Recent submissions

Comment · 11 days ago
Maybe. With enough money and resources and time, maybe. But it would need to be very reliable to be at all useful, and that level of reliability is very hard to achieve with something so nuanced and complex.

You have an entire lifetime of experience and the wisdom of countless generations to inform you of the context with which you should process new information. You were specifically trained for years to be able to do this somewhat effectively. Doing the same for an LLM may or may not be possible. They contain much of that experience in some form, but are not well equipped to make use of it iteratively. It is incredibly expensive to attempt even a simple and ineffective version of it with our current methods.

If the LLM can achieve even 90% accuracy, it becomes more of a hindrance than a help. Do you make use of the function and trust it successfully understood the provenance of new information? If so, ten percent of the time you will be misled, which could be disastrous across a population. If you don't simply trust it, then do you painstakingly check the provenance of everything it tells you? Of course not, you already don't do that with current search engines and blogs and such. Yet falling somewhere in between would be so much worse than simply not having the LLM attempt to discern trustworthiness from providence in the first place.

But all of that is opinion and I may be incorrect. Perhaps someone will create some ingenious way of imparting wisdom and discernment to LLMs next year and this will all be trivial.

Comment · 11 days ago
Of course. But when you see text in the descriptor of a satchel on a satchel seller's site, you contextualize it as marketing. If you saw the same text in a textbook on the history, design, and manufacturing of satchels, you would contextualize it very differently.

When an LLM is the lens through which you view that text, you often don't have the context of where it came from, and the LLM is often really bad at filtering trustworthiness based on context when retrieving information to answer a query with.

I wouldn't go to a random site with a sketchy URL to get the customer service number for my xyz. I'd go to their official domain. Thus successfully navigating the treacherous waters scammers attempt to muddy.

Comment · 1 month ago
No. They can't play chess on a grandmaster level without a harness programmed to make it possible. Simply training an LLM on chess games isn't enough.

It's moronic to suggest a "formal" definition of a commonly understood word is somehow necessary to say whether that word applies in a given situation.

LLMs cannot write poetry via understanding what makes good poetry. They generate tokens. They do not know whether those tokens are poetry or a recipe for cat food. Because they cannot know anything.

Comment · 1 month ago
To be fair, we can't model human language well enough to accurately predict what an actual human will say either. Our ability to accurately model physics is similar to our ability to accurately model human language. And we make immense use of both kinds of model, despite their flaws, inaccuracies, and inability to ever be perfect.
Comment · 1 month ago
This is so wildly incorrect I don't even know where to start.

For one, they were absolutely programmed to play chess if they can play chess. That is the only way they can play chess.

For another, they cannot understand literally anything, much less love.

Trying to actually educate you would be an exercise in futility, enjoy your willful ignorance, I hear it's bliss. But for anyone reading this, this is absolutely, unequivocally not how any of this works.

Comment · 1 month ago
It isn't hard to program a gpt. You can do it in a weekend with a few hundred lines of python. The code is pretty simple. The math is not particularly high level.

The complexity and scale with LLMs come from the amount of training data used, not some kind of black magic in the programming.

Comment · 1 month ago
That isn't the correct context. The code running the llm is well understood and the llm is simply the result of that code being executed. It is still a computer doing what it is told. It's just that we told it to use an incredibly large number of probabilities to calculate what series of tokens would have most likely come next after a given series of tokens. There is no hallucination or lie or rogue actions. There's just a program using math to generate tokens in response to other tokens.
Comment · 1 month ago
I am trying to imagine how the magnet could be compromised. Could you theoretically embed an electromagnetic and a controller within a decoy magnet and somehow detect what was being recorded and subvert it? Probably not but... No, just probably not.
Comment · 2 months ago
Windows batch, no?
Comment · 2 months ago
It stays plugged into my PC and requires a single second of effort to tap it. I have another that lives on my keys and again requires barely any effort to tap against my phone.

But sure, if the tiniest bit of effort is too much, there isn't really a good way to make passwords actually secure for you. Hopefully that doesn't have any totally unforeseeable consequences for you down the line.

Comment · 2 months ago
You use a yubikey? Duh?
Comment · 2 months ago
Comment · 2 months ago
Always makes me chuckle when there's this uncountably large group of people, and someone meets a handful of them and then decides they can make broad, sweeping statements about the entire group, despite having not met 99.99...% of them XD
Comment · 2 months ago
Is the extracted content stored in a way that could be easily converted to markdown? Seems like this could be integrated incredibly well with obsidian as a way to automatically expand your knowledge base, as well as a better search for it.
Comment · 2 months ago
Is this an ad for "pangram"? Reads like one to me. Not much of anything related to peptides was actually communicated, which makes the insult about your reader's potential ignorance of peptides even more unnecessary.

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