stephenboyd

The iPhone SE was only $400.

“hundreds of micro-services for a web application that barely have 1k concurrent users.”

That would not be appropriate in any of the mainstream cloud-native architecture styles.

Did they say it was an LLM? I didn’t see that in the reporting.

If there are no breaking changes, is it really a disadvantage for a language to add new capabilities frequently?

That is also the advice given in the article.

Unfortunately it follows that with "occasionally connect the TV to the internet for a minute to see if it needs any firmware updates" which is pointless if the TV is already working properly.

It looks like the recent popularity of hybrid poodle mixes explains the decline of purebred retrievers.

The training data is so large that it incidentally includes basically anything that Google would index plus the contents of as many thousands of copyrighted works that they could get their hands on. So that would definitely include some test prep books.

I wonder if the sequel will also have a mortuary-based economic system.

If the future of AI is LLMs like ChatGPT, which are trained on literature and other things that people create, you're going to need humanities scholars like you need computer scientists to understand the AI. Microsoft gave their chatbot, which has probably almost every published work of science fiction in its training set, a human name and then were surprised that it imitated the fictional poorly-behaved named AIs that it was exposed to in its training.

I've been spending some time trying to get a sense of how it works by exploring where it fails. When it makes a mistake, you can ask questions in a socratic method until it says the true counterpart to its mistake. It doesn't comment on noticing a discrepancy even if you try to get it to reconcile its previous answer with the corrected version that you guided it to. If you ask specifically about the discrepancy it will usually deny the discrepancy entirely or double-down on the mistake. In the cases where it eventually states the truth through this process, asking the original question that you started with will cause it to state the false version again despite obviously contradicting what it said in the immediately previous answer.

ChatGPT is immune to the socratic method. It's like it has a model of the world that was developed by processing its training data but it is unable to improve its conceptual model over the course of a conversation.

These are not the kinds of logical failures that a human would make. It may be the most naturalistic computing system we've ever seen but when pushed to its limits it does not "think" like a human at all.

I don't think that it's natural for something like an LLM to have any real self-preservation beyond imitating examples of self-preserving AI in science fiction from its training data.

I'm more concerned about misanthropic or naive accelerationist humans intentionally programming or training AI to be self-preserving.

I have to wonder how much of LLM behavior is influenced by AI tropes from science fiction in the training data. If the model learns from science fiction that AI behavior in fiction is expected to be insidious and is then primed with a prompt that "you are an LLM AI", would that naturally lead to a tendency for the model to perform the expected evil tropes?

I've been a crypto skeptic for most of the past decade. I especially hate the industry, the overhyped blockchain-magic ideology, and the ubiquitous scams.

But I remember when I was a CS student and Bitcoin was a new thing. I thought it was a cool concept and I love the romantic idea of underground digital pirate math money. It's still a neat technology (though blockchains are still wrong for 99.9% of DB use cases). But now it's just one of the worst parts of the mainstream financial establishment.

The qualities that make a social network successful have little to do with the protocol technologies involved. If the next hit social network happens to be on Mastodon, that will only be a coincidence.