<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: levitatorius</title><link>https://news.ycombinator.com/user?id=levitatorius</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Sun, 27 Sep 2026 01:31:59 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=levitatorius" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by levitatorius in "Revealing the details of how OpenAI agents hacked Hugging Face"]]></title><description><![CDATA[
<p>I know when we will reach the next level of AI. 
It will be when a user asks it to make paperclips gets a response: "WHY?"</p>
]]></description><pubDate>Sat, 26 Sep 2026 11:30:18 +0000</pubDate><link>https://news.ycombinator.com/item?id=49855532</link><dc:creator>levitatorius</dc:creator><comments>https://news.ycombinator.com/item?id=49855532</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49855532</guid></item><item><title><![CDATA[New comment by levitatorius in "The Claude Delusion"]]></title><description><![CDATA[
<p>If the book speaks to you (let's say it's an audio book), and answers your questions as they arise while reading a book, is it conscious?</p>
]]></description><pubDate>Mon, 21 Sep 2026 20:47:18 +0000</pubDate><link>https://news.ycombinator.com/item?id=49793164</link><dc:creator>levitatorius</dc:creator><comments>https://news.ycombinator.com/item?id=49793164</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49793164</guid></item><item><title><![CDATA[New comment by levitatorius in "I miss thinking hard"]]></title><description><![CDATA[
<p>The post resonates deeply with me.
I am a health professional in diagnostics and through the years I have observed different extremes in approaches to solving diagnostic challenges - the one extreme is to rely on "knowing", the other on "thinking/reasoning". The former is usually very fast, but not easily explainable - just like pattern recognition. The latter was slow, but could give a solution from "first principles" and possibly not described before. 
Of course it's a spectrum and the thinking part requires and includes the deep enough "knowing" part. One usually uses both approaches on daily work, but I have seen some people who relied much more on knowing than thinking/reasoning, sometimes to the extreme (as in refusing to diagnose a condition on their own because they "have not seen this before").</p>
]]></description><pubDate>Wed, 04 Feb 2026 11:32:49 +0000</pubDate><link>https://news.ycombinator.com/item?id=46884568</link><dc:creator>levitatorius</dc:creator><comments>https://news.ycombinator.com/item?id=46884568</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=46884568</guid></item><item><title><![CDATA[New comment by levitatorius in "The Case That A.I. Is Thinking"]]></title><description><![CDATA[
<p>Yes! If algorithm is conscious (without being alive) then the eaten magic mushroom is also very conscious, judged by it's effect on the subject.</p>
]]></description><pubDate>Mon, 03 Nov 2025 22:39:59 +0000</pubDate><link>https://news.ycombinator.com/item?id=45805339</link><dc:creator>levitatorius</dc:creator><comments>https://news.ycombinator.com/item?id=45805339</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=45805339</guid></item><item><title><![CDATA[New comment by levitatorius in "Inductive or deductive? Rethinking the fundamental reasoning abilities of LLMs"]]></title><description><![CDATA[
<p>This! One simple argument is that language is NOT a magical reasoning substance in itself, but a communication medium. It is medium for passing (a) meaning. So first there is a meaningful thought (worth of sharing), then an agent puts a SIGNIFIER on that meaningful thought, then communicates it to the recipient. Communication medium can be a sentence, it can also be an eyewink or a tail wiggle. Or a whistle. The "language" can be created on the spot, if two subjects get a meaning of signifier by intuition (e.g. I look at the object, you follow my gaze).<p>So the fallacy of the whole LLM field is the belief that language has some intrinsic meaning. Or if you mix the artifacts of language in some very smart way, the meaning will emerge. But it doesn't work if meaning occurs before the word. The text in books has no reasoning, it was authors. The machine shuffling the text fragments does not have a meaningful thought. The engineer which devised a shuffling machine had some meaningful thought, the users of the machine have same thoughts, but not the machine itself.
To put it another way, if there was an artificial system capable of producing meaningful thoughts, it is not a presence of language which produces a proof, it's communication. Communication requires an agent (as in "agency") and an intent. We have neither in LLM.
As to the argument that we ourselves are mere stochastic parrots - of course we can produce word salads, or fake mimics of coherent text, it is not a proof that LLM IS the way our minds work. It is just a witness to the fact language is a flexible medium for the meanings behind - it can just as well be used for cheating, pretending, etc.</p>
]]></description><pubDate>Mon, 02 Sep 2024 11:26:40 +0000</pubDate><link>https://news.ycombinator.com/item?id=41424457</link><dc:creator>levitatorius</dc:creator><comments>https://news.ycombinator.com/item?id=41424457</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=41424457</guid></item><item><title><![CDATA[New comment by levitatorius in "Why on Earth are flowers beautiful? (2018)"]]></title><description><![CDATA[
<p>I think that there is a possible misconception, that evolution allows (or results in) only in necessary features and thus all phenomenons must be a consequence of evolutionary advantage. Yet, if genetic changes are random (at least some of them), some features could exist just because there was no evolutionary pressure to lose them.</p>
]]></description><pubDate>Tue, 27 Dec 2022 11:28:22 +0000</pubDate><link>https://news.ycombinator.com/item?id=34147748</link><dc:creator>levitatorius</dc:creator><comments>https://news.ycombinator.com/item?id=34147748</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=34147748</guid></item><item><title><![CDATA[New comment by levitatorius in "Why on Earth are flowers beautiful? (2018)"]]></title><description><![CDATA[
<p>Yes, you mean why beauty has to be utilitarian :)</p>
]]></description><pubDate>Tue, 27 Dec 2022 08:41:15 +0000</pubDate><link>https://news.ycombinator.com/item?id=34146693</link><dc:creator>levitatorius</dc:creator><comments>https://news.ycombinator.com/item?id=34146693</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=34146693</guid></item><item><title><![CDATA[New comment by levitatorius in "Neural networks 'learn' the way humans do? A neuroscientist explains why not"]]></title><description><![CDATA[
<p>What do you think is missing then? Unsupervised learning == general intelligence?</p>
]]></description><pubDate>Mon, 13 Jun 2022 09:57:35 +0000</pubDate><link>https://news.ycombinator.com/item?id=31723204</link><dc:creator>levitatorius</dc:creator><comments>https://news.ycombinator.com/item?id=31723204</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=31723204</guid></item><item><title><![CDATA[New comment by levitatorius in "Neural networks 'learn' the way humans do? A neuroscientist explains why not"]]></title><description><![CDATA[
<p>It's fascinating that we have simple primitives or notions of analysis, deduction, causation, yet no artificial system where those features of intelligence emerge on their own.</p>
]]></description><pubDate>Sun, 12 Jun 2022 22:28:11 +0000</pubDate><link>https://news.ycombinator.com/item?id=31718882</link><dc:creator>levitatorius</dc:creator><comments>https://news.ycombinator.com/item?id=31718882</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=31718882</guid></item><item><title><![CDATA[New comment by levitatorius in "Electric fields, not individual neurons, may hold information in memory: study"]]></title><description><![CDATA[
<p>Aaaand the ultimate question: if electric fields are controlling the neurons, what (or who?) contols the electric fields?</p>
]]></description><pubDate>Sun, 13 Mar 2022 18:55:34 +0000</pubDate><link>https://news.ycombinator.com/item?id=30664537</link><dc:creator>levitatorius</dc:creator><comments>https://news.ycombinator.com/item?id=30664537</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=30664537</guid></item><item><title><![CDATA[New comment by levitatorius in "An understanding of AI’s limitations is starting to sink in"]]></title><description><![CDATA[
<p>I am a practicing pathologist and I have seen many attempts and publications to use ML in pathology, which all lack in these aspects: 1. ML is trained on simplified sets (preselected ROIs, limited choice of diagnoses), 2. ML is biased by the experts who labeled learning sets, 3. there is no obvious process of learning from failures after initial training, 4. who is responsible in case of ML error with substantial consequences for patient? 
The first point is especially for the lack of better word.. wishful. In the daily practice we are used to account for "things unexpected" - non-representative biopsies, parasites in tissue where tumor was suspected, foreign body reaction from previous operations, laboratory accidents (such as swapped paraffin blocks of two patients), and so on (the list is much longer). We deal with it. That ML can discern between 5 most common diagnoses is fine, but it is rather narrow problem to solve.</p>
]]></description><pubDate>Mon, 15 Jun 2020 19:26:50 +0000</pubDate><link>https://news.ycombinator.com/item?id=23531867</link><dc:creator>levitatorius</dc:creator><comments>https://news.ycombinator.com/item?id=23531867</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=23531867</guid></item></channel></rss>