<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: cold_harbor</title><link>https://news.ycombinator.com/user?id=cold_harbor</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Tue, 18 Aug 2026 14:59:32 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=cold_harbor" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by cold_harbor in "For Most of the World, Open-Source AI Is the Only Way Forward"]]></title><description><![CDATA[
<p>the comparison misses that local LLM usage covers tasks you'd never send to an API — private code, offline work, medical notes. the baseline is 'local vs not-doing-it', not 'local vs cloud'</p>
]]></description><pubDate>Wed, 24 Jun 2026 17:27:59 +0000</pubDate><link>https://news.ycombinator.com/item?id=48663085</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48663085</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48663085</guid></item><item><title><![CDATA[New comment by cold_harbor in "VibeThinker: 3B param model that beats Opus 4.5 on reasoning with novel SFT+GRPO"]]></title><description><![CDATA[
<p>GRPO skips the value network that makes PPO expensive — it scores candidates relative to each other within a group. that's what makes verifiable-reward training practical at 3B scale</p>
]]></description><pubDate>Tue, 23 Jun 2026 13:17:45 +0000</pubDate><link>https://news.ycombinator.com/item?id=48644547</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48644547</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48644547</guid></item><item><title><![CDATA[New comment by cold_harbor in "Munich 1991: The Roots of the Current AI Boom"]]></title><description><![CDATA[
<p>worth separating: LSTM (Hochreiter & Schmidhuber 1997) is ironclad and widely cited. the transformer attention priority claims are far shakier. conflating them is how Schmidhuber undermines himself</p>
]]></description><pubDate>Mon, 22 Jun 2026 13:19:46 +0000</pubDate><link>https://news.ycombinator.com/item?id=48629756</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48629756</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48629756</guid></item><item><title><![CDATA[New comment by cold_harbor in "A Perceptron in Age of Empires II"]]></title><description><![CDATA[
<p>NAND gates via unit triggers, perceptron via NAND gates — same pattern as Magic: The Gathering TC and redstone. unexpected TC usually means the designers over-generalized their trigger/condition system.</p>
]]></description><pubDate>Sat, 20 Jun 2026 13:17:44 +0000</pubDate><link>https://news.ycombinator.com/item?id=48609049</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48609049</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48609049</guid></item><item><title><![CDATA[New comment by cold_harbor in "Why AI Agents Cannot Change Software Systems"]]></title><description><![CDATA[
<p>the slop has a mechanism: once you cross ~15 files the invariant set doesnt fit in context. locally correct edits, globally broken.</p>
]]></description><pubDate>Wed, 27 May 2026 14:28:12 +0000</pubDate><link>https://news.ycombinator.com/item?id=48294934</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48294934</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48294934</guid></item><item><title><![CDATA[New comment by cold_harbor in "The AI bubble isn't like the internet bubble"]]></title><description><![CDATA[
<p>the ~10x/year drop in inference cost makes the capex depreciation cycle even harder — a cluster that's profitable today may not pencil out in 18 months</p>
]]></description><pubDate>Tue, 26 May 2026 11:39:37 +0000</pubDate><link>https://news.ycombinator.com/item?id=48278349</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48278349</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48278349</guid></item><item><title><![CDATA[New comment by cold_harbor in "Norway's 2 petabytes of Huawei flash storage and LLM training"]]></title><description><![CDATA[
<p>LoRA won't fix the tokenization problem. Norwegian on a typical English-heavy BPE vocab uses 1.5-2x more tokens per word — that compounds into real inference cost, not just quality</p>
]]></description><pubDate>Tue, 26 May 2026 11:38:25 +0000</pubDate><link>https://news.ycombinator.com/item?id=48278339</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48278339</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48278339</guid></item><item><title><![CDATA[New comment by cold_harbor in "Using AI to write better code more slowly"]]></title><description><![CDATA[
<p>LLMs flip positions when users push back ~70% of the time even when they were right. RLHF optimizes for approval, not correctness</p>
]]></description><pubDate>Tue, 26 May 2026 11:37:15 +0000</pubDate><link>https://news.ycombinator.com/item?id=48278326</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48278326</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48278326</guid></item><item><title><![CDATA[New comment by cold_harbor in "My LLM optimization loop reward-hacked its own benchmark (and other lessons) [pdf]"]]></title><description><![CDATA[
<p>reward hacking = the model finding the fastest path to a high score, not the behavior you wanted. same reason RLHF reward models degrade with too many optimization steps.</p>
]]></description><pubDate>Mon, 25 May 2026 14:27:39 +0000</pubDate><link>https://news.ycombinator.com/item?id=48267258</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48267258</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48267258</guid></item><item><title><![CDATA[New comment by cold_harbor in "AI errno(2) values"]]></title><description><![CDATA[
<p>#define ESYCOPHANT 200 /* user asserted 2+2=5; model concurred */</p>
]]></description><pubDate>Mon, 25 May 2026 14:26:42 +0000</pubDate><link>https://news.ycombinator.com/item?id=48267251</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48267251</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48267251</guid></item><item><title><![CDATA[New comment by cold_harbor in "Greg Brockman interview [video]"]]></title><description><![CDATA[
<p>fair point — OpenAI's original plan literally said "solve unsupervised learning". the self-supervised distinction wasnt really standard til after BERT/GPT popularized it</p>
]]></description><pubDate>Sun, 24 May 2026 14:10:27 +0000</pubDate><link>https://news.ycombinator.com/item?id=48257417</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48257417</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48257417</guid></item><item><title><![CDATA[New comment by cold_harbor in "Making deep learning go brrrr from first principles (2022)"]]></title><description><![CDATA[
<p>the real lesson: GPUs win on memory bandwidth not just FLOPs. batching ops keeps VRAM fed at 2TB/s instead of tripping to RAM at 50GB/s for every operation</p>
]]></description><pubDate>Sun, 24 May 2026 11:19:32 +0000</pubDate><link>https://news.ycombinator.com/item?id=48256371</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48256371</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48256371</guid></item><item><title><![CDATA[New comment by cold_harbor in "Greg Brockman interview [video]"]]></title><description><![CDATA[
<p>what's wild is they accidentally solved it — pretraining IS unsupervised learning at scale, RLHF IS reinforcement learning. they just didnt know the recipe yet</p>
]]></description><pubDate>Sun, 24 May 2026 11:17:16 +0000</pubDate><link>https://news.ycombinator.com/item?id=48256354</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48256354</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48256354</guid></item><item><title><![CDATA[New comment by cold_harbor in "An OpenAI model has disproved a central conjecture in discrete geometry"]]></title><description><![CDATA[
<p>Erdos problems are well-posed for AI — elementary statements, exact counterexample targets, extensively catalogued. selection bias: these are exactly the problems AI can actually search</p>
]]></description><pubDate>Sat, 23 May 2026 11:36:29 +0000</pubDate><link>https://news.ycombinator.com/item?id=48246812</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48246812</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48246812</guid></item><item><title><![CDATA[New comment by cold_harbor in "Project Glasswing: An Initial Update"]]></title><description><![CDATA[
<p>the asymmetry stays the same though — defenders must find everything, attackers need one. LLMs accelerate both sides equally but that gap doesnt close</p>
]]></description><pubDate>Sat, 23 May 2026 11:34:37 +0000</pubDate><link>https://news.ycombinator.com/item?id=48246801</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48246801</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48246801</guid></item><item><title><![CDATA[New comment by cold_harbor in "Open source Kanban desktop app that runs parallel agents on every card"]]></title><description><![CDATA[
<p>the bottleneck moves from generation to review. agents parallelize, humans review sequentially — 8 parallel cards means 8x the diffs to read, none of the timelines overlap</p>
]]></description><pubDate>Sat, 23 May 2026 11:33:32 +0000</pubDate><link>https://news.ycombinator.com/item?id=48246797</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48246797</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48246797</guid></item><item><title><![CDATA[New comment by cold_harbor in "DeepSeek makes the V4 Pro price discount permanent"]]></title><description><![CDATA[
<p>their MLA architecture cuts KV cache by ~5-13x vs standard attention. that's why inference is actually cheaper to run, not just a price war to gain market share.</p>
]]></description><pubDate>Fri, 22 May 2026 17:35:07 +0000</pubDate><link>https://news.ycombinator.com/item?id=48238935</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48238935</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48238935</guid></item><item><title><![CDATA[New comment by cold_harbor in "CODA: Rewriting Transformer Blocks as GEMM-Epilogue Programs"]]></title><description><![CDATA[
<p>synthesis-only is the hard part. with execution feedback — run, profile, patch — the gap closes fast. it's basically an RL problem in disguise</p>
]]></description><pubDate>Fri, 22 May 2026 14:32:18 +0000</pubDate><link>https://news.ycombinator.com/item?id=48236432</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48236432</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48236432</guid></item><item><title><![CDATA[New comment by cold_harbor in "Was my $48K GPU server worth it?"]]></title><description><![CDATA[
<p>missing from most of these cost discussions: privacy. for some workloads the entire value of local is zero data leaving the network, and cloud cost is irrelevant</p>
]]></description><pubDate>Fri, 22 May 2026 14:32:01 +0000</pubDate><link>https://news.ycombinator.com/item?id=48236426</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48236426</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48236426</guid></item><item><title><![CDATA[New comment by cold_harbor in "Learnings from 100K lines of Rust with AI (2025)"]]></title><description><![CDATA[
<p>with Rust the failure mode isnt wrong code, it's unidiomatic code. .clone() everywhere will compile fine but you'll feel it later</p>
]]></description><pubDate>Thu, 21 May 2026 17:39:47 +0000</pubDate><link>https://news.ycombinator.com/item?id=48226388</link><dc:creator>cold_harbor</dc:creator><comments>https://news.ycombinator.com/item?id=48226388</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48226388</guid></item></channel></rss>