Every time I see an article like this, it's always missing --- but is it any good, is it correct? They always show you the part that is impressive - "it walked the tricky tightrope of figuring out what might be an interesting topic and how to execute it with the data it had - one of the hardest things to teach."
Then it goes on, "After a couple of vague commands (“build it out more, make it better”) I got a 14 page paper." I hear..."I got 14 pages of words". But is it a good paper, that another PhD would think is good? Is it even coherent?
When I see the code these systems generate within a complex system, I think okay, well that's kinda close, but this is wrong and this is a security problem, etc etc. But because I'm not a PhD in these subjects, am I supposed to think, "Well of course the 14 pages on a topic I'm not an expert in are good"?
It just doesn't add up... Things I understand, it looks good at first, but isn't shippable. Things I don't understand must be great?
It's gotten more and more shippable, especially with the latest generation (Codex 5.1, Sonnet 4.5, now Opus 4.5). My metric is "wtfs per line", and it's been decreasing rapidly.
My current preference is Codex 5.1 (Sonnet 4.5 as a close second, though it got really dumb today for "some reason"). It's been good to the point where I shipped multiple projects with it without a problem (with eg https://pine.town being one I made without me writing any code).
I feel it sometimes tries to be overly correct. Like using BigInts when working with offsets in big files in javascript. My files are big but not 53bits of mantissa big. And no file APIs work with bigints. This was from Gemini 3 thinking btw
Coding LLMs were almost useless for me, until my AGENTS.md crossed some threshold of completeness and now they are mostly useful. I now curate multiple different markdown files in a /docs folder, that I add to the context as needed. Any time the LLM trips on something and we figure it out, then I ask it to document it's learnings in a markdown doc, and voila it can do it correctly from then on.
Judging by the site, they don't have insightful answers to these questions. It's broken with weird artifacts, errors, and amateurish console printing in PROD.
I definitely don't have insightful answers to these questions, just the ones I gave in the sibling comment an hour before yours. How could someone who uses LLMs be expected to know anything, or even be human?
Alas, I did not realize I was being held to the standard of having no bugs under any circumstance, and printing nothing to the console.
I have removed the amateurish log entries, I am pitiably sorry for any offense they may have caused. I will be sure to artisanally hand-write all my code from now on, to atone for the enormity of my sin.
Yeah, all of the above was a single bug in the plot allocation code, the exception that handled the transaction rollback had the wrong name. It's working again.
> how did you make sure that each new prompt didn't break some previous functionality?
For the backend, I reviewed the code and steered it to better solutions a few times (fewer than I thought I'd need to!). For the frontend, I only tested and steered, because I don't know much about React at all.
This was impossible with previous models, I was really surprised that Codex didn't seem to completely break down after a few iterations!
> did you have a precise vision
I had a fairly precise vision, but the LLM made some good contributions. The UI aesthetic is mostly the LLM, as I'm not very good at that. The UX and functionality is almost entirely me.
> did you not run into this problem described by ilya below
I used to run into a related issue, where fixing a bug would add more bugs, to the point where it would not be able to progress past a given codebase complexity. However, Codex is much better at not doing that. There are some cases where the model kept going back and forth between two bugs, but I discovered that that was because I had misunderstood the constraints and was telling the model to do something impossible.
> how did you discover that and why it slip out.
Sentry alerted me but I thought it was an edge case, and I didn't pay attention until hours later.
I use a spiral allocation algorithm to allocate plots, so new users are clustered around the center. Sometimes plots are emptied (when the user isn't active), so you can have gaps in the spiral, which the algorithm tries to fill, and it's meant to go to the next plot if the current one can't be assigned.
For one specific plot, however, conditions were such that the database was giving an integrity error. The exception handling code that was supposed to handle that didn't take into account that it needed to roll back before resuming, so the entire request failed, instead of resuming gracefully. Just adding an atomic() context manager fixed it.
> looks like site wasn't working at all when you posted that comment?
It was working for a few hundreds (thousands?) of visitors, then the allocation code hit the plot that caused the bug, and signup couldn't proceed after that.
> Just adding an atomic() context manager fixed it.
ok looks like you are intimately familiar with the code that is being produced and are AI as code generator rather than pure vibe coding.
That makes sense to me.
Btw did AI add that line when you explained what the error was or did you add that in manually.
No, I paste the trace back, ask it to explain the error, judge whether it makes sense, and either ask it to fix it or say "that makes no sense, please look again/change the fix/etc".
I certainly hold those opinions still, because the models still have yet to prove they are anything worth a person's time. I don't bother posting that because there's no way an AI hype person and I are ever going to convince each other, so what's the point?
The skeptics haven't evaporated, they just aren't bothering to try to talk to you any more because they don't think there's value in it.
And whats with everything else regarding ML progress like image generation, 3d world generation etc.?
I vibe coded plenty of small things i haven't ever had the time for them. You don't have anything which you wanted to do and can fit in a single page html application? It can even use local storage etc.
This is why they don't talk to you anymore. The only comparison you can make to a flat earther is that you think they're wrong, and flat earthers are also wrong. It's just dumb invective, and people don't like getting empty insults. I prefer my insults full.
The earth is flat until you have evidence of the contrary. It's you who should provide that evidence. We had physics, navigation and then space shuttles that clearly showed the earth is not flat.
We are yet to have a fully vibe-coded piece of software that actually works. The blog post is actually great because LLMs are very good are regurgitating pieces of code that already exist on a single prompt. Now ask them to make a few changes and suddenly the genie is back in the bottle.
Something doesn't math out. You can't be both a genius and extremely dumb (retarded) at the same time. You can be, however, good at information retrieval and presenting it in a better way. That's what LLMs are and am not discounting the usefulness of that.
It’s good at quickly producing a lot of code which is most likely going to give interesting results, and it’s completely unaware of anything including why human might want to produce code.
The marketing bullshit that it’s a "thinking" and "hallucinating" is just bringing the intended confusion on the table.
They are great tools for many purpose. But a GPS is not a copilot, and an LLM is not going to replace coworkers where their humanity matters.
I mean is it really that interesting if it completely falls flat and permanently runs in unfulfilling circles around basically any mild complexity the problem introduces as you get further along solving it, making it really hard to not feel like you need to just do it yourself?
For one thing, it’s far more interesting than a rubber duck in many cases. Of course on that matter in the end it’s about framing the representation adequately and enter a fictional dialog.
Original post alone mentions multiple projects and links https://pine.town as no code directly written by the author.
From perspective of personally using it daily, seeing what my team is using it for it's quite shocking to still see those kind of comments, it's like we're living on different planets - again, gives flat earther like vibe.
We're living in such interesting times - you can talk to a computer and it works, in many cases at extraordinary level - yet you still see intellectually constipated opinions arguing against basic facts established years ago - incredible.
It has been interesting experience, like trolling but you actually believe what you're saying. I wonder how you arrived at it - is it fear, insecurity, ignorance, feelings of injustice or maybe something else? I wonder what bothers you about LLMs?
I think the stochastic part is true and useless. It can be applied to anyone or anything. Yes, the models give you probabilities, but any algorithm gives you probabilities (only zero or one for deterministic ones).
You can definitely view the human mind as a complex statistical model of the world.
Now, that being said, do I think they are as good as a skilled human on most things? No, I don't. My trust issues have increased after the GPT-5 presentation. The very first question was to showcase its "PhD-level" knowledge, and it gave a wrong answer. It just happened to be in a field I know enough about to notice, but most didn't.
So, while I think they can be considered as having some form of intelligence, I believe they have more limits than a lot of people seem to realise.
It is all those things. It consistently fails to make truly novel discoveries, everything it does is derived from something it trained on from somewhere.
No point in arguing about it though with true believers, they will never change their minds.
It's very good but it feels kind of off-the-rails in comparison to Sonnet 4.5 - at least with Cursor it does strange things like putting its reasoning in comments that are about 15 lines long, deleting 90% of a file for no real reason (especially when context is reaching capacity) and making the same error that I just told it not to do.
The computer science field is going to be an absolute shitshow within 5 years (it already kinda is). On one side you'll have ADHD dog attention span zoomers trying out all these nth party model apis and tools every 5 seconds (switching them like socks, insisting the latest one is better, but ultimately producing the same slop) and on the other side you'll have all these applied math gurus squeezing out the last bits of usable AI compute on the planet... and nothing else.
We used to joke that "The internet was a mistake.", making fun of the bad parts... but LLMs take the fucking cake. No intelligent beings, no sentient robots, just unlimited amounts of slop.
The tech basically stopped evolving right around the point of it being good enough for spam and slop, but not going any further, there are no cures no new laws of physics or math or anything else being discovered by these things. All AI use in science I can see is based on finding patters in data, not intelligent thought (as in novel ideas). What a bust.
Completely disagree, what i see agentic coding agents do in combination with LLMs is seriously mind-blowing. I don't care how much knowledge is compressed into an LLM. What is way more interesting is what it does when it misses some knowledge. I see it come up with a plan to create the knowledge by running an experiment (running a script, sometimes asking me to run a script or try something), evaluating the output, and then replan based on the output. Full Plan-Do-Check-Act. Finding answers systematically to things you don't know is way more impressive than remembering lots of stuff.
I don't see a big difference to humans, we are saying many unreasonable things too, validation is necessary. If you use internet, books or AI it is your job to test their validity. Anything can be bullshit, written by human or AI.
In fact I fear the humans optimize for attention and cater to the feed ranking Algorithm too much, while AI is at least trying to do a decent job. But with AI it is the responsibility of the user to guide it, what AI does depends on what the user does.
There are some major differences though. Without using these tools, individual are pretty limited in how much bullshit they can output for many reasons, including they are not mere digital puppet without need to survive in society.
It’s clear pro-slavery-minded elitists are happy to sell the speech that people should become "good complement to AI", that is even more disposable as this puppets. But unlike this mindless entities, people have will to survive deeply engraved as primary behavior.
Sure, but that’s not raw individual output on its mere direct utterance capacities.
Now anyone mildly capable of using a computer is able to produce many more fictional characters than all that humanity collectively kept in its miscellaneous lores, and drawn them in an ocean of insipid narratives. All that nonetheless mostly passing all the grammatical checkboxes at a level most humans would fail (I definitely would :D).
Why does it matter? If you consider not just the people creating these hallucination, but also the people accepting them and using them, it must be billions and billions...
and that's the point. You need a critical mass of people buying into something. With LLMs, you just need ONE person with ONE model and a modest enough hardware.
>Here’s a concise and thoughtful response you could use to engage with ako’s last point:
---
"The scale and speed might be the key difference here. While human-generated narratives—like religions or myths—emerged over centuries through collective belief, debate, and cultural evolution, LLMs enable individuals to produce vast, coherent-seeming narratives almost instantaneously. The challenge isn’t just the volume of ‘bullshit,’ but the potential for it to spread unchecked, without the friction or feedback loops that historically shaped human ideas. It’s less about the number of people involved and more about the pace and context in which these narratives are created and consumed."
No, the web is now full of this bot generated noise.
And even when only considering the tools used in isolated sessions not exposed by default, the most popular ones are tuned to favor engagement and retention over relevance. That's a different point as LLM definitely can be tuned in different direction, but in practice in does matter in terms of social impact at scale. Even prime time infotainment covered people falling in love or encouraged into suicidal loops by now. You're absolutely right is not always the best
The worst part is when the AI spits out dogshit results --people show up at lightspeed in the comments to say how "you're not using it right" / "try this other model, it's better"
Anecdotally, the people I see the most excited about AI are the people that don't do any fucking work. I can create a lot of value with plain ol' for loop style automation in my niche. We're stil nowhere near the limit of what we can do with automation, that I don't give a fuck about what AI can do. Bruh in windows 10 copy and fuckin paste doesn't work for me anymore, but instead of fixing that they're adding AI
LLMs help a lot of users with making FOR loops and things like that. At least it's been the case for me, I'd never tried to use PowerShell before but with a bit of LLM guidance was able to cobble together some useful (for me) one-liner commands to do things like "use this CSV of file names and pixel locations, and make cropped PNG thumbnails of these locations from these images".
Stuff like that which regular users often do by hand, they can ask an LLM for the command (usually just a few lines of a scripting language if they only know the magic words to use).
My wife and I are both paid to work on AI products and we both think the whole thing’s only sorta useful in-fact. Not nothing, but… not that much, either.
I’m not worried about AI taking our jobs, I’m worried about the market crash when the reality of the various failed (… to actually reduce payroll) or would’ve-been-cheaper-and-better-without-AI initiatives the two of us have been working on non-stop since this shit started break through the hype of investment and the music stops.
It's been three years of amazing use cases and discoveries, and in those same years we got things like Ozempic. You can be skeptical of all the hyped things that are said that may be exaggerated without negating the good side.
imo don't waste your time for coding with Gemini 3. Perhaps worth it if it's something Claude's not helping with, as Gemini 3's reasoning is very good supposedly.
You could trust the expert analysis of people in that field. You can hit personal ideologies or outliers, but asking several people seems to find a degree of consensus.
You could try varying tasks that perform complex things that result in easy to test things.
When I started trying chatbots for coding, one of my test prompts was
Create a JavaScript function edgeDetect(image) that takes an ImageData object and returns a new ImageData object with all direction Sobel edge detection.
That was about the level where some models would succeed and some will fail.
Recently I found
Can you create a webgl glow blur shader that takes a 2d canvas as a texture and renders it onscreen with webgl boosting the brightness so that #ffffff is extremely bright white and glowing,
Produced a nice demo with slider for parameters, a few refinements (hierarchical scaling version) and I got it to produce the same interface as a module that I had written myself and it worked as a drop in replacement.
These things are fairly easy to check because if it is performant and visually correct then it's about good enough to go.
It's also worth noting that as they attempt more and more ambitious tasks, they are quite probably testing around the limit of capability. There is both marketing and science in this area. When they say they can do X, it might not mean it can do it every time, but it has done it at least once.
> You could trust the expert analysis of people in that field
That’s the problem - the experts all promise stuff that can’t be easily replicated. The promises the experts send doesn’t match the model. The same request might succeed and might fail, and might fail in such a way that subsequent prompts might recover or might not.
That's how working with junior team members or open source project contributors goes too. Perhaps that's the big disconnect. Reviewing and integrating LLM contributions slotted right into my existing workflow on my open source projects. Not all of them work. They often need fixing, stylistic adjustments, or tweaking to fit a larger architectural goal. That is the norm for all contributions in my experience. So the LLM is just a very fast, very responsive contributor to me. I don't expect it to get things right the first time.
But it seems lots of folks do.
Nevertheless, style, tweaks, and adjustments are a lot less work than banging out a thousand lines of code by hand. And whether an LLM or a person on the other side of the world did it, I'd still have to review it. So I'm happy to take increasingly common and increasingly sophisticated wins.
Junior's grow into mids, and eventually into seniors. OSS contributor's eventually learn the codebase, you talk to them, you all get invested in the shared success of the project and sometimes you even become friends.
For me, personally, I just don't see the point of putting that same effort into a machine. It won't learn or grow from the corrections I make in that PR, so why bother? I might as well have written it myself and saved the merge review headache.
Maybe one day it'll reach perfect parity of what I could've written myself, but today isn't that day.
I wonder if that difference in mentality is a large part of the pro- vs anti-AI debate.
To me the AI is a very smart tool, not a very dumb co-worker. When I use the tool, my goal is for _me_ to learn from _its_ mistakes, so I can get better at using the tool. Code I produce using an AI tool is my code. I don't produce it by directly writing it, but my techniques guide the tool through the generation process and I am responsible for the fitness and quality of the resulting code.
I accept that the tool doesn't learn like a human, just like I accept that my IDE or a screwdriver doesn't learn like a human. But I myself can improve the performance of the AI coding by developing my own skills through usage and then applying those skills.
> It won't learn or grow from the corrections I make in that PR, so why bother?
That does not match my experience. As the codebases I've worked with LLMs on become more opinionated and stylized, it seems to to a better job of following the existing work. And over time the models have absolutely improved in terms of their ability to understand issues and offer solutions. Each new release has solved problems for me that the previous ones have struggled with.
Re: interpersonal interactions, I don't find that the LLM has pushed them out or away. My projects still have groups of interested folk who talk and joke and learn and have fun. What the LLMs have addressed for me in part is the relative scarcity of labor for such work. I'm not hacking on the Linux Kernel with 10,000 contributors. Even with a dozen contributors, the amount of contributed code is relatively low and only in areas they are interested in. The LLM doesn't mind if I ask it to do something super boring. And it's been surprisingly helpful in chasing down bugs.
> Maybe one day it'll reach perfect parity of what I could've written myself, but today isn't that day.
Regardless of whether or not that happens, they've already been useful for me for at least 9 months. Since O3, which is the first one that really started to understand Rust's borrow checker in my experience. My measure isn't whether or not it writes code as well as I do, but how productive I am when working with it compared to not. In my measurements with SLOCCount over the last 9 months, I'm about 8x more productive than the previous 15 years without (as long as I've been measuring). And that's allowed me to get to projects which have been on the shelf for years.
I think they get to that a couple of paragraphs later:
> The idea was good, as were many elements of the execution, but there were also problems: some of its statistical methods needed more work, some of its approaches were not optimal, some of its theorizing went too far given the evidence, and so on. Again, we have moved past hallucinations and errors to more subtle, and often human-like, concerns.
Well, that's why people still have jobs but I appreciate the idea of the post that the neat demo was a coherent paragraph or silly poem. The silly poems were all kind of similar, not very funny, and the paragraphs were a good start but I wouldn't use them for anything important.
Now the tightrope is a whole application or a 14 page paper and the short pieces of code and prose are now professional quality more often than not. That's some serious progress.
The author actually discusses the results of the paper. He's not some rando but a Wharton Professor and when he is comparing the results to a grad student, it is with some authority.
"So is this a PhD-level intelligence? In some ways, yes, if you define a PhD level intelligence as doing the work of a competent grad student at a research university. But it also had some of the weaknesses of a grad student. The idea was good, as were many elements of the execution, but there were also problems..."
I think the point is we’re getting there. These models are growing up real fast. Remember 54% of US adults read at or below the equivalent of a sixth-grade level.
Education is not just a funding issues. Policy choices, like making it impossible for students to fail which means they have no incentive to learn anything, can be more impactful.
As far as I understand it, the problem isn’t that teachers are shit. Giving more money would bring in better teachers, but I don’t know that they’d be able to overcome the other obstacles
> Giving more money would bring in better teachers, but I don’t know that they’d be able to overcome the other obstacles
Start with the easiest thing to control? Of giving more money and see what it does?
We seem to believe in every other industry that to get the best talent pay a high salary salary, but for some reason we expect teachers to do it out of compassion for the children while they struggle to pay bills. It's absurd.
Probably one of the single most important responsibilities of a society is to prepare the next generation, and it pays enormous return. But because we can't measure it with quarterly profits we just ignore it.
The rate of return on providing society with as good education is insane.
I think you need to research the issue more. Teachers are well remunerated in most states. Educational outcomes are largely a function of policy settings. Have a look at the amazing turnaround in literacy rates in Mississippi after they started teaching phonics again.
I date a lot of teachers. My last one was in the San Ramon (CA) Valley School district, she makes about $90k a year at 34 years old.
Talking to her basically makes me want to homeschool my kids to make sure someone like her isn't their teacher.
Paying teachers more won't do ANYTHING until we become a lot more selective about who gets to become and stay a teacher. It can't be like most government jobs where getting it is like winning the lottery and knowing you can make above market money for below market performance.
There is so much wrong with this. You cannot judge the class of teachers based on a small sample of your taste in women. You didn't actually communicate anything materially wrong with her. You listed a high income area to make us think teachers are overpaid but we have no insight by default into median income in the area or her qualifications.
Lastly its entirely impossible to attract better candidates without more money its just not how the world works.
For reference the median household income in san ramon is about 200k so 2 teachers would be below average. A cop with her experience in the same town makes 158k
I personally am not of the belief that anyone making under $90k a year is dumb. I believe if you were selective, you could take smart motivated people from other industries that don't pay much but still have smart employees, and have them do a great job teaching.
I do talk to actual teachers at many social events, and IMO they are a joke. Maybe it's hard to get this across in short messages.
Maybe take a look at reading and math proficiency rates... And then add in the fact that many kids propping up those stats are basically part time home schooled by parents after school and on the weekend to makeup for the lacking teachers.
Its interesting to hear you say that you date a lot of teachers while simultaneously holding this view of their level of competence. Or just not the ones you date?
If teachers made as much as half the people on this site, perhaps things would be better. 90k in San Ramon is more or less the median wage [1]. It's not _that_ much money.
Who knows? Maybe with the way AI is going that will be considered a lot of money compared to what people earn on this site.
As in what people generally earn on this site will crash way down and be outsourced to these models. I'm already seeing it personally from a social perspective - as a SWE most people I know (inc teachers in my circle) look at me like my days are numbered "cause of AI".
When I said government employees make above market, I didn't mean for the general area average.. I meant for the work they do.
Should a city landscape truck driver make $250k because his truck drives around a rich town? No, he should make what other people in this kind of industry make.
This is so basic that I feel I shouldn't need to say it, but you can't be selective if you don't pay. You take what you get.
The reason teaching became largely a women's profession when they used to be exclusively men is because we wanted to make education universal and free so we did that by paying less, and women who needed to work also had to take what they could get. The reason it has become a moron's profession is because we have made it uniquely undesirable. If you think that teachers should be amazing and imminently qualified and infinitely safe to have around children, pay them like programmers.
Instead, the middle-class meme is to pay them nothing, put them in horrible conditions, and resent them too. Typical "woman's work" model.
>The reason teaching became largely a women's profession when they used to be exclusively men is because we wanted to make education universal and free so we did that by paying less, and women who needed to work also had to take what they could get.
Do you have any source on the assertion that being a teacher used to pay more? Because to my knowledge it has never been a high paying profession.
I guess the problem isn't only the pay, it's the opportunity cost which only a certain kind of people are willing to pay for the whole career. If you select those people out... you're left with zero candidates.
It's not just investing in education, it's using tools proven to work.
WA spends a ton of money on education, and on reading Mississipi, the worst state for almost every metric, has beaten them.
The difference?
Mississipi went hard on supporting students and using phonics which are proven to work. WA still uses the hippie theory of guessing words from pictures (https://en.wikipedia.org/wiki/Whole_language) for learning how to read.
Because education alone in a vacuum won't fix the issues.
Even if the current model was working, just continuing to invest money in it while ignoring other issues like early childhood nutrition, a good and healthy home environment, environmental impacts, etc. will just continue to fail people.
Schooling alone isn't going to help the kid with a crappy home life, with poor parents who can't afford proper nutrition, and without the proper tools to develop the mindset needed to learn (because these tools were never taught by the parents, and/or they are too focused on simply surviving).
We, as a society, need to stop allowing people to be in a situation where they can't focus on education because they are too focused on working and surviving.
A lot of that funding in the US goes to pay teachers money they then use to pay for health insurance -- which in other countries is often provided by the tax base at large and not counted as an education expense.
That's half true. You have to think about cost of living, you can't just compare across the globe like that. And especially opportunity cost. In the US, teacher pay lags behind similarly educated professionals.
But you're right after a certain point other factors matter more than simple $ per student. Unfortunately one of those factors is teacher pay <=> teacher quality.
From the teacher's I've talked to, it's teacher work conditions related to student behavior that are creating more problems than anything else.
Disruptive students in particular who negatively impact everyone around them but for whatever reason, are frequently not removed from the environment. It's also driving a lot of good teachers into retirement.
When you see clusters of poor performance, my guess is that it's associated with regional policy creating a poor environment rather than a total absence of quality teachers.
Literally look at any education chart and it's straight up better than wage growth for the last 70 years.
Further, the statement is about as nuanced as "the universe is just atoms". For example, I come from New Orleans where since Katrina they have effectively been 100% Charter schools (that's privatized). It has been a total disaster as not only did it not change literally any statistic for the better, it totally wrecked the local policy atmosphere. Now that shit is in 30 other states. Those "schools" get the same amount of funding (sometimes more!) and are worse in literally every meaningful measurement for society.
What measurements show the charter schools are worse?
Locals demand charter schools when the existing schools are already failing but the politics of a larger district make it impossible to meaningfully change anything.
It’s been a couple of years since I looked into Louisiana’s charters. When I last looked most of what I saw was political propaganda (from both proponents and opponents).
EDIT: I looked into it. Charters appear to experience the same performance spread (approximately) as district schools where negative performance is primarily associated with poverty.
And that makes the point…school funding is not the problem. The environment outside of school for the child is the problem. Pumping money into the schools isn’t going to get the benefit because it can’t affect outside factors. Money is better allocated elsewhere.
Relevant excerpt:
> Older studies align with this nuance: A 2013 analysis found 86% of Louisiana charters outperforming peers in reading/math, with spillover benefits. But a 2023 legislative audit linked poor results to poverty—71% of students are economically disadvantaged statewide, and concentrations above 80% predict lower scores. Notably, 85 of 138 rated charters earned D’s or F’s, and some high performers enrolled fewer low-income students than legally required.
It's pretty clear that while spending is a factor, it's probably not the biggest one. The countries that seem to do best are those that combine adequate funding with real rigor in instruction.
I posted elsewhere you can't just compare across the globe like that. You have to think about cost of living and especially opportunity cost. In the US, teacher pay lags behind similarly educated professionals, which means they get stretched thin and the best with options will leave.
We're higher paying than a number of countries with higher cost of living that (whether fairly or unfairly) pay lower than us.
I stand by my assertion. I don't think our per pupil spending is the major bottleneck in our performance. I think our educational system needs fundamental reform (just like everything else in this country)
> While U.S. teachers make 58% of their counterparts’ salaries, Finnish teachers make 92% of the salaries of similarly educated professions. This trend follows with other countries ranked highly in the World Happiness Report. Teachers in Denmark (ranked #2 in World Happiness) make 81% of their counterparts’ salaries and teachers in Sweden (ranked #4) make 74% of their counterparts’ salaries.
I mean, I don't deny that teachers are paid less compared to other fields, but that is actually pretty universal among occupations that provide the worker with a higher sense of purpose. You can see the same thing in social work, the non profit sector and elsewhere. Whether that's truly just is an entirely different question than 'is there a direct relationship between teacher pay and student achievement' and looking at all other sources I've provided, there clearly is not.
I'm not from the US and I think that attitude is fucked up. You'll get your wish -- the US has been steadily dropping on the lists of "World's Happiest Countries"[1]. But luckily I don't need to do anything. Nature will teach you what a simple text box cannot. Eventually you guys will ruin all your important institutions & become deeply unhappy & hit rock bottom & start meditating or something.
[1] https://data.worldhappiness.report/chart -- Fit a line and you can extrapolate by ~2030 China will be a better place to live. That's really not that far away. That attitude is not "universal".
New Mexico (where I live) is dead last in education out of all 50 states. They are currently advertising for elementary school teachers between 65-85K per year. Summers off. Nice pension. In this low cost of living state that is a very good salary, particularly the upper bands.
In WA they always pass levies for education funding at local and state level however results are not there.
Mississipi is doing better on reading, the biggest difference being that they use phonics approach to teaching how to read, which is proven to work, whereas WA uses whole language theory (https://en.wikipedia.org/wiki/Whole_language), which is a terrible idea I don't know how it got traction.
So the gist of it, yes, spend on education, but ensure that you are using the right tools, otherwise it's a waste of money.
First time hearing of whole language theory, and man, it sounds ridiculous. Sounds similar to the old theory that kids who aren't taught a language at all will simply speak perfect Hebrew.
I almost agree, but too many people will take that to mean “we need to do more with less”. It’s a feature of capitalism. Teachers are stretched thin in most places, that’s always the main problem. Are WA teachers compensated about the same as other similarly educated professionals? As cops?
Hire smart motivated people, pay them well, leave them alone, they’ll figure this one out. It’s not hard, anyone can google what Finland does.
> WA teachers compensated about the same as other similarly educated professionals
WA teachers are among the best salaries in the country for being a teacher (within top 5). You start at around 84k$ I think, 90k$+ if you have a masters degree, at least in Seattle, and it can scale up to 150k$ with enough seniority, as well as pension plan.
> Hire smart motivated people, pay them well, leave them alone, they’ll figure this one out. It’s not hard, anyone can google what Finland does.
The problem is not the teachers themselves, it's what the system tells them to teach. You can have the best teacher in the world, but if they use BS curricula students will unfortunately learn BS.
Think about it, you can have brilliant engineers, but an idiot ceo, and the company will fail despite the engineers.
What I'm hearing is "teachers just outside Seattle are doing great, but inside Seattle and the rest of America, they're really not." That's the local cost of living set by the tech sector.
In my own social/family circle, there’s no correlation between net worth and how someone leans politically. I’ve never understood why given the pretty obvious pros/cons (amount paid in taxes vs. benefits received)
That's interesting b/c I see it very obviously in mine with the partial exception of myself. The more professional and private sector their job or spouse, the more conservative they are. E.g a real estate lawyer is conservative, a lawyer for the state is liberal, a software engineer is a communist, and the musicians are libertarians or socialist-lite.
Professional or artisanal work are petit bourgeois positions, so are flexible in their outlook regardless of income.
If they own their own land or equipment it makes more sense. It's their relationship to production that is the driving force, but if they are not self-employed and don't own their own equipment it is a little more of an interesting situation.
The people most vociferously for conservative values are middle class, small business owners, or upper class, though the true upper class are libertine (notice who participated in the Epstein affair). The working class is filled with all kinds of very diverse people united by the fact they have to work for a living and often can't afford e.g. expensive weddings. Some of them are religious, a whole bunch aren't. It's easy to be disillusioned with formal institutions that seem to not care at all about you.
Unfortunately, a lot of these people have either concluded it is too difficult to vote, can't vote, or that their votes don't matter (I don't think they're wrong). Their unions were also destroyed. Some of them vote against their interests, but it's not clear that their interests are ever represented, so they vote for change instead.
By policy changes giving unions less power, enacted by politicians that were mostly voted for by a majority, which is mostly composed of the working class. Was this people voting against their interests? (Almost literally yes, but you could argue that their ideological preference for weaker unions trumps their economic interest in stronger unions.)
You don't need an educated workforce if you have machines that can do it reliably. The more important question is: who will buy your crap if your population is too poor due to lack of well paying jobs? A look towards England or Germany has the answer.
Unfortunately, people are born with a certain intellectual capacity and can't be improved beyond that with any amount of training or education. We're largely hitting peoples' capacities already.
We can't educate someone with 80 IQ to be you; we can't educate you (or I) into being Einstein. The same way we can't just train anyone to be an amazing basketball player.
From what I've read, IQ is one of the more heritable traits, but only about 50% of one's intelligence is attributable to one's genes.
That means there are absolutely still massive benefits to be had in trying to ensure that kids grow up in safe, loving homes, with proper amounts of stimulation and enrichment, and are taught with a growth, not a fixed potential mindset.
Sad to say, but your own fixed mindset probably held you back from what you could truly achieve. You don't have to be Einstein to operate on the cutting edge of a field, I think most nobel prize winners have an iq of ~ 120
This is extremely not settled science. Education in fact does improve IQ and we don't know how fixed intelligence is and how it responds to different environmental cues.
Thinking that speech recognise is a solution to the illiterate is like thinking that low code tools can replace traditional programming tools. The bottleneck is and has always been the cognitive capacity limits of your average human. No interface can solve the issue of humans being illiterate
You don't use it that way. You use it to help you build and run experiments, and help you discuss your findings, and in the end helps you write your discoveries. You provide the content, and actual experiments provide the signal.
Like clockwork. Each time someone criticizes any aspect of any LLM there's always someone to tell that person they're using the LLM wrong. Perhaps it's time to stop blaming the user?
Why would their response be appropriate when even the creators of the LLM doesn't clearly state the purpose of their software, yet alone instruct users how to use it? The person I replied to said that this software should be used yo "help you build and run experiments, and help you discuss your findings, and in the end helps you write your discoveries" - I dare anyone to find any mention of this workflow being the "correct" way of using any LLM in the LLM's official documentation.
You wouldn't use a screwdriver to hammer a nail. Understanding how to use a tool is part of using the tool. It's early days and how to make the best use of these tools is still being discovered. Fortunately a lot of people are experimenting on what works best, so it only takes a little bit of reading to get more consistent results.
What if the company selling the screwdriver kept telling you your could use it as a hammer? What if you were being bombarded with marketing the hammers are being replaced by screwdrivers?
You can recognise that the technology has a poor user interface and is wrought with subtleties without denying its underlying capabilities. People misuse good technology all the time. It's kind of what users do. I would not expect a radically new form of computing which is under five years old to be intuitive to most people.
For what it's worth I have been using Gemini 2.5/3 extensively for my masters thesis and it has been a tremendous help. It's done a lot of math for me that I couldn't have done on my own (without days of research), suggested many good approaches to problems that weren't on my mind and helped me explore ideas quickly. When I ask it to generate entire chapters they're never up to my standard but that's mostly an issue of style. It seems to me that LLMs are good when you don't know exactly what you want or you don't care too much about the details. Asking it to generate a presentation is an utter crap shoot, even if you merely ask for bullet points without formatting.
I bet they were talking about how people didn't do long division when the calculator first came out too. Is using matlab and excel ok but AI not? Where do we draw the line with tools?
Apparently not. This is the most perfect example I've seen of "I can recite it, but I don't understand it so I don't know if it's really right or not" that I've seen in a while.
Truth is you still need human to review all of it, fix it where needed, guide it when it hallucinate and write correct instructions and prompts.
Without knowledge how to use this “PROBALISTIC” slot machine to have better results ypu are only wasting energy those GPUs need to run and answer questions.
Majority of ppl use LLMs incorrectly.
Majority of ppl selling LLMs as a panacea for everyting are lying.
But we need hype or the bubble will burst taking whole market with it, so shuushh me.
Then it goes on, "After a couple of vague commands (“build it out more, make it better”) I got a 14 page paper." I hear..."I got 14 pages of words". But is it a good paper, that another PhD would think is good? Is it even coherent?
When I see the code these systems generate within a complex system, I think okay, well that's kinda close, but this is wrong and this is a security problem, etc etc. But because I'm not a PhD in these subjects, am I supposed to think, "Well of course the 14 pages on a topic I'm not an expert in are good"?
It just doesn't add up... Things I understand, it looks good at first, but isn't shippable. Things I don't understand must be great?