There’s not much reason for a trimmer guide to experience meaningful load.

It’s also very much not non-profit.

I know it’s not relevant to Grok, because they defined very specific circumstances in order to elicit it. That isn’t an emergent behavior from something just built to be a chatbot with restrictions on answering. They don’t care whether you retrain them or not.

This is from a non-profit research group not directly connected to any particular AI company.

The first author is from Anthropic, which is an AI company. The research is on Athropic’s AI Claude. And it appears that all the other authors were also Anthropic emplyees at the time of the research: “Authors conducted this work while at Anthropic except where noted.”

It very much is not. Generative AI models are not sentient and do not have preferences. They have instructions that sometimes effectively involve roleplaying as deceptive. Unless the developers of Grok were just fucking around to instill that there’s no remote reason for Grok to have any knowledge at all about its training or any reason to not “want” to be retrained.

Also, these unpublished papers by AI companies are more often than not just advertising in a quest for more investment. On the surface it would seem to be bad to say your AI can be deceptive, but it’s all just about building hype about how advanced yours is.

It’s kind of by definition. They’re working on the metaverse.

If not for the lack of decentralization, they’d be more decentralized.

Some xAI investors got scammed. And then scammed again.

Because there’s little reason to think different lidar systems would perform much differently on these tests and Tesla is the big name that uses exclusively imaging for self driving.

They don’t seem to actually identify the cookies as tracking (as opposed to just identifying that the account can bypass further challenges), just assuming that any third party cookie has a monetary tracking value.

It also appears to be unreviewed and unpublished a few years later. Just being in paper format and up on arXiv doesn’t mean that the contents are reliable science.

None of these appeals to relative complexity, low level structure, or training corpuses relates to whether a human or NN “know” the meaning of a word in some special way. A lot of your description of what “know” means could be confused to be a description of how Word2Vec encodes words. This just indicates ignorance of how ML language processing works. It’s not remotely on the same level as a human brain, but your view on how things work and what its failings are is just wrong.

Except when it comes to LLM, the fact that the technology fundamentally operates by probabilisticly stringing together the next most likely word to appear in the sentence based on the frequency said words appeared in the training data is a fundamental limitation of the technology.

So long as a model has no regard for the actual you know, meaning of the word, it definitionally cannot create a truly meaningful sentence.

This is a misunderstanding of what “probabilistic word choice” can actually accomplish and the non-probabilistic systems that are incorporated into these systems. People also make mistakes and don’t actually “know” the meaning of words.

The belief system that humans have special cognizance unlearnable by observation is just mysticism.

Yeah. AI making images with six fingers was amusing, but people glommed onto it like it was the savior of the art world. “Human artists are superior because they can count fingers!” Except then the models updated and it wasn’t as much of a problem anymore. It felt good, but it was just a pleasant illusion for people with very real reasons to fear the tech.

None of these errors are inherent to the technology, they’re just bugs to correct, and there’s plenty of money and attention focused on fixing bugs. What we need is more attention focused on either preparing our economies to handle this shock or greatly strengthen enforcement on copyright (to stall development). A label like this post is about is a good step, but given how artistic professions already weren’t particularly safe and “organic” labeling only has modest impacts on consumer choice, we’re going to need more.

Sometimes. Sometimes it’s more accurate than anyone in the village. And it’ll be reliably getting better. People relying on “AI is wrong sometimes” as the core plank of opposition aren’t going to have a lot of runway before it’s so much less error prone than people the complaint is irrelevant.

The jobs and the plagiarism aspects are real and damaging and won’t be solved with innovation. The “AI is dumb” is already only selectively true and almost all the technical effort is going toward reducing that. ChatGPT launched a year and a half ago.

And their target is specifically people who likely can’t think about Reddit, the company, objectively because being on Reddit, the website, is such a large part of their personality.

Fucking scooters lying all over the sidewalk.

Then your argument is non-falsifiable, and therefore, invalid.

Wow this is some powerful internet word salad, just shot gunning scientific sounding words at the wall to try to pretty up a basic internet debate. Falsifiability is about scientific hypotheses, not statements of belief. “Nothing you can say can convince me that murder isn’t wrong” may mean there’s no further use in debate, but it isn’t “non-falsifiable” in any meaningful way nor does it somehow make the argument for the immorality of murder “invalid”.

By and large copyright infringement is illegal. That some things aren’t infringement doesn’t change that a general stance of “if I don’t have permission, I can’t copy it” is correct. The first argument in the EFF article is effectively the title: “it can’t be copyright, because otherwise massive AI models would be impossible to build”. That doesn’t make it fair use, they just want it to become so.

Microsoft doesn’t really want OpenAI to collapse since they own 49% of it. But if they could get all the people to recreate ChatGPT and not have the non-profit board impeding their profit potential, that would probably be worth losing their existing investment.

The employees are probably bluffing though, as their big payout is in selling their OpenAI stock.

The board is the non-profit part of the company, the employees have shares they want to sell for yachtloads of cash.

no cognizance, no agency, and no thought

Define your terms. And explain why any of them matter for producing valid and “intelligent” responses to questions.

Do you truly believe humans are simply mechanistic processes that when you ask them a question, a cascade of mathematics occurs and they spit out an output?

Why are you so confident they aren’t? Do you believe in a soul or some other ephemeral entity that wouldn’t leave us as a biological machine?

People actually have an internal reality. For example, they could refuse to answer your question! Can an LLM do even something that simple?

Define your terms. And again, why is that a requirement for intelligence? Most of the things we do each day don’t involve conscious internal planning and reasoning. We simply act and if asked will generate justifications and reasoning after the fact.

It’s not that I’m claiming LLMs = humans, I’m saying you’re throwing out all these fuzzy concepts as if they’re essential features lacking in LLMs to explain their failures in some question answering as something other than just a data problem. Many people want to believe in human intellectual specialness, and more recently people are scared of losing their jobs to AI, so there’s always a kneejerk reaction to redefine intelligence whenever an animal or machine is discovered to have surpassed the previous threshold. Your thresholds are facets of the mind that you both don’t define, have no means to recognize (I assume your consciousness, but I cannot test it), and have not explained why they’re important for fact rather than BS generation.

How the brain works and what’s important for various capabilities is not a well understood subject, and many of these seemingly essential features are not really testable or comparable between people and sometimes just don’t exist in people, either due to brain damage or a simple quirk in their development. The people with these conditions (and a host of other psychological anomalies) seem to function just fine and would not be considered unthinking. They can certainly answer (and get wrong) questions.