<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: stijntonk</title><link>https://news.ycombinator.com/user?id=stijntonk</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Fri, 08 May 2026 13:32:55 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=stijntonk" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by stijntonk in "AlphaEvolve: Gemini-powered coding agent scaling impact across fields"]]></title><description><![CDATA[
<p>No, for clients we use paid Vertex AI accounts. We often need to host workloads in an EU region, which rules out “global” models (and probably better capacity).<p>In the past, we used a wrapper that round-robined across multiple projects to get enough quota. Luckily, many of our workloads are workflow-style tasks, so we can simply keep retrying on 429s.<p>Fun fact: for one of their services, I think it was Stitch, I noticed that my paid key kept hitting quota, while the free worked fine. That blew my mind.</p>
]]></description><pubDate>Thu, 07 May 2026 18:51:24 +0000</pubDate><link>https://news.ycombinator.com/item?id=48053258</link><dc:creator>stijntonk</dc:creator><comments>https://news.ycombinator.com/item?id=48053258</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48053258</guid></item><item><title><![CDATA[New comment by stijntonk in "AlphaEvolve: Gemini-powered coding agent scaling impact across fields"]]></title><description><![CDATA[
<p>I wish that Google would focus on bringing their Gemini 3.x models to GA, and provide enough capacity such that one not constantly has to fight with 429 errors.<p>It often feels like they do not want me to develop applications for corporate clients using their Vertex API. It is just such a shame, given that their models were so great for document analysis etc.</p>
]]></description><pubDate>Thu, 07 May 2026 18:27:31 +0000</pubDate><link>https://news.ycombinator.com/item?id=48052966</link><dc:creator>stijntonk</dc:creator><comments>https://news.ycombinator.com/item?id=48052966</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48052966</guid></item><item><title><![CDATA[New comment by stijntonk in "Computer vision is having another ImageNet moment"]]></title><description><![CDATA[
<p>Over a decade has passed since the ‘deep learning revolution’ turned the world of computer vision upside-down, and now we are about to witness another transformative shift that promises to make computer vision simpler and more accessible than ever before.</p>
]]></description><pubDate>Fri, 12 Jul 2024 08:23:41 +0000</pubDate><link>https://news.ycombinator.com/item?id=40943638</link><dc:creator>stijntonk</dc:creator><comments>https://news.ycombinator.com/item?id=40943638</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=40943638</guid></item><item><title><![CDATA[Computer vision is having another ImageNet moment]]></title><description><![CDATA[
<p>Article URL: <a href="https://www.mozaik.ai/blog/computer-vision-is-having-another-imagenet-moment">https://www.mozaik.ai/blog/computer-vision-is-having-another-imagenet-moment</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=40943637">https://news.ycombinator.com/item?id=40943637</a></p>
<p>Points: 4</p>
<p># Comments: 1</p>
]]></description><pubDate>Fri, 12 Jul 2024 08:23:41 +0000</pubDate><link>https://www.mozaik.ai/blog/computer-vision-is-having-another-imagenet-moment</link><dc:creator>stijntonk</dc:creator><comments>https://news.ycombinator.com/item?id=40943637</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=40943637</guid></item><item><title><![CDATA[Open-sourcing Whirl: Local Airflow development made easy]]></title><description><![CDATA[
<p>Article URL: <a href="https://blog.godatadriven.com/open-source-airflow-local-development">https://blog.godatadriven.com/open-source-airflow-local-development</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=20000489">https://news.ycombinator.com/item?id=20000489</a></p>
<p>Points: 2</p>
<p># Comments: 0</p>
]]></description><pubDate>Fri, 24 May 2019 11:43:26 +0000</pubDate><link>https://blog.godatadriven.com/open-source-airflow-local-development</link><dc:creator>stijntonk</dc:creator><comments>https://news.ycombinator.com/item?id=20000489</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=20000489</guid></item><item><title><![CDATA[Towards fairness in ML with adversarial networks]]></title><description><![CDATA[
<p>Article URL: <a href="https://blog.godatadriven.com/fairness-in-ml">https://blog.godatadriven.com/fairness-in-ml</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=16943970">https://news.ycombinator.com/item?id=16943970</a></p>
<p>Points: 2</p>
<p># Comments: 0</p>
]]></description><pubDate>Fri, 27 Apr 2018 20:22:32 +0000</pubDate><link>https://blog.godatadriven.com/fairness-in-ml</link><dc:creator>stijntonk</dc:creator><comments>https://news.ycombinator.com/item?id=16943970</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=16943970</guid></item><item><title><![CDATA[Parallel scikit-learn on YARN [pdf]]]></title><description><![CDATA[
<p>Article URL: <a href="http://files.meetup.com/3097452/sklearn-yarn.pdf">http://files.meetup.com/3097452/sklearn-yarn.pdf</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=11086431">https://news.ycombinator.com/item?id=11086431</a></p>
<p>Points: 6</p>
<p># Comments: 0</p>
]]></description><pubDate>Fri, 12 Feb 2016 10:57:25 +0000</pubDate><link>http://files.meetup.com/3097452/sklearn-yarn.pdf</link><dc:creator>stijntonk</dc:creator><comments>https://news.ycombinator.com/item?id=11086431</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=11086431</guid></item></channel></rss>