<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: gdiamos</title><link>https://news.ycombinator.com/user?id=gdiamos</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Sun, 01 Nov 2026 13:22:54 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=gdiamos" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by gdiamos in "Anthropic blocks users for anything touching training larger models"]]></title><description><![CDATA[
<p>Some thoughts on this.<p>The Pile was created by high school students. I was impressed how good it was when it came out given the team and how many resources they had.<p>Including 200k pirated books seems like a problem. It should be removed. If I was an author, I would be concerned by a process that allows this much content to be effectively published with no filter on the internet.<p>I personally think there is a lower bar for researchers and high school students to clean datasets used for research or class projects given that there is no commercial harm and cleaning huge datasets takes engineering resources that not everyone has.<p>In this case, it looks like it was removed by <a href="https://huggingface.co/collections/common-pile/common-pile-v01" rel="nofollow">https://huggingface.co/collections/common-pile/common-pile-v...</a><p>Companies that commercialize the data should have a higher bar because they have more resources. It seems like Anthropic paid $1.5B for not cleaning the data before releasing a model based on it.</p>
]]></description><pubDate>Sun, 01 Nov 2026 05:05:38 +0000</pubDate><link>https://news.ycombinator.com/item?id=50322871</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=50322871</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=50322871</guid></item><item><title><![CDATA[New comment by gdiamos in "Anthropic blocks users for anything touching training larger models"]]></title><description><![CDATA[
<p>>> Where I draw the line is asking Claude to label training data. I don’t do this.<p>> Why draw any line? Anthropic doesn't. They actively take the world's intellectual property, don't pay for it, and put it behind a paywall.<p>I know a lot of silicon valley founders think like this. I personally don't think that just because someone else violated a boundary makes it okay to do it.</p>
]]></description><pubDate>Sun, 01 Nov 2026 04:41:50 +0000</pubDate><link>https://news.ycombinator.com/item?id=50322763</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=50322763</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=50322763</guid></item><item><title><![CDATA[New comment by gdiamos in "Anthropic blocks users for anything touching training larger models"]]></title><description><![CDATA[
<p>It's right here - you can't see it due to being downvoted.<p>I asked Claude to research this one and it turned up an interesting point. Pirated books got into the Pile and Anthropic paid 3k per book.
Worth noting if anyone still uses the Pile.<p>[Claude researched, not verified]<p>In October 2020, developer Shawn Presser converted the Bibliotik pirate tracker into Books3 (196,640 books) and hosted it on The Eye, aiming to give everyone what OpenAI had with its secret Books1 and Books2. EleutherAI then folded Books3 into The Pile, distributed via Hugging Face and GitHub, and it went on to train Meta's LLaMA, EleutherAI's Pythia, and BloombergGPT. In August 2023, Alex Reisner of The Atlantic exposed its contents, and Maria Fredenslund's Danish Rights Alliance forced takedowns at The Eye, Hugging Face, and EleutherAI. A year later, Andrea Bartz (The Lost Night), Charles Graeber (The Good Nurse), and Kirk Wallace Johnson (The Feather Thief) filed Bartz v. Anthropic before Judge William Alsup, accusing Anthropic of using Books3, LibGen, and PiLiMi to train Claude; the case settled for $1.5 billion, about $3,000 per work.</p>
]]></description><pubDate>Sun, 01 Nov 2026 04:30:57 +0000</pubDate><link>https://news.ycombinator.com/item?id=50322718</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=50322718</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=50322718</guid></item><item><title><![CDATA[New comment by gdiamos in "Anthropic blocks users for anything touching training larger models"]]></title><description><![CDATA[
<p>Downvoted after providing evidence.</p>
]]></description><pubDate>Sun, 01 Nov 2026 03:36:58 +0000</pubDate><link>https://news.ycombinator.com/item?id=50322490</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=50322490</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=50322490</guid></item><item><title><![CDATA[New comment by gdiamos in "Anthropic blocks users for anything touching training larger models"]]></title><description><![CDATA[
<p>That's very click baitey. Do you have an argument or evidence for why?</p>
]]></description><pubDate>Sun, 01 Nov 2026 01:22:25 +0000</pubDate><link>https://news.ycombinator.com/item?id=50321888</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=50321888</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=50321888</guid></item><item><title><![CDATA[New comment by gdiamos in "Anthropic blocks users for anything touching training larger models"]]></title><description><![CDATA[
<p>One of my points of my ethical framework is that IP is valuable and should not be stolen.<p>Another way of saying is that hard work that advances the state of the art should be rewarded. Patents should exist.<p>I’m sure they are watching what I’m doing and would retaliate via service cut off and legal action if I crossed it egregiously and they found out.<p>I would do the same thing if a user or employee did this to my IP.<p>I don’t completely buy the argument of web scraping being an IP violation.<p>I don’t send my core ip in an email to my main competitors and I don’t post it on the internet.</p>
]]></description><pubDate>Sat, 31 Oct 2026 23:29:00 +0000</pubDate><link>https://news.ycombinator.com/item?id=50321266</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=50321266</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=50321266</guid></item><item><title><![CDATA[New comment by gdiamos in "Anthropic blocks users for anything touching training larger models"]]></title><description><![CDATA[
<p>Where I draw the line is asking Claude to label training data. I don’t do this.<p>I ask it questions about large models like big MoEs all the time. I’ve never had it refuse a question, but I would expect it to refuse sometimes.<p>For training data from existing models I just get open models to spill their guts. It’s fine<p>In industry we train employees to not reveal proprietary information.<p>I think it would be easier to do this for a model than a lot of employees</p>
]]></description><pubDate>Sat, 31 Oct 2026 21:49:13 +0000</pubDate><link>https://news.ycombinator.com/item?id=50320591</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=50320591</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=50320591</guid></item><item><title><![CDATA[New comment by gdiamos in "Classification of Finite Simple Groups Formalized in Lean"]]></title><description><![CDATA[
<p>This tech is about to come for software.</p>
]]></description><pubDate>Wed, 28 Oct 2026 08:58:36 +0000</pubDate><link>https://news.ycombinator.com/item?id=50270822</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=50270822</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=50270822</guid></item><item><title><![CDATA[New comment by gdiamos in "Using AI to reverse engineer hardware"]]></title><description><![CDATA[
<p>Why don’t you do as much of this as possible for the next six months and make the best product you can.<p>It sounds like it will go faster if you use coding agents.<p>Anyone copying you will have to do the same.<p>Perhaps spend a month with your agent making it harder for other agents to reverse engineer?</p>
]]></description><pubDate>Thu, 15 Oct 2026 15:46:02 +0000</pubDate><link>https://news.ycombinator.com/item?id=50105375</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=50105375</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=50105375</guid></item><item><title><![CDATA[New comment by gdiamos in "Typesafe AI raises $870M at $7.5B"]]></title><description><![CDATA[
<p>Good job typesafe.<p>You won the competition with VCs</p>
]]></description><pubDate>Fri, 09 Oct 2026 21:42:24 +0000</pubDate><link>https://news.ycombinator.com/item?id=50026939</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=50026939</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=50026939</guid></item><item><title><![CDATA[New comment by gdiamos in "Stay discoverable in search while disallowing AI training"]]></title><description><![CDATA[
<p>I wouldn’t trust an AI company to honor this as far as I could throw them</p>
]]></description><pubDate>Wed, 16 Sep 2026 05:24:33 +0000</pubDate><link>https://news.ycombinator.com/item?id=49722412</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=49722412</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49722412</guid></item><item><title><![CDATA[New comment by gdiamos in "More questions about whether researchers can trust OpenAI with unpublished math"]]></title><description><![CDATA[
<p>How to steal ideas with AI.<p>step 1, identify high value users by net worth, citation count, or number of followers<p>step 2, select all prompts by high value users<p>step 3, invest 10 billion thinking tokens in modeling an objective for each user<p>step 4, build an RL environment for each user<p>step 5, rollout 10 billion tokens per environment<p>step 6, train on resulting traces</p>
]]></description><pubDate>Thu, 10 Sep 2026 19:09:23 +0000</pubDate><link>https://news.ycombinator.com/item?id=49648805</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=49648805</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49648805</guid></item><item><title><![CDATA[New comment by gdiamos in ">10x More Efficient Pretraining"]]></title><description><![CDATA[
<p>Training improvements are very easy to copy.</p>
]]></description><pubDate>Thu, 10 Sep 2026 17:31:09 +0000</pubDate><link>https://news.ycombinator.com/item?id=49647417</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=49647417</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49647417</guid></item><item><title><![CDATA[New comment by gdiamos in "Outrageously Small Neural Networks: Emergent Basic Reasoning at 6,616 tok/SEC [pdf]"]]></title><description><![CDATA[
<p>Data is doing more of the work than it used to. Every  source in our mixture is a curated artifact built with large models<p>Training a model this small on them is distillation<p>When models of this size were last studied seriously such corpora did not exist</p>
]]></description><pubDate>Tue, 08 Sep 2026 01:30:02 +0000</pubDate><link>https://news.ycombinator.com/item?id=49604709</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=49604709</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49604709</guid></item><item><title><![CDATA[New comment by gdiamos in "Outrageously Small Neural Networks: Emergent Basic Reasoning at 6,616 tok/SEC [pdf]"]]></title><description><![CDATA[
<p>The loss does not saturate. Across a 4.91B-token run, smoothed training loss falls monotonically within each curriculum phase and is still descending at the end</p>
]]></description><pubDate>Tue, 08 Sep 2026 01:29:40 +0000</pubDate><link>https://news.ycombinator.com/item?id=49604705</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=49604705</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49604705</guid></item><item><title><![CDATA[New comment by gdiamos in "Outrageously Small Neural Networks: Emergent Basic Reasoning at 6,616 tok/SEC [pdf]"]]></title><description><![CDATA[
<p>blog: <a href="https://gregdiamos.com/2026/09/07/outrageously-small-neural-networks.html" rel="nofollow">https://gregdiamos.com/2026/09/07/outrageously-small-neural-...</a><p>X discussion: <a href="https://x.com/GregoryDiamos/status/2096873745420075020?s=20" rel="nofollow">https://x.com/GregoryDiamos/status/2096873745420075020?s=20</a><p>I added some of the main points to the thread so they are easier to read.</p>
]]></description><pubDate>Tue, 08 Sep 2026 01:11:45 +0000</pubDate><link>https://news.ycombinator.com/item?id=49604602</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=49604602</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49604602</guid></item><item><title><![CDATA[Outrageously Small NNs: Emergent Reasoning at 6,616 Tok/s on One Intel AMX Core]]></title><description><![CDATA[
<p>Article URL: <a href="http://gregdiamos.com/2026/09/07/outrageously-small-neural-networks.html">http://gregdiamos.com/2026/09/07/outrageously-small-neural-networks.html</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=49604500">https://news.ycombinator.com/item?id=49604500</a></p>
<p>Points: 1</p>
<p># Comments: 0</p>
]]></description><pubDate>Tue, 08 Sep 2026 00:54:49 +0000</pubDate><link>http://gregdiamos.com/2026/09/07/outrageously-small-neural-networks.html</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=49604500</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49604500</guid></item><item><title><![CDATA[New comment by gdiamos in "It's time for Mark Zuckerberg to resign from Meta"]]></title><description><![CDATA[
<p>I liked how the article was aimed at Mark personally.<p>Not everyone gets super voting shares, but everyone gets a life and has to live on the same planet.</p>
]]></description><pubDate>Mon, 07 Sep 2026 09:33:58 +0000</pubDate><link>https://news.ycombinator.com/item?id=49596125</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=49596125</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49596125</guid></item><item><title><![CDATA[New comment by gdiamos in "It's time for Mark Zuckerberg to resign from Meta"]]></title><description><![CDATA[
<p>OxyContin, Enron, WorldCom, Super-size-me, Pets.com, Asbestos in the ceiling tiles...<p>It was always burning since the world's been turning</p>
]]></description><pubDate>Mon, 07 Sep 2026 08:59:13 +0000</pubDate><link>https://news.ycombinator.com/item?id=49595834</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=49595834</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49595834</guid></item><item><title><![CDATA[New comment by gdiamos in "It's time for Mark Zuckerberg to resign from Meta"]]></title><description><![CDATA[
<p>we will look back on it as the big tobacco of our generation</p>
]]></description><pubDate>Mon, 07 Sep 2026 08:38:30 +0000</pubDate><link>https://news.ycombinator.com/item?id=49595640</link><dc:creator>gdiamos</dc:creator><comments>https://news.ycombinator.com/item?id=49595640</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49595640</guid></item></channel></rss>