numeri

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61.
by numeri 1y ago
I'll just throw in support for gaming on Linux – it's pretty nice feeling these days! I still have the occasional (once every 5–8 months?) update cause a short-lived bug, but it's a very justifiable trade-off to avoid Windows
62.
by numeri 1y ago
This is written by someone who's not an AI researcher, working with tiny models on toy datasets. It's at the level of a motivated undergraduate student in their first NLP course, but not much more.
63.
by numeri 1y ago
One sign would be occasionally changing course in response to overwhelming employee feedback. If that never or almost never happens, the feedback is being ignored, not taken constructively and not followed.
64.
by numeri 1y ago
This isn't right – calibration (informally, the degree to which certainty in the model's logits correlates with its chance of getting an answer correct) is well studied in LLMs of all sizes. LLMs are not (generally) well calibrate
65.
by numeri 1y ago
I really like your posts, and they're generally very clearly written. Maybe this one's just the odd duck out, as it's hard for me to find what you actually meant (as clarified in your comment here) in this paragraph: > Thi
66.
by numeri 1y ago
I'm a little shocked at Simon's conclusion here. We have a man who bought an social media website so he could control what's said, and founded an AI lab so he could get a bot that agrees with him, and who has publicly threate
67.
by numeri 1y ago
That's a bold claim! Actually, there are plenty of scientific experiments that show actual differences between people who report aphantasia and those who don't, including different stress responses to frightening non-visual descri
68.
by numeri 1y ago
That's the thing, some people do see things in their mind that clearly. It's about as rare as full aphantasia, but it's absolutely a spectrum.
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by numeri 1y ago
I think you're assuming more people are like you than actually are. This is part of the classic debate around aphantasia – both sides assume the other side is speaking more metaphorically, while they're speaking literally. E.g., &
70.
by numeri 1y ago
They're definitely quite hard for me. I bet my colleagues, friends or family could answer them for me better than I can without prep (which would involve chatting with my wife). Many of the experiences in this article resonate with me,
71.
by numeri 1y ago
Is the analysis right, or did the LLM hallucinate this?
72.
by numeri 1y ago
Yes, so that one can use it for more creative writing exercises. It was pretty creative, I'll give it that.
73.
by numeri 1y ago
No, it's completely useless, and puts the entire rest of the analysis in a bad light. LLMs have next to no understanding of their own internal processes. There's a significant amount of research that demonstrates this. All explana
74.
by numeri 1y ago
It makes quite a lot of sense juxtaposed with "train time compute". The point being made is that a set budget can be split between paying for more training or more inference _at test time_ or rather _at the time of testing_ the mo
75.
The Case for Insect Consciousness(asteriskmag.com)
4 points by numeri 2y ago|0 comments
76.
by numeri 2y ago
You seem to be responding to what you think I'm saying, not what I'm saying. As far as I know, "killing children" is not a dog-whistle. No one uses the words "killing children" to e.g., secretly express support
77.
by numeri 2y ago
No, avoiding anything potentially negative is not what I'm saying. Your argument (that context always matters) leaves discourse and society highly susceptible to dog-whistles[1], by forcing all good-faith participants to interpret all
78.
by numeri 2y ago
It was the term invented by the architects of the Holocaust, and I disagree that "eh, context matters". Setting all moral arguments aside, it's important to know that similar phrases can work as dog-whistles to signal belongi
79.
by numeri 2y ago
No, the person you're responding to is absolutely right. The easy test (which has been done in papers again and again) is the ability to train linear probes (or non-linear classifier heads) on the current hidden representations to pred
80.
by numeri 2y ago
Do you have a good reference I can read up on? I'd love to learn a bit more and update my mental "citation"
81.
by numeri 2y ago
I've been slightly annoyed by how the Speculative Decoding paper has gotten all the credit for the technique – I first learned about the technique from a paper more than a year older[1], Shallow Aggressive Decoding. They introduce the
82.
by numeri 2y ago
This behavior started happening for me in the last few months. If I click on a result, then go back, I have different search results. I've found a workaround, though – click back into the DDG search box at the top of the page and hit e
83.
by numeri 2y ago
The First Amendement limits what the US Congress/government can do, not what a private person can do. > Congress shall make no law respecting an establishment of religion, or prohibiting the free exercise thereof; or abridging the f
84.
by numeri 2y ago
But gpt-4o can already answer your question for a fraction of the price and time: To determine which of the items could be used to make an actual fire, we need to analyze the definitions provided: 1. *Glaarg*: A wooden item. 2. *Bliirg*: A
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by numeri 2y ago
There was at least one case of someone trying this against Nigel in French, and he got them.
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by numeri 2y ago
Nigel Richards usually outperforms (and is orders of magnitude faster than, at least for the complicated endgames, if I understand correctly) the best computer Scrabble programs.
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by numeri 2y ago
Yes, from what I understand – and they also make mistakes.
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by numeri 2y ago
The big issue here is that they didn't issue a DMCA request, they reported them for fraud.
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by numeri 2y ago
GPU inference is always a balancing act, trying to avoid bottlenecks on memory bandwidth (loading data from the GPU's global memory/VRAM to the much smaller internal shared memory, where it can be used for calculations) and comput
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by numeri 2y ago
The point of this program isn't that it makes things substantially quicker at the checkpoint – it is a minor speed-up at best. The goal is to normalize the collection of biometric data, to shift the Overton window of surveillance.

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