arthur O&#39;Dwyer – Stuff mostly about C++</title>
      <link>https://quuxplusone.github.io/blog/2025/04/04/etymology-of-call/</link>
      <description>On StackExchange, someone asks why programmers talk about “calling” a function. Several possible allusions spring to mind:&#xD;&#xA;&#xD;&#xA;    Calling a function is like calling on a friend — we go, we stay a while, we come back.&#xD;&#xA;    Calling a function is like calling for a servant — a summoning to perform a task.&#xD;&#xA;    Calling a function is like making a phone call — we ask a question and get an answer from outside ourselves.&#xD;&#xA;&#xD;&#xA;The true answer seems to be the middle one — “calling” as in “calling up, summoning” — but indirectly, originating in the notion of “calling for” a subroutine out of a library of subroutines in the same way that we’d “call for” a book out of a closed-stack library of books.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #compsci #history #programming&lt;/p&gt;</description>
      <pubDate>Thu, 10 Jul 2025 02:58:49 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:29455</guid>
      <category>compsci</category>
      <category>history</category>
      <category>programming</category>
    </item>
    <item>
      <title>Between the Booms: AI in Winter – Communications of the ACM</title>
      <link>https://cacm.acm.org/opinion/between-the-booms-ai-in-winter/</link>
      <description>After people stopped caring, artificial intelligence got more interesting.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #ai #compsci #genai #ml&lt;/p&gt;</description>
      <pubDate>Wed, 27 Nov 2024 19:06:53 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:29814</guid>
      <category>ai</category>
      <category>compsci</category>
      <category>genai</category>
      <category>ml</category>
    </item>
    <item>
      <title>I don&#39;t have time to learn React - Keith Cirkel</title>
      <link>https://www.keithcirkel.co.uk/i-dont-have-time-to-learn-react/</link>
      <description>When I mentor early career developers and they ask me what they should learn, I can&#39;t say React, they don&#39;t have time. I mean sure, pick up enough React to land you the inevitable job doing it, but it&#39;s not going to level up your career. Anyone with $5,000-$10,000 can make their way through a bootcamp and scrape their way through an interview, but it&#39;s a competitive market and it&#39;s usually quite evident when your interviewing a bootcamp candidate. Stand out by picking up some more fundamentals&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #compsci #react #web #webdev&lt;/p&gt;</description>
      <pubDate>Mon, 25 Nov 2024 18:51:59 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:29829</guid>
      <category>compsci</category>
      <category>react</category>
      <category>web</category>
      <category>webdev</category>
    </item>
    <item>
      <title>Big-O Algorithm Complexity Cheat Sheet (Know Thy Complexities!) @ericdrowell</title>
      <link>https://www.bigocheatsheet.com/</link>
      <description>Hi there!  This webpage covers the space and time Big-O complexities of common algorithms used in Computer Science.  When preparing for technical interviews in the past, I found myself spending hours crawling the internet putting together the best, average, and worst case complexities for search and sorting algorithms so that I wouldn&#39;t be stumped when asked about them.  Over the last few years, I&#39;ve interviewed at several Silicon Valley startups, and also some bigger companies, like Google, Facebook, Yahoo, LinkedIn, and Uber, and each time that I prepared for an interview, I thought to myself &#34;Why hasn&#39;t someone created a nice Big-O cheat sheet?&#34;.  So, to save all of you fine folks a ton of time, I went ahead and created one.  Enjoy! - Eric&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #bigo #compsci&lt;/p&gt;</description>
      <pubDate>Tue, 19 Nov 2024 22:36:55 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:29849</guid>
      <category>bigo</category>
      <category>compsci</category>
    </item>
    <item>
      <title>parnas-1979.pdf</title>
      <link>https://courses.cs.washington.edu/courses/cse503/08wi/parnas-1979.pdf</link>
      <description>Designing software to be extensible and easily contracted is&#xD;&#xA;discussed as a special case of design for change. A number of ways that&#xD;&#xA;extension and contraction problems manifest themselves in current&#xD;&#xA;software are explained.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #compsci #software&lt;/p&gt;</description>
      <pubDate>Thu, 31 Oct 2024 20:54:11 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:29936</guid>
      <category>compsci</category>
      <category>software</category>
    </item>
    <item>
      <title>Before You Can Have Smalltalk, You Must First Defeat Capitalism. — Matthew Gaudet</title>
      <link>https://www.mgaudet.ca/blog/2024/10/28/before-you-can-have-smalltalk-you-must-first-defeat-capitalism</link>
      <description>The title of this blog post is at least a little sarcastic, but I think is an honest to goodness truth: If you want to build a future that involves beautiful systems like Smalltalk, you must first rebuild the economic environment wherein it could be built. Wherein it could succeed! These systems idealized in lamentations at SPLASH all seem to me to be products of economic surplus combined with the right people. We need an economy that has surpluses around for people to do explorations.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #compsci #economy #programming #smalltalk&lt;/p&gt;</description>
      <pubDate>Tue, 29 Oct 2024 06:09:51 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:29942</guid>
      <category>compsci</category>
      <category>economy</category>
      <category>programming</category>
      <category>smalltalk</category>
    </item>
    <item>
      <title>AI Winter Is Coming</title>
      <link>https://leehanchung.github.io/blogs/2024/09/20/ai-winter/</link>
      <description>This is how we’re headed for another AI winter, just as we saw with the fall of data science, crypto, and the modern data stack. And that’s actually a good thing. The promoters will hop onto the next trendy buzzword, while the real producers will keep moving forward, building a more capable future for AI.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #ai #compsci #ml&lt;/p&gt;</description>
      <pubDate>Sat, 12 Oct 2024 02:48:46 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:30438</guid>
      <category>ai</category>
      <category>compsci</category>
      <category>ml</category>
    </item>
    <item>
      <title>a blog by biggiemac42</title>
      <link>https://btm.qva.mybluehost.me/building-arbitrary-life-patterns-in-15-gliders/</link>
      <description>Select any pattern that can be built in Life – for example, the Waterbear. Begin with a small number of gliders (now 15) in an otherwise empty Game of Life universe. After enough time goes by, those gliders need to build that pattern. No extra leftover debris, no stray scaffolding, just a pure synthesis of whatever you chose.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #compsci #conway #imported:pinboard #life #math&lt;/p&gt;</description>
      <pubDate>Sat, 10 Jun 2023 19:19:05 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:30607</guid>
      <category>compsci</category>
      <category>conway</category>
      <category>imported:pinboard</category>
      <category>life</category>
      <category>math</category>
    </item>
    <item>
      <title>a blog by biggiemac42</title>
      <link>https://btm.qva.mybluehost.me/building-arbitrary-life-patterns-in-15-gliders</link>
      <description>Select any pattern that can be built in Life – for example, the Waterbear. Begin with a small number of gliders (now 15) in an otherwise empty Game of Life universe. After enough time goes by, those gliders need to build that pattern. No extra leftover debris, no stray scaffolding, just a pure synthesis of whatever you chose.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #compsci #conway #life #math&lt;/p&gt;</description>
      <pubDate>Sat, 10 Jun 2023 19:19:05 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:29348</guid>
      <category>compsci</category>
      <category>conway</category>
      <category>life</category>
      <category>math</category>
    </item>
    <item>
      <title>Building ucblogo (Berkeley Logo) on the Raspberry Pi 400 | Dan Malec&#39;s Blog</title>
      <link>https://danmalec.com/2020/11/30/building-ucblogo-berkeley-logo-on-the-raspberry-pi-400/</link>
      <description>The following are my notes on using the two together – building and installing ucblogo (Berkeley Logo) on the Raspberry Pi 400. Hopefully, others will take this journey too.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #compsci #imported:pinboard #logo #raspi&lt;/p&gt;</description>
      <pubDate>Sun, 26 Mar 2023 18:28:03 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:30631</guid>
      <category>compsci</category>
      <category>imported:pinboard</category>
      <category>logo</category>
      <category>raspi</category>
    </item>
    <item>
      <title>Building ucblogo (Berkeley Logo) on the Raspberry Pi 400 | Dan Malec&#39;s Blog</title>
      <link>https://danmalec.com/2020/11/30/building-ucblogo-berkeley-logo-on-the-raspberry-pi-400</link>
      <description>The following are my notes on using the two together – building and installing ucblogo (Berkeley Logo) on the Raspberry Pi 400. Hopefully, others will take this journey too.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #compsci #logo #raspi&lt;/p&gt;</description>
      <pubDate>Sun, 26 Mar 2023 18:28:03 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:29288</guid>
      <category>compsci</category>
      <category>logo</category>
      <category>raspi</category>
    </item>
    <item>
      <title>Programmer as wizard, programmer as engineer</title>
      <link>https://www.tedinski.com/2018/03/20/wizarding-vs-engineering.html</link>
      <description>Are we just trying to solve a problem quickly, or are we trying to build a robust solution? I got into programming at least in part because it seemed like the closest thing to magic that really exists. So I’m going to call these two distinct styles wizarding and engineering.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #compsci #dev #devops #imported:pinboard #programming&lt;/p&gt;</description>
      <pubDate>Fri, 04 Jan 2019 19:32:33 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:27998</guid>
      <category>compsci</category>
      <category>dev</category>
      <category>devops</category>
      <category>imported:pinboard</category>
      <category>programming</category>
    </item>
  </channel>
</rss>
