The potato plant is a nightshade, closely related to the tomato. All nightshades contain poisonous alkaloids, including small amounts in tomato fruits and green potato skins.

The potato is still a vegetable though… Vegetable is a culinary term and can apply to any part of a plant, including roots and tubers.

But it didn’t though. Old apps work just fine. There are plenty of reasons to complain about Apple - but the way they changed architecture twice and did so with impressive backwards compatibility both times is not one of them.

I’ve previously argued that current gen “AI” built on transformers are just fancy predictive type, but as I’ve watched the models continue to grow in complexity it does seem like something emergent that could be described as a type of intelligence is happening.

These current transformer models don’t possess any concept of truth and, as far as I understand it, that is fundamental to their nature. That makes their application severely more limited than the hype train suggests, but that shouldn’t undermine quite how incredible they are at what they can do. A big enough statistical graph holds an unimaginably complex conceptual space.

They feel like a dream state intelligence - a freewheeling conceptual synthesis, where locally the concepts are consistent, while globally rules and logic are as flexible as they need to be to make everything make sense.

Some of the latest image and video transformers, in particular, are just mind blowing in a way that I think either deserves to be credited with a level of intelligence, or should make us question more deeply what we means by intelligence.

I find dreams to be a fascinating place. It often excites people to thing that animals also dream, and I find it as exciting that code running on silicon might be starting to share some of that nature of free association conceptual generation.

Are we near AGI? Maybe. I don’t think that a transformer model is about to spring into awareness, but maybe we’re only a few breakthroughs away from a technology which will pull all these pieces off specific domain AI together into a working general intelligence.

Squeezing a metal cylinder out my chute sounds a lot less pleasant than just pooping poop.

I read a series of super interesting posts a few months back where someone was exploring the dimensional concept space in LLMs. The jump off point was the discovery of weird glitch tokens which would break GPTs, making them enter a tailspin of nonsense, but the author presented a really interesting deep dive into how concepts are clustered dimensionally, presenting some fascinating examples and, for me at least, explained in a very accessible manner. I don’t know if being able to identify those conceptual clusters of weights means we’re anywhere close to being able to manually tune them, but the series is well worth a read for the curious. There’s also a YouTube series which really dives into the nitty gritty of LLMs, much of which goes over my head, but helped me understand at least the outlines of how the magic happens.

(Excuse any confused terminology here, my knowledge level is interested amateur!)

Posts on glitch tokens and exploring how an LLM encodes concepts in multidimensional space. https://www.lesswrong.com/posts/8viQEp8KBg2QSW4Yc/solidgoldmagikarp-iii-glitch-token-archaeology

YouTube series is by 3Blue1Brown - https://m.youtube.com/@3blue1brown

This one is particularly relevant - https://m.youtube.com/watch?v=9-Jl0dxWQs8

I’ve never heard of Macs running embedded systems - I think that would be a pretty crazy waste of money - but Mac OS Server was a thing for years. My college campus was all Mac in the G4 iMac days, running MacOS Server to administer the network. As far as I understand it was really solid and capable, but I guess it didn’t really fit Apples focus as their market moved from industry professionals to consumers, and they killed it.

🛼 Yeah, RISC is good ⚗️🔥

If it’s trained on the average Reddit reply: $420.69, nice.

Thanks for taking the time to write that! I learned something new today. I usually take tea with oat milk, so now I’m curious what proteins oat milk has and if they act similarly. I’ll do some more reading.

You have piqued my interest on the thing of milk binding up beneficial chemicals. Can you elaborate?

Some people even put the milk in first.

Tip of the iceberg. I’m perplexed about every 30 minutes working on this codebase.

Merry Christmas is a popular expression in the UK too.

I think that merriment is actually much easier to attain than happiness. One could be miserable in life, but have a few drinks and be merry.

Oof. Meme hits hard.

Any platform has vulnerability to exploit to some degree. But this article is about piggybacking on the Find My network to transmit data without actually compromising the network. It’s a clever technique, and worth reading more than the headline.

Trans people are literally just trying to get on with their lives while bigots obsess about them.

The same type of people said the same things about women getting the vote, interracial couples, and homosexuality.

I hope history continues to move in the right direction and leave these nosey fucks as nothing more than shameful memories.

When native English speakers complain that changing pronouns is too hard 🧐

Just to add some cool etymology to your reply: the word silhouette comes from a type of affordable portrait made by quickly painting or cutting out a persons profile in black paper. These, and portrait miniatures, fell quickly out of favour with the advent of photography.

The word silhouette is derived from the name of Étienne de Silhouette, a French finance minister who, in 1759, was forced by France’s credit crisis during the Seven Years’ War to impose severe economic demands upon the French people, particularly the wealthy.[3] Because of de Silhouette’s austere economies, his name became synonymous with anything done or made cheaply and so with these outline portraits.[4][5] Prior to the advent of photography, silhouette profiles cut from black card were the cheapest way of recording a person’s appearance.[6][7]

https://en.wikipedia.org/wiki/Silhouette

This is also an interesting article on the subject of pre-photographic portraiture: https://en.m.wikipedia.org/wiki/Portrait_miniature

I built my family tree and thought - oh neat, even more ancestors to disappoint.

Already we know we must lead all roads to this place.