<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: rahen</title><link>https://news.ycombinator.com/user?id=rahen</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Thu, 29 Oct 2026 20:04:42 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=rahen" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by rahen in "Mistral Large 4"]]></title><description><![CDATA[
<p>The benchmarks against Opus 5.5 and GPT-6.1 Sol look pretty good for 3D generation:
<a href="https://x.com/atomic_chat_hq/status/2107516529608700383" rel="nofollow">https://x.com/atomic_chat_hq/status/2107516529608700383</a></p>
]]></description><pubDate>Tue, 06 Oct 2026 20:19:53 +0000</pubDate><link>https://news.ycombinator.com/item?id=49983523</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49983523</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49983523</guid></item><item><title><![CDATA[New comment by rahen in "Mistral Large 4"]]></title><description><![CDATA[
<p>It's in the announcement: "ML4 was trained from scratch on 3,800 NVIDIA Grace Blackwell GPUs in Mistral’s own datacenters in Europe".<p><a href="https://mistral.ai/news/mistral-large-4/" rel="nofollow">https://mistral.ai/news/mistral-large-4/</a></p>
]]></description><pubDate>Tue, 06 Oct 2026 15:13:55 +0000</pubDate><link>https://news.ycombinator.com/item?id=49979745</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49979745</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49979745</guid></item><item><title><![CDATA[New comment by rahen in "Mistral Large 4"]]></title><description><![CDATA[
<p>Give them time. ML 4.0 was just pretrained. Mistral will certainly use it as the base for distillation and RL for smaller, better, more efficient iterations, just as the competition does.</p>
]]></description><pubDate>Tue, 06 Oct 2026 14:58:25 +0000</pubDate><link>https://news.ycombinator.com/item?id=49979490</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49979490</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49979490</guid></item><item><title><![CDATA[New comment by rahen in "Mistral Large 4"]]></title><description><![CDATA[
<p>I’d rather have one European AI lab like Mistral, with the financial firepower and compute to pretrain its own large models, than 20 weak labs that fine-tune Chinese models.<p>AI needs big bucks, and Mistral is Europe’s Anthropic.</p>
]]></description><pubDate>Tue, 06 Oct 2026 14:00:36 +0000</pubDate><link>https://news.ycombinator.com/item?id=49978634</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49978634</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49978634</guid></item><item><title><![CDATA[New comment by rahen in "Mistral Large 4"]]></title><description><![CDATA[
<p>Mistral is the only major non-Chinese contender in the AI race releasing open-weight models. I’d rather trust that French weights haven’t been backdoored than Chinese ones. Heck, I’d even trust Mistral more than Anthropic for sensitive work.</p>
]]></description><pubDate>Tue, 06 Oct 2026 13:41:09 +0000</pubDate><link>https://news.ycombinator.com/item?id=49978337</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49978337</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49978337</guid></item><item><title><![CDATA[New comment by rahen in "Zig’s Io.Threaded is neat"]]></title><description><![CDATA[
<p>You asked if there was "tangible benefit to end user or developer using ai assisted development". My answer is no, it can be done but has no benefits for this use case. Use Rust here, because its compiler acts as an AI safety net.<p>Being a code artisan is not gatekeeping. It means if you're used to being close to the metal and sometimes know better than the compiler, Zig is for you. If you're not, use Rust.</p>
]]></description><pubDate>Sat, 22 Aug 2026 08:40:35 +0000</pubDate><link>https://news.ycombinator.com/item?id=49397816</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49397816</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49397816</guid></item><item><title><![CDATA[New comment by rahen in "Zig’s Io.Threaded is neat"]]></title><description><![CDATA[
<p>Use Rust if you're not writing code yourself.<p>The borrow checker will catch all kinds of bugs that AI-generated code will happily compile in Zig but will blow up as UB at runtime.<p>Zig's value prop is different and closer to a modern C: it fits in your head and maps fairly closely to assembly. There is no hidden control flow or hidden allocations, so you can tweak performance at a very low level. You're the pilot, not the compiler.<p>Rust trades the low-level clarity for compiler-enforced safety. If you're not a code artisan or don't care about being one, then <i>please</i> use Rust.</p>
]]></description><pubDate>Sat, 22 Aug 2026 06:37:54 +0000</pubDate><link>https://news.ycombinator.com/item?id=49397195</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49397195</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49397195</guid></item><item><title><![CDATA[New comment by rahen in "Jolt: Clojure compiler implemented with Chez Scheme"]]></title><description><![CDATA[
<p>It definitely is vibe-coded, but yogthos is a competent programmer who has been working on public Clojure projects and repos since 2009, and has maintained a large Clojure framework since well before LLMs were a thing.<p>I don't think "2k commits in 2 months" is enough to dismiss as slop when it's being developed by a competent Clojure dev.</p>
]]></description><pubDate>Tue, 11 Aug 2026 21:43:30 +0000</pubDate><link>https://news.ycombinator.com/item?id=49264912</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49264912</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49264912</guid></item><item><title><![CDATA[New comment by rahen in "Jolt: Clojure compiler implemented with Chez Scheme"]]></title><description><![CDATA[
<p>Not slop, though. The main developer is Dmitri Sotnikov (yogthos), who's been around in the Clojure scene for a long time and knows what he's doing.<p>However, you're right to point out that the development is moving really fast.<p>I'm building a Clojure compiler for machine learning (<a href="https://github.com/sheaf-lang/sheaf" rel="nofollow">https://github.com/sheaf-lang/sheaf</a>), and after 9 months, it's still very far from being production-ready.</p>
]]></description><pubDate>Tue, 11 Aug 2026 21:22:29 +0000</pubDate><link>https://news.ycombinator.com/item?id=49264684</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49264684</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49264684</guid></item><item><title><![CDATA[New comment by rahen in "Building a Rust Inference Engine That Matches Llama.cpp"]]></title><description><![CDATA[
<p>Four day old repo with 92K lines added per day, okay...<p>There is basically no evidence of human competence in this repo. This is yet another "rewrite in Rust with Claude" project that brings nothing to the table, but devalues expert work by mimicking competence without the expertise.</p>
]]></description><pubDate>Sat, 08 Aug 2026 18:25:24 +0000</pubDate><link>https://news.ycombinator.com/item?id=49224448</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49224448</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49224448</guid></item><item><title><![CDATA[New comment by rahen in "Voyager 1 FDS Computer Emulator"]]></title><description><![CDATA[
<p>This was common back then. The PDP-8 had eight primary instructions, although one of them was multi-purpose. This helped keep the hardware simple when we didn't have ICs.<p>RISC isn't about having a small ISA but about a regular, orthogonal instruction set.</p>
]]></description><pubDate>Sat, 08 Aug 2026 17:00:49 +0000</pubDate><link>https://news.ycombinator.com/item?id=49223597</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49223597</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49223597</guid></item><item><title><![CDATA[New comment by rahen in "Voyager 1 FDS Computer Emulator"]]></title><description><![CDATA[
<p>The author has also published a Setun-70 emulator (a Soviet ternary computer rather than a binary one):<p><a href="https://github.com/Zaneham/setun70-emulator" rel="nofollow">https://github.com/Zaneham/setun70-emulator</a></p>
]]></description><pubDate>Sat, 08 Aug 2026 14:52:09 +0000</pubDate><link>https://news.ycombinator.com/item?id=49222396</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49222396</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49222396</guid></item><item><title><![CDATA[Voyager 1 FDS Computer Emulator]]></title><description><![CDATA[
<p>Article URL: <a href="https://zaneham.github.io/voyager-fds-emulator/">https://zaneham.github.io/voyager-fds-emulator/</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=49221679">https://news.ycombinator.com/item?id=49221679</a></p>
<p>Points: 92</p>
<p># Comments: 17</p>
]]></description><pubDate>Sat, 08 Aug 2026 13:28:38 +0000</pubDate><link>https://zaneham.github.io/voyager-fds-emulator/</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49221679</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49221679</guid></item><item><title><![CDATA[The Maxwell Conjecture Is False (GPT 5.6 Sol)]]></title><description><![CDATA[
<p>Article URL: <a href="https://arxiv.org/abs/2607.27197">https://arxiv.org/abs/2607.27197</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=49121868">https://news.ycombinator.com/item?id=49121868</a></p>
<p>Points: 157</p>
<p># Comments: 142</p>
]]></description><pubDate>Fri, 31 Jul 2026 11:37:12 +0000</pubDate><link>https://arxiv.org/abs/2607.27197</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49121868</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49121868</guid></item><item><title><![CDATA[New comment by rahen in "Show HN: A udev implementation in Guile Scheme"]]></title><description><![CDATA[
<p>I was initially surprised because this is not a good use case for Scheme. The current C implementation is clean and efficient, and I'd rather use Scheme to replace some messy Python code with its dependency hell.<p>And then I saw this: "As mentioned above, some code has been automatically translated from C to Scheme, using generative AI. This is not creative work, and as such, the authors of Goodev cannot claim copyright for it."<p>Somehow I wish those tokens would had been more usefully spent on porting code where a sound language could actually make a difference.</p>
]]></description><pubDate>Fri, 31 Jul 2026 10:55:25 +0000</pubDate><link>https://news.ycombinator.com/item?id=49121557</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=49121557</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49121557</guid></item><item><title><![CDATA[New comment by rahen in "All about the IBM 1130 Computing System"]]></title><description><![CDATA[
<p>Not very far off, the IBM 1130 was very much built around its punch-card reader.
I've written a backprop in Fortran IV for the 1130 and while it works, it was tedious.<p>Add ten more years, and the IBM 801 could have been a CPU architecture good enough to scale all the way to the present day without emulation, unlike the 360.</p>
]]></description><pubDate>Wed, 17 Jun 2026 08:43:30 +0000</pubDate><link>https://news.ycombinator.com/item?id=48567542</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=48567542</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48567542</guid></item><item><title><![CDATA[New comment by rahen in "macOS Container Machines"]]></title><description><![CDATA[
<p>What kind of virtualization do you use internally? I assume some kind of LXD fork? OrbStack really feels like a single-node Incus host.</p>
]]></description><pubDate>Wed, 10 Jun 2026 09:39:48 +0000</pubDate><link>https://news.ycombinator.com/item?id=48473819</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=48473819</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48473819</guid></item><item><title><![CDATA[New comment by rahen in "The Smallest Brain You Can Build: A Perceptron in Python"]]></title><description><![CDATA[
<p>The first AI winter was largely triggered by Minsky in a book he published in 1969, which mathematically proved that single-layer perceptrons couldn't solve non-linear problems. Favorite quote: "Our intuitive judgment is that the extension [to multilayer systems] is sterile."<p>Yet we had the computational power to run backpropagation in the 1960s and small Transformers in the 1970s (I'm the author of both):<p><a href="https://github.com/dbrll/Xortran" rel="nofollow">https://github.com/dbrll/Xortran</a> (backprop on IBM 1130, 60s)<p><a href="https://github.com/dbrll/ATTN-11" rel="nofollow">https://github.com/dbrll/ATTN-11</a> (Transformer on PDP-11, 70s)<p>What was missing wasn't the raw processing power, but the ideas and algorithms themselves. Because funding and research were completely discouraged during the AI winter, neural networks research was left dormant and we lost two decades.</p>
]]></description><pubDate>Mon, 08 Jun 2026 14:27:24 +0000</pubDate><link>https://news.ycombinator.com/item?id=48445878</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=48445878</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48445878</guid></item><item><title><![CDATA[New comment by rahen in "The Smallest Brain You Can Build: A Perceptron in Python"]]></title><description><![CDATA[
<p>In the early days of machine learning (before the first AI winter), networks like this were often implemented and trained in hardware: <a href="https://en.wikipedia.org/wiki/ADALINE" rel="nofollow">https://en.wikipedia.org/wiki/ADALINE</a><p>That was the first thing that came to mind when I read "the smallest brain you can <i>build</i>". Nowadays, that "small brain" would likely be built on a breadboard using op-amps instead.</p>
]]></description><pubDate>Mon, 08 Jun 2026 06:31:31 +0000</pubDate><link>https://news.ycombinator.com/item?id=48441935</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=48441935</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48441935</guid></item><item><title><![CDATA[New comment by rahen in "Powering up a module from the IBM 604: an electronic calculator from 1948"]]></title><description><![CDATA[
<p>The Gamma 3, which competed with the 604, only had about 400 tubes as far as I remember: <a href="https://en.wikipedia.org/wiki/Bull_Gamma_3" rel="nofollow">https://en.wikipedia.org/wiki/Bull_Gamma_3</a><p>Both the 604 and the G3 were bit serial to save components.</p>
]]></description><pubDate>Sun, 07 Jun 2026 19:56:25 +0000</pubDate><link>https://news.ycombinator.com/item?id=48437962</link><dc:creator>rahen</dc:creator><comments>https://news.ycombinator.com/item?id=48437962</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48437962</guid></item></channel></rss>