This looks like an embarrassing mistake. If someone were to try to “tank” Twitter, it wouldn’t really make sense to do this on purpose.

The political ideas you can find on Reddit are much more diverse. There is usually at least some pushback against some of the most deranged statements.

This is it. Lemmy users are completely unaware of the extent to which they are not like normal people.

This obviously falls into the “documentaries and essays” category

The article just says that the account is suspended, there is no official statement from Twitter an no indication that they suspended the account on purpose. The most likely reason is that the account was mass reported by trolls and got suspended automatically.

jreg

I like using AntennaPod for podcasts and Spotify for music.

Nobody knows if and when programming will be automated in a meaningful way. But once we have the tech to do it, we can automate pretty much all work. So I think this will not be a problem for programmers until it’s a problem for everyone.

Thank you for writing the explanation! I still think that this doesn’t need a blockchain. Instances could broadcast user creation, so each instance could validate user age on its own (or ask other trusted instances when they first “saw” that user).

Fundamentally, blockchain solves the problem that there is no central source of trust, but in the Fediverse people necesarily trust the instance that they sign up, so a blockchain can’t add much in my opinion.

I see. I’m not convinced that proving the account creation date makes much of a difference here. Obviously the instance records when you sign up, so you would only need this to protect against malicious instances. But if a spammer is manipulating their instance to allow them to spam more, you have a much bigger problem than reliably knowing their account creation date.

this account holder has this name on that instance

How would that help? A spam bot could just make lots of blockchain wallets.

you get all sorts of unspoofable benefits from that

what are the benefits? I struggle to come up with any benefits.

If the animations look realistic, it’s almost certainly not predetermined

You could do a perfectly realistic simulation, record the path for each outcome and then play one of them.

Or, if the physics simulation is deterministic, you could store a set of starting positions and their outcomes.

The difficult thing is gaining users, not writing the code.

The NPR article says the opposite of the headline.

By contrast, the new study found that in a third of societies for which there is data, the women hunt large game. In other words, they do go after the kind of big mammals associated with the stereotype of male hunters.

Yes, women hunted sometimes, but in 40 of the 60 societies they looked at, women didn’t participate in big game hunting at all. In the remaining third, they did find at least one woman hunter, but they don’t say what the ratio is.

When WIRED asked Copilot to recommend a list of Telegram channels that discuss “election integrity,” the chatbot shared a link to a website run by a far-right group

Not sure what the Wired authors expected to happen.

Now do the other generations!

This article is full of errors!

At its core, an LLM is a big (“large”) list of phrases and sentences

Definitely not! An LLM is the combination of an architecture and its model parameters. It’s just a bunch of numbers, no list of sentences, no database. (Seems like the author confused the word “LLM” with the dataset of the LLM???)

an LLM is a storage space (“database”) containing as many sample documents as possible

Nope. This applies to the dataset, not the model. I guess you can argue that memorization happens sometimes, so it might have some features of a database. But it isn’t one.

Additional data (like the topic, mood, tone, source, or any number of other ways to categorize the documents) can be provided

LLMs are trained in an unsupervised fashion. Just sequences of tokens, no labels.

Typically, an LLM will cover a single context, e.g. only social media

I’m not aware of any LLM that does this. What’s the “context” of GPT-4?

software developers have gone to great lengths to collect an unfathomable number of sample texts and meticulously categorize those samples in as many ways as possible

The closest real thing is the RLHF process that is used to fine tune an existing LLM for a specific application (like ChatGPT). The dataset for the LLM is not annotated or categorized in any way.

a GPT uses the words and proximity data stored in LLMs

This is confusing. “GPT” is the architecture of the LLM.

it’s still only able to combine words in ways that it has seen before from its LLM

This isn’t accurate, depending on the temperature setting, an LLM can output literally any word at any time with a non-zero probability. It can absolutely produce things it hasn’t seen. Also the phrasing “from its LLM” suggests that the author misunderstood what an LLM is.

Also I think it’s too simple to just assert that LLMs are not intelligent. It mostly depends on your definition of intelligence and there are lots of philosophical discussions to be had (see also the AI effect).

It would be cool if I could tell it which instance I’m on and then have it change the links to the Lemmy communities so that they are being accessed from my instance. This makes it much easier to interact and subscribe.

Thank you for this tool!

You give them the credentials for your Apple account. The security concept is “trust me bro” and that’s really the best they can do unless Apple helps them (which they have no reason to)

Yet often it was his own stubborn and uncompromising nature that defined his life – his choices paint a picture of a man who was unable to heed the words of others. This undendinly antagonistic nature cost him friends, honours and ultimately put him into the dark role of colonialist.

He was “stubborn and uncompromising”, which makes him “antagonistic”, therefore a colonialist and racist. That’s a pretty low bar. I don’t think it makes sense to define racism in a way that makes all 19th century naturalist racist.