401–410 of 412 posts
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Except, very literally, data is a collection of single points (ie what we call "anecdotes").
“Plural of anecdote is data” is meant to be tongue-in-cheek. Actual data is sampled randomly. Anecdotes very much are not.
To be fair, possibly because of this tongue-in-cheek statement, anecdote is sometimes used in place of datum and not as anecdote is usually defined.
I dunno, these reasoning models seems kinda "dumb" because they try to bootstrap itself via reasoning, even though a simple direct answer might not exist (for example key information are missing for a proper answer). Ask something like: "Ravioli: x = y: France, what could be x and y?" (it thought for 500s and the answers were "weird") Or "Order from left to right these items ..." and give partial information on their…
Not sure if it there's some prior literature it was trained on.
https://chat.qwen.ai/s/e239e36f-185a-4f6c-a3d2-f4c4ee0d2960?...
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The question doesn't define which side you're going to look from at the end, so either looking down or up is valid.
While technically true, one could argue that because they described sliding a mirror underneath the table, that they did this in order to be able to see from that particular angle, so the implication for any reasonable answer would be that are looking down at the table.
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Didn't know Perplexity cracked R1's censorship but it is completely uncensored. Anyone can try even without an account: https://labs.perplexity.ai/ . HuggingFace also was working on Open R1 but not sure how far they got.
>completely uncensored Sorry, no. It's not. It can't write about anything "problematic". Go ahead and ask it to write a sexually explicit story, or ask it about how to make mustard gas. These kinds of queries are not censored in the standard API deepseek R1. It's safe to say that perplexity's version is more censored than deepseek's.
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I'm curious what kind of prompting or context you are providing before asking for a liquid soap script - or if you've tried using Cursor and providing a bunch of context with documentation about liquid soap as part of it. My guess was these kinds of things get the models to perform much better. I have seen this work with internal APIs / best practices / patterns.
Yes, I used Cursor and tried providing both the whole Liquidsoap book or the URL to the online reference just in case the book was too large for context or it was triggering some sort of RAG. Not successful. It's not that it didn't do what I wanted: most of the time it didn't even run. Iterating on the error messages just arrived at progressively dumber not-solutions and running in circles.
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I similarly have a small, simple spatial reasoning problem that only reasoning models get right, and not all of them, and which Qwen3 on max reasoning still gets wrong. > I put a coin in a cup and slam it upside-down on a glass table. I can't see the coin because the cup is over it. I slide a mirror under the table and see heads. What will I see if I take the cup (and the mirror) away?
Sonnet 3.7 non-reasoning got it right. I'll think this through step by step. When you place a coin in a cup and slam it upside-down on a glass table, the coin will be between the table surface and the cup. When you look at the reflection in the mirror beneath the table, you're seeing the bottom side of the coin through the glass. Since the mirror shows heads, you're seeing the heads side of the coin reflected in the…
lol
I have a small physics-based problem I pose to LLMs. It's tricky for humans as well, and all LLMs I've tried (GPT o3, Claude 3.7, Gemini 2.5 Pro) fail to answer correctly. If I ask them to explain their answer, they do get it eventually, but none get it right the first time. Qwen3 with max thinking got it even more wrong than the rest, for what it's worth.
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> I’ve gotten 0 production usable python out of any LLM Fascinating, I wonder how you use it because once I decompose code to modules and function signatures, Claude[0] is pretty good at implementing Python functions. I'd say it one-shots 60% of the times, I have to tweak the prompt or adjust the proposed diffs 30%, and the remaining 10% is unusable code that I end up writing by hand. Other things Claude is even bett…
I agree - you have to treat them like juniors and provide the same context you would someone who is still learning. You can’t assume it’s correct but where it doesn’t matter it is a productivity improvement. The vast majority of the code I write doesn’t even go into production so it’s fantastic for my usage.