<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hacker News: gkcnlr</title><link>https://news.ycombinator.com/user?id=gkcnlr</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Tue, 13 Oct 2026 08:37:56 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=gkcnlr" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by gkcnlr in "The RAM shortage is bringing back DDR4"]]></title><description><![CDATA[
<p>Of course, when we talk about utilizing AI as an efficient tooling, it is well expected to see the very outcomes you desire. But the point here is the disconnect between the perceived productivity gains and their corresponding measuring metrics. Remember the Goodhart's Law[1]? It becomes fairly unreliable when you try to measure productivity by a set of standards instead of actually producing productivity. When it comes to future about this issue, I'd hope to see the progress actually happening in open source, decentralized AI instead of the current way of using it.<p>[1]: <a href="https://en.wikipedia.org/wiki/Goodhart%27s_law" rel="nofollow">https://en.wikipedia.org/wiki/Goodhart%27s_law</a></p>
]]></description><pubDate>Sun, 11 Oct 2026 15:53:53 +0000</pubDate><link>https://news.ycombinator.com/item?id=50044597</link><dc:creator>gkcnlr</dc:creator><comments>https://news.ycombinator.com/item?id=50044597</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=50044597</guid></item><item><title><![CDATA[New comment by gkcnlr in "The RAM shortage is bringing back DDR4"]]></title><description><![CDATA[
<p>How are all these related news regarding silicon shortages surprising at all? It was well predicted that while 2023 chip turmoil[1] was happening, big AI aimed to secure almost all of the demand[2] intended for consumer markets regarding RAM chips so as to win the AI race going forward from that date. They cannibalized almost the entirety of the supply chain, so that they could sell you the incredibly subsidized AIaaS[3] with still considerably higher inference and astronomically higher training process without as of late 2026, failing to achieve any meaningful productivity at all[4]. The serfs now will be happy to own their decade old DDR4 architecture.<p>[1]: <a href="https://www.electronicdesign.com/technologies/embedded/article/21257375/objective-analysis-understanding-the-2023-chip-market-collapse" rel="nofollow">https://www.electronicdesign.com/technologies/embedded/artic...</a><p>[2]: <a href="https://www.reuters.com/technology/nvidia-supplier-sk-hynix-says-hbm-chips-almost-sold-out-2025-2024-05-02/" rel="nofollow">https://www.reuters.com/technology/nvidia-supplier-sk-hynix-...</a><p>[3]: <a href="https://arxiv.org/abs/2606.24616" rel="nofollow">https://arxiv.org/abs/2606.24616</a><p>[4]: <a href="https://www.apollo.com/insights-news/insights/daily-spark/No-signs-of-AI-in-the-productivity-data" rel="nofollow">https://www.apollo.com/insights-news/insights/daily-spark/No...</a></p>
]]></description><pubDate>Sun, 11 Oct 2026 15:15:06 +0000</pubDate><link>https://news.ycombinator.com/item?id=50044196</link><dc:creator>gkcnlr</dc:creator><comments>https://news.ycombinator.com/item?id=50044196</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=50044196</guid></item><item><title><![CDATA[New comment by gkcnlr in "I am so tired of this bullshit"]]></title><description><![CDATA[
<p>> i f*king love LLMs for generating code<p>> i f*king detest reading LLM-generated material<p>Thats quite a dichotomy right there.</p>
]]></description><pubDate>Thu, 01 Oct 2026 18:37:38 +0000</pubDate><link>https://news.ycombinator.com/item?id=49925405</link><dc:creator>gkcnlr</dc:creator><comments>https://news.ycombinator.com/item?id=49925405</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49925405</guid></item><item><title><![CDATA[New comment by gkcnlr in "How to keep enjoying programming in a world of LLMs"]]></title><description><![CDATA[
<p>People just like to spill out their justifications on how they interact with ai and generally try to be agreeable in their comfort zones until they get bamboozled by actual market demands. No competitive structure is willing to pay more (to you) that could be replaced by lower cost means to maximize profits. This is basic economy 101. This article seems a huge cope to me IMHO regarding the advice it gives. Programming is mostly solved, although in a very anti-humane way IMHO. Hobbyist means could justify it in the remaining time...<p>I just pray open weight wins at the end and people actually utilize their ai and own their ai.</p>
]]></description><pubDate>Sat, 26 Sep 2026 21:24:32 +0000</pubDate><link>https://news.ycombinator.com/item?id=49860681</link><dc:creator>gkcnlr</dc:creator><comments>https://news.ycombinator.com/item?id=49860681</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49860681</guid></item><item><title><![CDATA[New comment by gkcnlr in "Anthropic researcher says more than 10% chance AI "could kill all humans""]]></title><description><![CDATA[
<p>Two more weeks, then it'll happen.</p>
]]></description><pubDate>Wed, 09 Sep 2026 15:48:25 +0000</pubDate><link>https://news.ycombinator.com/item?id=49628506</link><dc:creator>gkcnlr</dc:creator><comments>https://news.ycombinator.com/item?id=49628506</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49628506</guid></item><item><title><![CDATA[New comment by gkcnlr in "Maybe you should learn something"]]></title><description><![CDATA[
<p>Learning process must be accompanied with enough space for an individual to realistically challenge himself to actually acquire that knowledge with foreseeable success of doing it. A person must believe s/he can really learn something. But in this status quo of AI hypeism (believing that knowing refined set of know-hows would be enough) people gradually begin losing that optimistic "a priori" belief to learn things.<p>But another side effect of this process is if people stop believing in the accrual of the knowledge which will lead them to nowhere (use cases for those information becoming irrelevant by the time you start using it), justifying this mentally exhausting practice becomes really hard. And I don't mean this on learning static information but also on how to define and build a meta-cognitive framework to systemically learn things.<p>I don't quite get the "lifelong learning" approach, since lifelong learning must usually be accompanied with organic evolution of the information space. Employers wont pay you because you are a lifelong learner, they'll pay you to actually fix a problem you provide a solution for. And that solution isn't guaranteed by the knowledge you possess and doesn't usually qualify the marginal cost of being a lifelong learner.<p>One could brain storm on these issues by critiquing the premise of this book: <a href="https://www.amazon.com/100-Year-Life-Living-Working-Longevity/dp/1472930150" rel="nofollow">https://www.amazon.com/100-Year-Life-Living-Working-Longevit...</a></p>
]]></description><pubDate>Sat, 04 Jul 2026 16:51:58 +0000</pubDate><link>https://news.ycombinator.com/item?id=48786846</link><dc:creator>gkcnlr</dc:creator><comments>https://news.ycombinator.com/item?id=48786846</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48786846</guid></item><item><title><![CDATA[New comment by gkcnlr in "Local AI needs to be the norm"]]></title><description><![CDATA[
<p>It seems like everybody is focused on "LLM"s, a.k.a Large Language Models. One interesting addition to that is fine-tuned- small parameter, distilled, context-dependent small language models that:<p>1- Do a particular task with great capability (due to its constrained, limited scope)
2- Do it in such a way, it integrates gracefully in your workflow without ever requiring you to know you are using an LM.<p>There is a difference between outsourcing your workflow to AI and actually utilizing it.<p>Check this: <a href="https://www.distillabs.ai/blog/we-benchmarked-12-small-language-models-across-8-tasks-to-find-the-best-base-model-for-fine-tuning/" rel="nofollow">https://www.distillabs.ai/blog/we-benchmarked-12-small-langu...</a></p>
]]></description><pubDate>Mon, 11 May 2026 03:45:15 +0000</pubDate><link>https://news.ycombinator.com/item?id=48090863</link><dc:creator>gkcnlr</dc:creator><comments>https://news.ycombinator.com/item?id=48090863</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48090863</guid></item><item><title><![CDATA[New comment by gkcnlr in "Windows Notepad App Remote Code Execution Vulnerability"]]></title><description><![CDATA[
<p>Search for this: "Revenue, classified by significant product and service offerings"</p>
]]></description><pubDate>Wed, 11 Feb 2026 16:51:31 +0000</pubDate><link>https://news.ycombinator.com/item?id=46977356</link><dc:creator>gkcnlr</dc:creator><comments>https://news.ycombinator.com/item?id=46977356</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=46977356</guid></item><item><title><![CDATA[New comment by gkcnlr in "Windows Notepad App Remote Code Execution Vulnerability"]]></title><description><![CDATA[
<p>By looking at their 2025 shareholder report (Look for the part below "NOTE 18"), Windows is only at the 5th place in terms of revenue source, even below the LinkedIn:<p><a href="https://www.microsoft.com/investor/reports/ar25/index.html#" rel="nofollow">https://www.microsoft.com/investor/reports/ar25/index.html#</a><p>I can only think that they do not even care about Windows anymore, let alone Notepad...</p>
]]></description><pubDate>Wed, 11 Feb 2026 15:50:48 +0000</pubDate><link>https://news.ycombinator.com/item?id=46976458</link><dc:creator>gkcnlr</dc:creator><comments>https://news.ycombinator.com/item?id=46976458</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=46976458</guid></item><item><title><![CDATA[New comment by gkcnlr in "Stop generating, start thinking"]]></title><description><![CDATA[
<p>As long as AI (genAI, LLMs, whatever you call it describe the current tech) is perceived not as a "bicycle of the mind" and a tool to utilize 'your' skills to a next phase but as a commodity to be exploited by giant corporations whose existence is based on maximizing profits regardless of virtue or dignity (a basic set of ethics to, for example, not to burn books after you scan it feed your LLM like Anthropic), it is really hard to justify the current state of AI.<p>Once you understand the sole winner in this hype is the one who'll be brutally scraping every bit of data, whether it's real-time or static and then refining it to give it back to you without your involvement in the process (a.k.a, learning) you'll come to understand that the current AI by nature is hugely unfavorable to mental progression...</p>
]]></description><pubDate>Mon, 09 Feb 2026 04:45:22 +0000</pubDate><link>https://news.ycombinator.com/item?id=46941665</link><dc:creator>gkcnlr</dc:creator><comments>https://news.ycombinator.com/item?id=46941665</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=46941665</guid></item><item><title><![CDATA[New comment by gkcnlr in "The age of average (2023)"]]></title><description><![CDATA[
<p>Current economic supply/demand balance as well as philosophical principles are so utterly deranged, people lean toward what could maximize their profit. If this is achieved through conformism & doing what you're accustomed to, no one will try to truly innovate and prefer staying in their comfort zone.</p>
]]></description><pubDate>Fri, 13 Dec 2024 09:42:40 +0000</pubDate><link>https://news.ycombinator.com/item?id=42407251</link><dc:creator>gkcnlr</dc:creator><comments>https://news.ycombinator.com/item?id=42407251</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=42407251</guid></item></channel></rss>