<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: potatoman22</title><link>https://news.ycombinator.com/user?id=potatoman22</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Fri, 23 Oct 2026 19:07:38 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=potatoman22" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by potatoman22 in "Google Playground: Create and play custom games"]]></title><description><![CDATA[
<p>Reminds me of <a href="https://github.com/lemonade-sdk/infinity-arcade" rel="nofollow">https://github.com/lemonade-sdk/infinity-arcade</a></p>
]]></description><pubDate>Wed, 07 Oct 2026 16:04:23 +0000</pubDate><link>https://news.ycombinator.com/item?id=49994716</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=49994716</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49994716</guid></item><item><title><![CDATA[New comment by potatoman22 in "Opus 5.5 is good at explainer videos"]]></title><description><![CDATA[
<p>I really liked this, thank you</p>
]]></description><pubDate>Fri, 25 Sep 2026 18:46:21 +0000</pubDate><link>https://news.ycombinator.com/item?id=49848387</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=49848387</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49848387</guid></item><item><title><![CDATA[New comment by potatoman22 in "Show HN: Cactus Needle 3: 8-29MB automation models can match DeepSeek V4 Flash"]]></title><description><![CDATA[
<p>I think a good "traditional" approach would look like a BM25 algorithm over an index of trigger phrases for each category, sitting behind a majority-vote classifier. The "fine tuning" would be done by reindexing the data, generating different/new phrases, and tuning the classification threshold.</p>
]]></description><pubDate>Fri, 18 Sep 2026 20:45:53 +0000</pubDate><link>https://news.ycombinator.com/item?id=49760041</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=49760041</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49760041</guid></item><item><title><![CDATA[New comment by potatoman22 in "Introducing System One Models and Jev"]]></title><description><![CDATA[
<p>I think that's to demonstrate its speed</p>
]]></description><pubDate>Tue, 15 Sep 2026 21:56:16 +0000</pubDate><link>https://news.ycombinator.com/item?id=49719411</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=49719411</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49719411</guid></item><item><title><![CDATA[New comment by potatoman22 in "StemDeck, a free, open-source and local AI stem separator"]]></title><description><![CDATA[
<p>Adding this to my homelab, thanks for the web browser option. How does your son use the backing tracks? Does he mute bass/drum, or play along with them?</p>
]]></description><pubDate>Sat, 29 Aug 2026 02:58:37 +0000</pubDate><link>https://news.ycombinator.com/item?id=49486497</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=49486497</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49486497</guid></item><item><title><![CDATA[New comment by potatoman22 in "Show HN: I trained a 125M model to autocomplete piano on-device"]]></title><description><![CDATA[
<p>I have about 60 hours of my own playing in midi data. I wonder if I could fine-tune this model on that?</p>
]]></description><pubDate>Fri, 21 Aug 2026 04:13:08 +0000</pubDate><link>https://news.ycombinator.com/item?id=49383703</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=49383703</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49383703</guid></item><item><title><![CDATA[New comment by potatoman22 in "Datasette Apps: Host custom HTML applications inside Datasette"]]></title><description><![CDATA[
<p>It's not specific to SQLlite per se, but that's what most dashboard builders are</p>
]]></description><pubDate>Fri, 19 Jun 2026 16:21:46 +0000</pubDate><link>https://news.ycombinator.com/item?id=48600254</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=48600254</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48600254</guid></item><item><title><![CDATA[New comment by potatoman22 in "Midjourney Medical"]]></title><description><![CDATA[
<p>I was trying to say there's precedent for using ML in this field. I don't think they even said this product is an image generation model. It's probably some ML version of this <a href="https://en.wikipedia.org/wiki/Ultrasound_computer_tomography" rel="nofollow">https://en.wikipedia.org/wiki/Ultrasound_computer_tomography</a><p>I also found this researcher on their staff who studies tomography <a href="https://scholar.google.com/citations?hl=en&user=idvD2yYAAAAJ" rel="nofollow">https://scholar.google.com/citations?hl=en&user=idvD2yYAAAAJ</a></p>
]]></description><pubDate>Thu, 18 Jun 2026 05:03:13 +0000</pubDate><link>https://news.ycombinator.com/item?id=48581023</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=48581023</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48581023</guid></item><item><title><![CDATA[New comment by potatoman22 in "Midjourney Medical"]]></title><description><![CDATA[
<p>Generative models have been used in healthcare for a while for things like drug design and data generation. Not to mention all the algorithms (and probably ML) used in generating results for MRI and CT scans. I don't think this is that crazy provided they can prove it's effective.</p>
]]></description><pubDate>Thu, 18 Jun 2026 02:30:31 +0000</pubDate><link>https://news.ycombinator.com/item?id=48579898</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=48579898</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48579898</guid></item><item><title><![CDATA[New comment by potatoman22 in "Apple reveals new AI architecture built around Google Gemini models"]]></title><description><![CDATA[
<p>I'd wager that for 99.9% of "Apple Intelligence" tasks, Google's models perform just as well as other frontier labs. Google also has done more work on getting LLMs running on edge devices compared to anthropic and openAI.<p>The source also says
> The new architecture centers on Apple Foundation Models co-developed with Google, which Apple says are adapted to run both on-device and on servers through its existing Private Cloud Compute infrastructure<p>Which could mean Google and Apple have trained some custom models, probably the on-device ones, specifically tailored towards Apple's hardware.</p>
]]></description><pubDate>Mon, 08 Jun 2026 20:20:16 +0000</pubDate><link>https://news.ycombinator.com/item?id=48451304</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=48451304</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48451304</guid></item><item><title><![CDATA[New comment by potatoman22 in "S&P 500 rejects SpaceX, also blocking entry for OpenAI and Anthropic"]]></title><description><![CDATA[
<p>Picking an equal weight fund is closer to picking specific stocks than investing in the S&P500 imo</p>
]]></description><pubDate>Sat, 06 Jun 2026 15:59:40 +0000</pubDate><link>https://news.ycombinator.com/item?id=48426249</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=48426249</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48426249</guid></item><item><title><![CDATA[New comment by potatoman22 in "1-Bit Bonsai Image 4B Image Generation for Local Devices"]]></title><description><![CDATA[
<p>I wonder why they didn't use a Bonsai model as the text encoder</p>
]]></description><pubDate>Sun, 31 May 2026 16:58:44 +0000</pubDate><link>https://news.ycombinator.com/item?id=48347326</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=48347326</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48347326</guid></item><item><title><![CDATA[New comment by potatoman22 in "Odysseus – self-hosted AI workspace"]]></title><description><![CDATA[
<p>It reminds me of the Nord theme <a href="https://github.com/nordtheme/nord" rel="nofollow">https://github.com/nordtheme/nord</a></p>
]]></description><pubDate>Sun, 31 May 2026 16:55:46 +0000</pubDate><link>https://news.ycombinator.com/item?id=48347294</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=48347294</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48347294</guid></item><item><title><![CDATA[New comment by potatoman22 in "Incident Report: May 19, 2026 – GCP Account Suspension"]]></title><description><![CDATA[
<p>Google should know why a human accepted the automated suggestion, or if and why there wasn't any human oversight in the first place.</p>
]]></description><pubDate>Wed, 20 May 2026 18:37:08 +0000</pubDate><link>https://news.ycombinator.com/item?id=48212094</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=48212094</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48212094</guid></item><item><title><![CDATA[New comment by potatoman22 in "DeepSeek-V4-Flash means LLM steering is interesting again"]]></title><description><![CDATA[
<p>This reminds me of control vectors, especially this line in the linked DwarfStar repo:<p>> y = y - scale * direction[layer] * dot(direction[layer], y)<p>From <a href="https://vgel.me/posts/representation-engineering/" rel="nofollow">https://vgel.me/posts/representation-engineering/</a><p>> A control vector is a vector (technically a list of vectors, one per layer) that you can apply to model activations during inference to control the model's behavior without additional prompting</p>
]]></description><pubDate>Sat, 16 May 2026 18:08:12 +0000</pubDate><link>https://news.ycombinator.com/item?id=48162410</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=48162410</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48162410</guid></item><item><title><![CDATA[New comment by potatoman22 in "Running local models on an M4 with 24GB memory"]]></title><description><![CDATA[
<p>Neat! It seems like Qwen 9b took the same amount of time as gemma4-e4b too, which is interesting. I haven't been able to get Qwen to stop thinking so much</p>
]]></description><pubDate>Wed, 13 May 2026 00:54:38 +0000</pubDate><link>https://news.ycombinator.com/item?id=48116582</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=48116582</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48116582</guid></item><item><title><![CDATA[New comment by potatoman22 in "Running local models on an M4 with 24GB memory"]]></title><description><![CDATA[
<p>Not to be nitpicky, but many of the 4-12b models are somewhere between GPT-3.5 and GPT-4o-mini. It's hard to find a good comparison though, because the benchmarks people score models against change so often. For reference, Sonnet 3.6 came out about a year after GPT 3.5</p>
]]></description><pubDate>Mon, 11 May 2026 04:47:01 +0000</pubDate><link>https://news.ycombinator.com/item?id=48091144</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=48091144</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48091144</guid></item><item><title><![CDATA[New comment by potatoman22 in "Talkie: a 13B vintage language model from 1930"]]></title><description><![CDATA[
<p>The website has a "chat" link near the top</p>
]]></description><pubDate>Tue, 28 Apr 2026 15:56:12 +0000</pubDate><link>https://news.ycombinator.com/item?id=47936240</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=47936240</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47936240</guid></item><item><title><![CDATA[New comment by potatoman22 in "The risk of AI isn't making us lazy, but making "lazy" look productive"]]></title><description><![CDATA[
<p>There's a point where they meet, but "faking it until you make it" doesn't work for productivity in the same way it doesn't work for getting rich.<p>But there's a secret: just buy my $399 masterclass and I'll teach you 17 simple productivity hacks to 100x your income.</p>
]]></description><pubDate>Sat, 28 Mar 2026 16:06:40 +0000</pubDate><link>https://news.ycombinator.com/item?id=47555850</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=47555850</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47555850</guid></item><item><title><![CDATA[New comment by potatoman22 in "North Korean's 100k fake IT workers net $500M a year for Kim"]]></title><description><![CDATA[
<p>Bloomberg made a good video about this <a href="https://www.youtube.com/watch?v=-gjnrMg9iSo" rel="nofollow">https://www.youtube.com/watch?v=-gjnrMg9iSo</a></p>
]]></description><pubDate>Wed, 18 Mar 2026 17:46:47 +0000</pubDate><link>https://news.ycombinator.com/item?id=47428878</link><dc:creator>potatoman22</dc:creator><comments>https://news.ycombinator.com/item?id=47428878</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47428878</guid></item></channel></rss>