<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: bloep</title><link>https://news.ycombinator.com/user?id=bloep</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Sun, 06 Sep 2026 08:28:41 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=bloep" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by bloep in "AI language models are struggling to “get” math"]]></title><description><![CDATA[
<p>You'd need something Spotify.<p>Another similar possibility might be to do more RL with this data, e.g. using upside-down RL. One can possibly steer this with user feedback as well.</p>
]]></description><pubDate>Fri, 14 Oct 2022 11:17:24 +0000</pubDate><link>https://news.ycombinator.com/item?id=33202015</link><dc:creator>bloep</dc:creator><comments>https://news.ycombinator.com/item?id=33202015</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=33202015</guid></item><item><title><![CDATA[New comment by bloep in "AI language models are struggling to “get” math"]]></title><description><![CDATA[
<p>What I had in mind was kind of like a reward model that is trained by on longer outputs that have a very high similarity to training examples. Something similar has been done to prevent LLMs from using toxic language. You'd simply backprop through that model like in GANs. And no it does not contradict the overall training objective completely because the criterion would be long verbatim copies and it would not affect shorter copies of sound fragments and the like which you would want a music model to produce in order for it to sound realistic and natural.</p>
]]></description><pubDate>Thu, 13 Oct 2022 21:03:05 +0000</pubDate><link>https://news.ycombinator.com/item?id=33196456</link><dc:creator>bloep</dc:creator><comments>https://news.ycombinator.com/item?id=33196456</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=33196456</guid></item><item><title><![CDATA[New comment by bloep in "AI language models are struggling to “get” math"]]></title><description><![CDATA[
<p>There are quite simple tricks to avoid repetition/copying in NNs, e.g. by (1) training a model to predict the "popularity" of the main model's outputs and penalizing popular/copied productions by backpropping through that model so as to decrease the predicted popularity, or (2) by conditioning on random inputs (LLMs can be prompted with imaginary "ID XXX" prefixes before each example to mitigate repetitions), or (3) by increasing temperature or optimizing for higher entropy. LLM outputs are already extremely diverse and verbatim copying is not a huge issue at all. The point being, all evidence points to this not being a show stopper if you massage these evolutionary methods for long enough in one or more of the various right ways.</p>
]]></description><pubDate>Wed, 12 Oct 2022 22:21:12 +0000</pubDate><link>https://news.ycombinator.com/item?id=33184419</link><dc:creator>bloep</dc:creator><comments>https://news.ycombinator.com/item?id=33184419</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=33184419</guid></item><item><title><![CDATA[New comment by bloep in "AI language models are struggling to “get” math"]]></title><description><![CDATA[
<p>Indeed, there is lots of denial or ignorance in this thread (ignorance in the technical sense). AudioLM already produced impressive results and it's a tiny fraction of what is already possible because performance simply improves with scale. One can probably solve music generation today with a ~$1B budget for most purposes like film or game music, or personalized soundtracks. This is not science fiction.</p>
]]></description><pubDate>Wed, 12 Oct 2022 20:03:06 +0000</pubDate><link>https://news.ycombinator.com/item?id=33182286</link><dc:creator>bloep</dc:creator><comments>https://news.ycombinator.com/item?id=33182286</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=33182286</guid></item><item><title><![CDATA[New comment by bloep in "ThinkPad’s 30th Anniversary: An Insider’s Perspective"]]></title><description><![CDATA[
<p>Modern ThinkPads are unfortunately also not very repairable. Replacing the USB-C port on the X1 Carbon is a 1 hour Job. The RAM is soldered on. Replacing the keyboard requires disassembling everything. Replacement parts are prohibitively expensive because Lenovo keeps the prices high. It's still better than Apple though.</p>
]]></description><pubDate>Sat, 08 Oct 2022 15:05:44 +0000</pubDate><link>https://news.ycombinator.com/item?id=33132900</link><dc:creator>bloep</dc:creator><comments>https://news.ycombinator.com/item?id=33132900</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=33132900</guid></item></channel></rss>