i believe this is the first ever direct attack on any nation's nuclear triad in history, and it succeeded.

https://twitter.com/shaunmmaguire/status/1929211001028927509

proof that strategic depth alone is not enough. enormous offensive / defensive asymmetry when some guys in a truck can successfully hit your strategic bomber fleet.

what exactly is wired’s purpose in publishing this article ? it includes names and personal details of the young men in question - what is intended to be achieved? in what sense is this in the public interest? media-fueled witch hunts against young men in the united states have ruined lives, and worse. this is unconscionable. we are fortunate that the legacy media apparatus is becoming more irrelevant by the day.

democracy is for the peaceful rotation of elites, not to express anyone’s will.

https://twitter.com/esyudkowsky/status/1853280134763327873

it neither leads to the best or even good government, nor does it allow you to be rid of a bad government. elections justify the transfer of power without bloodshed and this is what makes representative democracy historically unique.

responses to this post are emblematic of the broader cultural divide between and among tech and split into roughly four types:
1. 'yes, this is a hard and important problem that will likely take a lot of time and difficult work to solve, let's try to figure that out'

https://twitter.com/bayeslord/status/1819837187145220321

2. 'you fucking idiot, you stupid moron, don't you know how hard this problem is? the one that you said is hard? how dare you even think about trying to change or improve anything you goddamn tech bro'

yesterday evening i gave a presentation to founders, investors, and the ai community at @aixventureshq on how to think about ai application development. it was well received so i'm going to reproduce it in full here on x the everything app (which is also now a slide deck app). 1. buzzwords are mind killers. you must empty your head of all buzzwords. the temptation with any new technology is to use existing concepts as crutches as much as possible, but this kills the creativity necessary to explore the full capabilities of this new technology.

new abstractions which don't carry meaning are unnecessary / harmful:
- 'rag' is meaningless as a concept. imagine calling a web app 'database augmented programming'.
- 'agent' probably just means 'run an llm in a loop'

phd-sounding terms to say simple concepts mostly let everyone know how cool you are for readng the arxiv but don't help anyone get work done:
- 'prompting' means 'text input'
- 'system prompt' means 'the instruction part of the text input'

it is far too early to spend time adopting the abstractions imposed by existing tools and frameworks. until you understand what you want to build and how to build it, these can only slow you down

finally, ai application development is still just programming, with the same social and technological implications as all programming since we invented the stored instruction computer

before any of this gets fixed it's necessary to understand why men in tech dress like shit. hacker culture and the web allowed people to rebel against the stifling business culture of the 90's. in software, especially foss, people were judged by their work, not their appearance.

https://twitter.com/sarah_cone/status/1783149180963180617

the first wave of truly successful new-breed software companies were founded and succeeded by the hacker ethos. in contrast to 90's / 2000's microsoft, nobody gave a shit what you wore to work at early google as long as you did the job. the best flocked to these co's.

merry christmas

the only things in the new testament about jesus’ life after age 12, before starting his ministry at age 30, are the verses mark 6:3 and matthew 13:55

in most english translations, they say jesus was (the son of) a carpenter, but this isn’t quite right in the original greek, the word is τέκτων, tekton, a general term for artisans, craftsmen, and builders - indeed, this word has the same root as τεχνολογία - technologia, the study and discourse of craft

jesus spent his early adult life as a builder, making useful things

good morning from san francisco.

now that the dust has settled on the first round of the openai debacle, it’s time to start asking some questions

two of the board members who voted altman out, helen toner and tasha mccauley are deeply enmeshed in ‘effective altruism’ ‘effective altruism’ as a movement has a lot wrong with its ideas, some of which i’ve documented before, but this isn’t about that - it’s about basic competence

https://twitter.com/atroyn/status/1725936159665377333

regardless of how exactly this shakes out - and it’s looking increasingly likely that this was a poorly executed power grab by mental defectives - it’s important to remember that ‘effective altruists’ have been consistently wrong about literally everything they completely failed to predict the dominant paradigm for ai (llms), instead building castles out of sand on the idea of recursively self-improving agents and ideas like “instrumental convergence” and “orthogonality”, none of which apply because an llm has no agency

i spent the weekend working to try to get more data about the question of whether or not gpt has world models

my results seem to suggest it doesn't, but i found some interesting things along the way. writeup below. the entire question really kicked off for me when people were using gpt's performance on chess under certain conditions as strong evidence for the idea that it has world models

at the same time, it couldn't play well from random positions

https://twitter.com/atroyn/status/1708532375968530603

making retrieval practical for ai applications takes a lot more than repackaging a vector database built for semantic search, or adding vector search to an existing database. in the first place, the core vector search and storage architecture for ai is fundamentally different from that made for semantic search

in semantic search / recommender systems, all the data in a single very large index is accessible to every user

theodore ’ted’ kaczynski regains self-awareness in the basement of ‘the annex’ of the department of social relations, harvard, cambridge.

the heroic dose of lsd administered personally by henry murray has had unanticipated effects on his mind.

it is spring 1961.

ted is 19. his inherent shyness has melted away. something has reformed itself in his personality.

furthermore, murray’s constant psychological assault no longer touches him. it’s a feeling as if these people and their cruel experiments don’t matter.

he leaves the study.

here is an argument against the possibility of recursive self improvement of any 'intelligent' computer program, based on kolmogorov complexity. intelligence is the ability to make correct predictions about the state of the world given available information.

each program which makes predictions about the world has a kolmogorov complexity corresponding to the length of the shortest string which can express that program

have been discussing what exactly this means and felt it might be useful to clarify what i'm talking about when i say 'do engineering' in this context

i'm referring to the empirical approach to engineering which marks the evolution of any technology from experimental to useful

https://twitter.com/atroyn/status/1645504550890258432

the process goes like:
- identify an interesting phenomenon in the function of the system.
- empirically characterize the appearance and process of the phenomenon
- develop a predictive model of the phenomenon
- develop a theory which explains the model
- repeat

last weekend we ran the first ever chatgpt plugins hackathon, with support from @OpenAI, @Replit and @retool

by all accounts, it was an enormous success.

here are the winners:

https://twitter.com/atroyn/status/1644788509541277696

@OpenAI @Replit @retool category: civic duty

find relevant legislation in progress about a political issue you care about, find out what stage its in, then find the contact info of the relevant people and get your voice heard

https://twitter.com/mpopv/status/1645248186838290432

TREMBLE, ENEMIES OF TECHNOLOGICAL PROGRESS

CHROMA HAS SECURED FUNDING TO SHAKE THE VERY FOUNDATIONS OF THE POSSIBLE

A NEW WORLD IS BEING BORN

https://twitter.com/jeffreyhuber/status/1643987813346742274

i am, obviously, incredibly excited about this next stage for @trychroma.

a.i is the kind of once-in-a-generation shift you hope to see as an entrepreneur, and it feels like we're uniquely positioned to ride it

i have for a long time been prepared to be swayed by the arguments of @ESYudkowsky and of the alignment/safety community in general

i cannot get past this part in his piece in 'time'. this reads like 'and then the ai invents magic' @ESYudkowsky this is the part i struggle with most in trying to understand safety arguments, and believe me, i really have tried - sometimes i feel like the person on earth who has read the most safety / alignment literature while staying unconvinced

it's 2043.

agi has been with us for anywhere between ten and twenty years, depending on who you ask.

it's a sunny friday afternoon in san francisco. i'm walking to meet an old friend for coffee at flywheel.

it's still there, right at the edge of golden gate park. i've got my airphones set to minimal distraction - apple's ar thing worked out by the way, these are pretty good - i want to think 'organically' for a while, take the world in as it is instead of how it could be.

tomorrow there will be time to look ahead again.

chroma engineer @HammadTime has shipped a brilliant demo showing how you can use chroma's javascript API, together with vercel and the VoxCeleb dataset, to find out which celebrity you sound like. try it out!

https://twitter.com/HammadTime/status/1633222219219472384

@HammadTime building this kind of application is super simple with chroma - check out the write-up here, give it a shot for yourself!

trychroma.notion.site/chroma-blog-f6…

i don’t startup hustle post much, but one of the more gratifying things about building chroma has been the trust and confidence other successful founders of really great companies have in us if you like what we’re doing, we welcome your contributions via pull request or even github star github.com/chroma-core/ch…

why do most approaches to controlling model behavior rely on acting only in the model's input domain?

prompt engineering, fine-tuning etc. all feel like trying to pick a lock with a wet noodle. mechanistic interpretability (valuable work) follows the execution path and attempts to map it onto a human-understandable computation, but that doesn't quite feel right either.