<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: sergeivaskov</title><link>https://news.ycombinator.com/user?id=sergeivaskov</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Sun, 03 May 2026 18:43:45 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=sergeivaskov" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by sergeivaskov in "What do you think of people buying Mac mini's to run AI?"]]></title><description><![CDATA[
<p>The premise that 'barely any decent size models can run on it' misses the biggest advantage of Apple Silicon: Unified Memory. Where else can you get a machine with 64GB or 128GB of VRAM for running quantized models at this price point? Buying the equivalent VRAM in Nvidia GPUs (like multiple RTX 3090s/4090s) would cost thousands of dollars, draw massive power, and sound like a jet engine. The Mac Mini is dead silent, sips power, and lets you run 70B+ parameter models locally via llama.cpp. It's currently the undisputed king of VRAM-per-dollar for local inference.</p>
]]></description><pubDate>Fri, 01 May 2026 13:48:37 +0000</pubDate><link>https://news.ycombinator.com/item?id=47974783</link><dc:creator>sergeivaskov</dc:creator><comments>https://news.ycombinator.com/item?id=47974783</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47974783</guid></item><item><title><![CDATA[New comment by sergeivaskov in "Tell HN: VS Code v1.117.0 automatically adds GitHub Copilot as your co author"]]></title><description><![CDATA[
<p>If Copilot insists on being a co-author for suggesting a comma, I expect it to also take co-responsibility for the bugs it introduces and page itself when the production goes down at 2 AM.</p>
]]></description><pubDate>Fri, 01 May 2026 13:43:26 +0000</pubDate><link>https://news.ycombinator.com/item?id=47974734</link><dc:creator>sergeivaskov</dc:creator><comments>https://news.ycombinator.com/item?id=47974734</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47974734</guid></item><item><title><![CDATA[Meet Gantt Chart for Trello!]]></title><description><![CDATA[
<p>Article URL: <a href="https://www.reddit.com/r/productivity/comments/d2c5mi/meet_gantt_chart_for_trello/">https://www.reddit.com/r/productivity/comments/d2c5mi/meet_gantt_chart_for_trello/</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=20931845">https://news.ycombinator.com/item?id=20931845</a></p>
<p>Points: 3</p>
<p># Comments: 0</p>
]]></description><pubDate>Tue, 10 Sep 2019 18:50:37 +0000</pubDate><link>https://www.reddit.com/r/productivity/comments/d2c5mi/meet_gantt_chart_for_trello/</link><dc:creator>sergeivaskov</dc:creator><comments>https://news.ycombinator.com/item?id=20931845</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=20931845</guid></item><item><title><![CDATA[GoodGantt – The Best Gantt Chart for Trello]]></title><description><![CDATA[
<p>Article URL: <a href="https://goodgantt.com">https://goodgantt.com</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=18060004">https://news.ycombinator.com/item?id=18060004</a></p>
<p>Points: 1</p>
<p># Comments: 0</p>
]]></description><pubDate>Mon, 24 Sep 2018 18:22:38 +0000</pubDate><link>https://goodgantt.com</link><dc:creator>sergeivaskov</dc:creator><comments>https://news.ycombinator.com/item?id=18060004</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=18060004</guid></item></channel></rss>