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The Singularity will occur on a Tuesday
531–540 of 800 posts
Re: The Singularity will occur on a Tuesday
#532[dead]
Re: The Singularity will occur on a Tuesday
#533Earlier quoted context omitted.
No one relies on "interpretability" in quantum mechanics. It is famously uninterpretable. In any case, I don't think any further engagement is going to be productive for anyone here so I'm dropping out of this thread. Good luck.
Quantum mechanics has competing interpretations (Copenhagen, Many-Worlds, etc.) about what the math means philosophically, but we still have precise mathematical models that let us predict outcomes and engineer devices. Again, we lack even this much with LLMs so why say we know how they work ?
Unless I'm missing what you mean by a mile, this isn't true at all. We have infinitely precise models for the outcomes of LLMs because they're digital. We are also able to engineer them pretty effectively.
Re: The Singularity will occur on a Tuesday
#534Hail Zorp
Re: The Singularity will occur on a Tuesday
#535Slight correction, I've been studying token prices last weeks so this caught my eye:
>"(log-transformed, because the Gemini Flash outlier spans 150× the range otherwise)"
> "Gemini 2.0 Flash Dec 2024 2,500,000"
I think OP meant Gemini 2 flash lite, which is distinct from Gemini 2 flash. It's also important to consider that this tier had no successor in future models, there's no gemini 3 flash lite, and gemini 3 flash isn't the spiritual successor.
Re: The Singularity will occur on a Tuesday
#536Earlier quoted context omitted.
> We really have no idea how did ability to have a conversation emerge from predicting the next token. Maybe you don't. To be clear, this is benefiting massively from hindsight, just as how if I didn't know that combustion engines worked, I probably wouldn't have dreamed up how to make one, but the emergent conversational capabilities from LLMs are pretty obvious. In a massive dataset of human writing, the answer to…
> Maybe you don't. My best friend who has literally written a doctorate on artificial intelligence doesn't. If you do, please write a paper on it, and email it to me. My friend would be thrilled to read it.
Yeah I sort of cringed when I read his comment to be honest
The whole point of the area of work that as far as I know is called interpretability, is precisely to try and figure exactly how these things work
So I thought your comment was a good way of putting this
Re: The Singularity will occur on a Tuesday
#537Earlier quoted context omitted.
No this is false. No one understands. Using big words doesn’t change the fact that you cannot explain for any given input output pair how the LLM arrived at the answer. Every single academic expert who knows what they are talking about can confirm that we do not understand LLMs. We understand atoms and we know the human brain is made 100 percent out of atoms.we may know how atoms interact and bond and how a neuron wo…
I'm not pretending. Unlike you I do not have any issues making sense of function approximation w/ gradient descent. I learned this stuff when I was an undergrad so I understand exactly what's going on. You might be confused but that's a personal problem you should work to rectify by learning the basics.
omfg the hard part of ML is proving back-propagation from first principles and that's not even that hard. Basic calculus and application of the chain rule that's it. Anyone can understand ML, not anyone can understand something like quantum physics.
Anyone can understand the "learning algorithm" but the sheer complexity of the output of the "learning algorithm" is way to high such that we cannot at all characterize even how an LLM arrived at the most basic query.
This isn't just me saying this. ANYONE who knows what they are talking about knows we don't understand LLMs. Geoffrey Hinton: https://www.youtube.com/shorts/zKM-msksXq0. Geoffrey, if you are unaware, is the person who started the whole machine learning craze over a decade ago. The god father of ML.
Understand?
There's no confusion. Just people who don't what they are talking about (you)
Re: The Singularity will occur on a Tuesday
#538Earlier quoted context omitted.
I'm not pretending. Unlike you I do not have any issues making sense of function approximation w/ gradient descent. I learned this stuff when I was an undergrad so I understand exactly what's going on. You might be confused but that's a personal problem you should work to rectify by learning the basics.
omfg the hard part of ML is proving back-propagation from first principles and that's not even that hard. Basic calculus and application of the chain rule that's it. Anyone can understand ML, not anyone can understand something like quantum physics. Anyone can understand the "learning algorithm" but the sheer complexity of the output of the "learning algorithm" is way to high such that we cannot at all characterize e…
I don't see how telling me I don't understand anything is going to fix your confusion. If you're confused then take it up w/ the people who keep telling you they don't know how anything works. I have no such problem so I recommend you stop projecting your confusion onto strangers in online forums.
Re: The Singularity will occur on a Tuesday
#539> In 2025, 1.1 million layoffs were announced. Only the sixth time that threshold has been breached since 1993.
Wow only 6 times in 30 years! Surely a unique and world shattering once in a lifetime experience!
Re: The Singularity will occur on a Tuesday
#540Earlier quoted context omitted.
Quantum mechanics has competing interpretations (Copenhagen, Many-Worlds, etc.) about what the math means philosophically, but we still have precise mathematical models that let us predict outcomes and engineer devices. Again, we lack even this much with LLMs so why say we know how they work ?
Unless I'm missing what you mean by a mile, this isn't true at all. We have infinitely precise models for the outcomes of LLMs because they're digital. We are also able to engineer them pretty effectively.
The ML Research world (so this isn't simply a matter of being ignorant/uninformed) was surprised by the performance of GPT-2 and utterly shocked by GPT-3. Why ? Isn't that strange ? Did the transformer architecture fundamentally change between these releases ? No, it did not at all.
So why ? Because even in 2026, nevermind 18 and 19, the only way to really know exactly how a neural network will perform trained with x data at y scale is to train it and see. No elaborate "laws", no neat equations. Modern Artificial Intelligence is an extremely empirical, trial and error field, with researchers often giving post-hoc rationalizations for architectural decisions. So no, we do not have any precise models that tell us how a LLM will respond to any query. If we did, we wouldn't need to spend months and millions of dollars training them.