223 karma · joined November 11, 2019
When the topics are as diverse & nuanced as hn feed, sure. When searching for lawnmower or car, 300 text listings of vehicles not so much.
In the same way people take their cars to mechanics when they can do the job themselves, or call triple A for a flat tire when the spare and jack are in the trunk, or reach for the phone instead of a plunger when the toilet backs up, people don't lack the specific skillset, they lack the openness to problems being solvable. They are in perpetual search of answers, not solutions.
They don't want to learn to fish, they don't want to expend energy on process. They want someone else to do it. It's not laziness, it's not incompetence, and it's not entitlement. They are just of a mindset they cannot solve problems, and so they pick up the phone and abstract away the answer.
And I promise you, no 10 minute condescending conversation with someone is going to redefine their core attitudes about life. You're just going to have your well poisoned in the break room with your piss poor attitude because she called the plumber and he told her to fix her own shit (in a manner of speaking).
I don't remember if it was the blog or the extended video but he also got into some of the close to the metal choices they made, like sharing variables and rolling dice on the compiler each build to fit with only a few kb spare in the whole cd space.
This can best be seen in the history of middle earth, his son's chronicle of the writing process for his father's work; volume VI covers the fellowship of the ring, and it is a doozy in first drafts compared to the mainstream published version. He basically tried to reboot Bilbo, and in later drafts his son, going on another quest for dragon gold. It was only after the thing was in full swing that those old impulses and sources found their way into the fabric of the story, sort of figuring out where it was going based on how far he'd wandered in the draft phase.
Anyway he wasn't trying to build english myths when he wrote the books he is famous for, that was more a young & ambitious college student's feverdream.
There's a certain reflective quality and even satisfaction from using a chainsaw after coming up using a tree saw by hand. It feels progressive, even if it is just optimizing for time at the expense of energy.
https://www.dancarlin.com/product/hardcore-history-26-blitz-...
>>The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
hoo-boy.
Additionally hybrid developer/business folk are becoming a thing, diversifying the demand as well as the skillset. To say nothing of the "CEO Compensation" halo effect Silicon Valley wages have on the industry.
Next to sales it is increasingly becoming the most valuable aspect of many industries that are critical to modern western economies (finance, insurance, technology), and AI is 'always' on the horizon as a future cost cutter, so I expect the trend to stick around.
Still I'm willing to go out on an increasingly thin limb and say GPT3 is still playing a really big game of mad libs, and its 'understanding' of the language is more akin to the extremely rudimentary mathematical factoring of sentence structure and grammatical rules. That is, it could be trained to recycle on what others have done for poetry, and spit out something that sounds like what we've read that we call poetry, but it isn't putting poetry out, because it doesn't know what that means...not in like a conscientious way, but a literal, it has no "idea" which to express through a medium, it's just transcribing according to rules, not from say, first principles which then are interpreted through rules.
Again, too much to demand of a really fast adding machine anyway.
You had me up until there; the machine doesn't know jack about text. It knows arrays and sequences of numbers according to the rules we've defined them by, for it.
Yuo cna reda tihs raedliy btu teh copmtuer cna't. Your brain is trained by billions of years of evolution for symbolic parsing and pattern pairing, and language is just one flex of that muscle.
Where computers thrive is where we've done the hard work to break down the syllabic system that is inherent to our biology into mathematical abstractions that can be computed by addition. Computers are great at solving problems we've already done, and repeating the steps, nothing more.
Our machines are beautiful, well designed levers. But they don't move anything, they leverage our movement.
It's not our fault, our brains are wired to find quick & dirty; simple not small is beautiful. But people also contemptuous of what they understand, and accept at face value what they don't. Michael Crichton, much disparaged in his later years for contentious political stances, had much of value to say in his Gell-Mann Amnesia Effects' "wet sidewalks cause rain" critique of how we parse information.
Still, I'm glad it's transparent in this case and thus exposable. How much more is hidden, guarded jealously even, as though methodology was trade secret instead of, you know, the underpinnings of proposed outcome?
For starters, any increase of output with a decrease of input labor is by definition an increase of productivity, individual, net, all of it.
For two, AI hasn't proven anything beyond quickly doing grunt labor. Quickbooks & Excel didn't put the CPA trade out of business, an algorithm that identifies a cat in a picture or whatever reduces overhead, not eliminating professions.
Tangenitally I am, however, very excited at AI's prospects in reverse-engineering and rewriting code, a long-lived fantasy that we can actually un-fark many old or particular programs and systems that are currently hardware dependent or just not worth the man-hours to do the transcription from, say, 16 bit to 64 (or 128, or 256, wherever the future goes).
Lastly, robots have been around since the 60s, industrially and standardized. They do good work, consistently, reduce cost and thus prices and floors of production. The automotive industry is bigger than ever, and more top heavy. This is good, no?
No-one dreams of working on an assembly line for Ford, and unlike the common-wisdom ideal of teenagers & inexperienced workers starting in the service industry and working up & out to better professions, I don't know of anyone who realistically has a career plan of 20 to 60 working their way up from floor sweeper to head of district in any enterprise.
There is this weird pessimism that comes on the tails of this breakthrough in labor leverage, that we're going to put ourselves out of work and have to sit around and then starve to death or get UBI because we're incompetent, when 100 years ago the plurality of Americans were subsistence farmers. Society alters to meet social needs, what we're really talking about is introducing a ton of slack into industrial labor. That isn't a waste, it's the potential for great expansion in so many other fields (think what resources were sunk into industry during Cold War that then turned to softer industries after 1989. Maybe the fantasy here is we should have the best and brightest of us, I dunno stay as mechanical engineers and work for GE or UTC building better stealth bombers instead of looking to FAANG and writing better ad service algorithms).
More energy is always a better thing for society. Labor saving tech is equivalent to increasing the sum of energy available to society. I don't cry because the ladder of the old gold union benes at John Deere were pulled up while I was in gradeschool, I went in search of a better opportunity than the one that wasn't there. The difference may be that "this will affect millions simultaneously!" but so hasn't every transformative technology.
Last-lastly, to make a general economic argument I never see: tens of millions without labor drives up supply which drives down wages. Robots and AI make everything for a fraction of cost (comparable to shipping manufacturing to slave, I mean indigenous, labor overseas for pennies-on-the-dollar in 1970s), so reduced wages maintain balance with cost of goods & services. Entrepreneurs can now exploit a larger labor force with diverse skills to explore new ventures with reduced costs on all front due to labor-saving tech and labor-bloated workforce. This leads to new ideas and extrapolations previously unviable or with a too-high floor of cost to entertain. Trillionaire tech CEOs who own everything divvy out grants like feudal lords funding weird idea-people like Leeuwenhoek with his curious "micro-scope".
Not ideal but that's still more than a starved populace voting demagogues for bread doles.
Bacigalupi falls for japanophilia with the Japanese fetishization of geisha (the windup-girl of the title). His emphasis on mechanical power (i.e. springs and animal labor) was interesting though.
Try flying through Minnesota, Wisconsin, the automaker capital states. Airports full of now-yellowed directions in Japanese for the consideration of what was frequent visitations by their competitors.
It was a no-brainer to bet on Japanese tech in next generation...even Gibson's dated "5MB of hot hitachi RAM" was far-sighted when he wrote it...just not far enough.
I was hoping someone had more insight into process or metrics on it.
Your own post has an implicit accusation that lower socioeconomic situations preclude high testing, which has all kinds of implications about the quality of education and living standards as a prior for acumen. I suppose my own bias shows in drawing that conclusion though. As Henry said though,
"If I had seven peasants, I could make seven lords. But if I had seven lords, I could not make ONE Holbein."
What's your take on MIT's stance?
our ability to accurately predict student academic success at MIT 02 Our research shows this predictive validity holds even when you control for socioeconomic factors that correlate with testing.
Dressing up thoughts in symbols may seem like a marketability approach, or maybe an attack vector in the best traditions of fiction (the best sci-fi is, after all, merely a glass darkly by which to critique contemporary social ills), yet as Blair reminds us:
>"In prose, the worst thing one can do with words is surrender to them. When you think of a concrete object, you think wordlessly, and then, if you want to describe the thing you have been visualizing you probably hunt about until you find the exact words that seem to fit it. When you think of something abstract you are more inclined to use words from the start, and unless you make a conscious effort to prevent it, the existing dialect will come rushing in and do the job for you, at the expense of blurring or even changing your meaning. Probably it is better to put off using words as long as possible and get one's meaning as clear as one can through pictures and sensations."
So, jumping on pop-culture loaded symbols & jargon is a quick way to hijack sentiment or thought along well-dug rut of loaded connotation. Entirely valid critique.
It makes more sense that, without any context, our brain can't just "add" a color to its repertoire, but must interpret some data within the context of existing 'thought'. Some things may be literally unimaginable without a framework of existing memories and experiences, or only possible through some recursive process "Oh so 'a' is 'like' xyz, that makes sense".