- I log authorization errors as errors. Are they errors? It depends on how you read the logs. Perhaps you want to distinguish between internal, external and non-attributable errors for easier grepping.
- From the FAQ
* Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes.
* Comments should get more thoughtful and substantive, not less, as a topic gets more divisive.
* Please don't fulminate. Please don't sneer, including at the rest of the community.
* Eschew flamebait. Avoid generic tangents. Omit internet tropes.
* Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something.
* Please don't post insinuations about astroturfing, shilling, brigading, foreign agents, and the like. It degrades discussion and is usually mistaken. If you're worried about abuse, email hn@ycombinator.com and we'll look at the data.
- Lots of disagreement, but from necessity I (sort of) agree. Firefox foremost needs users. If it takes AI features to get them, so be it. However, Firefox cannot afford to lose its loyal user base, so they have to be optional.
- I think not everyone in this thread understands that. Someone wrote "It's a time machine", followed up by "Imagine having a conversation with Aristotle."
- There's a whole regiment of immigrants who worked on the Manhattan project, as we all know. We also know that the USSR obtained much of their knowledge on how to build the bomb through espionage.
- I got a bit into SPARK (a subset Ada of that has formal verification) with AoC, and while it can be tricky, SPARK is quite flexible in how much you prove. Dafny sounds interesting, but I can't find a comparison between the two. There's obviously a difference in memory management, but the rest looks quite similar at first sight, and their niche is quite similar. Does anyone know of a (deeper) comparison between both languages?
- Isn't Thunderbird (more or less) independent? "Thunderbird operates in a separate, for-profit subsidiary of the Mozilla Foundation."
- Don't count on it. Have you ever seen how much time and effort has been put in making Firefox, Safari and Chrome compliant and performant? It'll take Ladybird ages to get anywhere near.
Someone could try to merge e,g, V8 and Servo, once that's in decent shape. But even then it'll be time consuming to build an acceptable UI, cookie and history management, plugin interface, etc.
- Allow? It just happens, and when you're the weaker part in the equation, there's not much you can do against it. Where Russia and the USA give up power, China will grab it.
- Thiel and Musk want to decentralize as much as possible, and split everything into small autonomies, so they can pit different jurisdictions against each other, and pressure/manipulate them. That's fairly sure. The goal has never been revealed, but one can assume it is not because it hurts their interests.
- > It's proven that humans can just barely sense large-scale magnetic fields
It's tentatively proven that humans react to large magnetic fields. The reaction can come from simple interference, without ever being processed as a sense.
But there's so much more bullshit. That an MEG measurement was decoded only means that the brain produces a magnetic field that correlates with the information it is processing. So there's no Faraday cage in our head. Great. But the brain already knows what it is doing. All that information is there, very fast and reliable. Why should it try to decode its much less detailed and very weak magnetic field then? Where are the sensors? MEG needs super-conduction to work, and doesn't work when there's any disturbance. In the institute where I worked, it was forbidden to use carts (for moving equipment or coffee or whatever) on all floors in the corner where the MEG was located when there was an experiment going on, because it would disturb measurements. A few crystals aren't going to overcome those problems.
> The easier-than-expected problem of consciousness
OMFG. There's really no point in reading this.
- That misses the point by a mile and a half: nobody let's their children eat unlimited amounts of chocolate. They do, however, let their children access Tiltok, Youtube, etc.
- > The bet is that the effect size (if any) will be large enough to be informative despite the noise.
But you have no grounds to ascribe it to the posited difference. Finding no effect might yield more information, but that's hard: given the amount of noise, you're bound to find a great many effects.
> Have you seen this done?
Not in LLMs, but there have been experiments with regularizing languages, and getting people to learn them in Second Language Acquisition (L2) studies. But what I've seen is inconclusive and sometimes outright contradictory.
I think people have also looked via information theory at this. Probably using Markov models.
> Fedorenko's own comparison to "early LLMs" suggests she thinks the analogy has some merit.
I don't think she can seriously entertain that thought. We simply know practically nothing about language processes in the brain. What we know about the hardware is very different from LLMs, early or not.
Just to give an indication of how much we don't know: the Stroop effect (https://en.wikipedia.org/wiki/Stroop_effect) is almost 100 years old. We have no idea what causes it. There's no working model of word recognition. There are only vague suggestions about the origin of the delay. We have no clue how the visual signals for the color and the letters are separated, where they join again, and how that's related to linguistic knowledge. And that's almost 100 years of very, very much research. IF you go to Google Scholar and type "Stroop task", you'll get 197.000 (!) hits. That's nearly 200k articles etc. resulting in no knowledge whatsoever about a very simple, artificial task.
- It's a rather old-fashioned style of tokenization. In the 1980s this was common, I think. But, as noted in another comment, it doesn't work that well for languages with a richer morphology, or compounding. It's a very "English" approach.
- Wilders received a Russia-Netherlands friendship pin, and posted the picture of him posing with it (in the Duma, IIRC) on this twitter account on Mar 1, 2018.
- COBOL. Now there's a sensible name.
- And don't isomers share their name? And isotopes don't change the name either, I think?
- First: dyslexia has little to do with parsing, which is generally understood to relate to structure/relations between words.
Second: multiple levels of language processing have been identified, although it's not at all clear how well separated they are. The higher levels (semantics, pragmatics) are by necessity lagging behind the lower (phonetics, syntax). The higher levels also seem more "deliberate."
- Afasia, and general measures of "normal" performance.
There are various kinds of afasia, often linked to specific brain areas (Wernicke's and Broca's are well-known). And M/EEG and fMRI research suggests similar distinctions. It is difficult to reconcile with the idea that there is only one language system.
And you will also have noticed that your skills in perception and production differ. You can read/listen better than write/speak. Timing, ambiguity and errors in perception and production differ.
And more logically: the tasks are very different. In perception, you have to perceive the structure and meaning from a highly ambiguous, but ordered input of sound triggering auditory nerves, while during production, meaning is given (in non-linear order), and you have to find a way to fit it in a linear, grammatical order with matching words, which then have to be translated to muscle movements.
In more detail: Chomsky is/was not concerned with the models themselves, but rather with the distinction between statistical modelling in general, and "clean slate" models in particular on the one hand, and structural models discovered through human insight on the other.
With "clean slate" I mean models that start with as little linguistically informed structure as possible. E.g., Norvig mentions hybrid models: these can start out as classical rule based models, whose probabilities are then learnt. A random neural network would be as clean as possible.