In terms of AI, we've seen even here on HN everything from mathematical problems that remaind unsolved, being solved, mathematical proofs being used to disprove theories, heck we even learned more about alzheimers, new antibiotics, precision targeting in oncology, using AI to flag healthcare anomalies in imaging. The benefits are easy to miss, but they're snowballing into place, there's definitely an explosion of useless crap, but you have to look for the real things and you will come to find, that AI is giving us things we otherwise either might not have discovered or wouldn't have within our lifetimes.
Don't get me wrong. I love LLMs and use them myself. But the biggest gain for me is easier context switch and text manipulation. It's not the: replace X with a bunch of LLMs every CEO is dreaming of. So yes, you have higher productivity, but is the eval of those companies legit? x doubt.
By the time you see the applications, the market will have moved on to value the next set of future cash flows.
If the market only valued the obvious, investors would jump in to buy the price up, until it met the average expectations.
The market might be wrong, but the question is not: "Have you yet to see?", but rather, "What do you see in the next three to five years?"
Otherwise, how could investors ever invest in a startup?
Startups never have revenues to justify their initial valuations.
It's a bet on the future.
Investors are future looking.
Consumers are present looking.
We didn't see LLM harnesses coming even two years ago. Now they generate billions per month.
Investors can't wait until reality materializes to make their estimations of the future.
That's why investing is hard.
You have to try to predict the future.
Sir, this is a casino/Keynesian Beauty Contest.
Markets value what the market participants think the other participants will value. On occasion, this intersects with reality.
I find it interesting that using lines of code as a metric is making a comeback.
How many millions of emails do you think are composed using ChatGPT? How many legal briefs were reviewed by AI? How many businesses use AI generated art? How many kids do their homework using ChatGPT?
The GP is arguing that AI has struggled to replace humans, but in so many roles AI is doing the heavy lifting and humans are copying its output.
The homework "help" industry (i.e. paying for answers) is dead. Chegg stock fell 99% because of ChatGPT.
Stock photography is rapidly dying, nobody will pay for shutterstock when ChatGPT can generate a passable image for free.
ChatGPT is killing studio photography, it can generate great looking studio photos for free.
Same with basic graphic design / custom art commissions.
SEO / copywriting has been almost fully replaced by AI. Companies no longer pay writers to churn out SEO slop, and now the web is full of AI generated SEO spam.
Customer service as a job is dying and is rapidly being replaced by AI chatbots.
I can go on, but these are the major ones.
On top of that, you are showing another stark bias in considering the US experience as the global experience. It is not, and education in particular works way differently, aka, it's not a business wild west.
Cognitive surrender in writing emails is another shaky ground: do you honestly think that AI's worth the tens of trillion the tech bros are claiming it'll be worth as a glorified email-maker?
I will add that my point still stands. If you say this:
>>ChatGPT is killing studio photography, it can generate great looking studio photos for free. Same with basic graphic design / custom art commissions.
the only point you're proving is that you don't understand shit about photography as a business, nor about design as a business. AI is being rapidly integrated, for sure, but it has not upended those industries, and the average mediocrity it produces (because of its very nature) is not even close to replacing what you claim it is.
You asked about data, and I have it, and here it is: Chegg's CEO explicitly stated in their earnings call that ChatGPT was directly responsible for their collapse. Chegg stock fell 99%. You can verify this fact yourself. ChatGPT led to the near-destruction of a $14 billion company.
On photography and design: your counterargument is entirely assertion. You're claiming I don't understand those industries without demonstrating that you do. There is demonstrable fact AI has absolutely upended both industries. AI has gutted the commodity tier that constitutes the vast majority of revenue volume. Product shots, website graphics, social media content, marketing material. AI produces this content for free, at a quality so good that millions of people don't realize it's created by AI. You only consider the high-end, professional market, which so far has been relatively untouched.
Your only valid criticism is that my argument is US-centric. Fair enough. But ChatGPT has 700 million users globally, and you've produced zero evidence that non-US markets are insulated from the trends happening in the US.
Chegg shares drop more than 40% after company says ChatGPT is killing its business https://www.cnbc.com/2023/05/02/chegg-drops-more-than-40perc...
Otherwise Github wouldn't have 14% down time in the last 3 months.
What is _the proof_ if all the proofs are not _proofs_?
I don't babysit my LLM based services which are used by coaches and clients around the world. One of my LLM based solution get 30-4k daily hits and I have users coming back on the regular to use it. without babysitting, doing things that would take them hours of manual work and research.
I don't babysit the developers I work with and our clients, which both use LLM's themselves and at scale with their clients, serving all kinds of LLM powered services to millions of users worldwide.
You are not "seeing" the large adoption because:
- The technology is "a few years old" in its usable state - The corporate adoption cycle is slow - You have to understand the technology to use it in a good way, which most corporate devs and PM's do not
So it will take a bit for the "obvious" adaptation on large scale.
But you won't "know" when the large adoption happens.
Silent inference is growing every day, and that is what real adoption looks like - not an LLM being in your face chatbox, but running in the background, sorting, finding, fixing things, aligning data, figuring out analytics, tuning the ads, cleaning the datasets.
What a story this is
I am a radiologist and researcher predominately focused on AI.
You could also look at the market, one of the biggest players, Paige, was acquired for about 30% of the money they raised.
Anecdotally, my practice has most FDA approved AI deployed as we are an evaluation site and very rarely is the AI result useful. Over the past few months we have been cancelling contracts as these cost quite a lot of money (in some cases eating >50% of the study interpretation cost) for little to no benefit and a LOT of noise.
Do you think this will result in more routine/boring/tedious tests? Is the bottleneck on these things the human time to analyse them?
For some things, like 3D volume segmentation of structure or disease (e.g. CVA/stroke volume, cardiac muscle mass, iron quantification) the bottleneck is the time it takes so we currently use approximations like single longest dimension, circular regions of interest, etc. AI will dramatically increase accuracy allowing for more accurate treatment and easier large scale research with quantitative endpoints.
Other things people think of like detection of aneurysms, fracture, lung nodules are not “hard” but AI has already added and will continue to add the second-reader benefit which will reduce detection errors. For this category the clinical benefit is as of yet unclear and we know that increased detection does not necessarily translate into improved patient outcomes and can in fact make them worse from over-diagnosis which means investigation related harms and over-treatment.
We were already in a phase of “over detection” in much of radiology with advances in imaging technology so the incremental benefit of current AI remains to be seen and I personally think is going to be much more limited. I had a case recently where a 2 mm brain aneurysm was missed on 3 CT scans over 10 years but was picked up by AI so now is being followed annually. This is too small to treat considering the risks and a serious argument could be made that 10 years of stability is proof enough that this is almost certainly clinically irrelevant for this patient.
Far more interesting areas of AI in imaging are in acquisition of acceleration (i.e. the medical equivalent of upscaling) which can dramatically decrease costs and increase accessibility as well as analyzing imperceptible features.
It may not be a popular take here but in my opinion the future of radiology is like what we see in software engineering today - a skilled human equipped with AI will outperform humans without AI and AI without humans, the latter of which we are still several years away from prototyping due to various technical hurdles.
> in my opinion the future of radiology is like what we see in software engineering today - a skilled human equipped with AI will outperform humans without AI and AI without humans
I suspect this will be the case across the board. It's a useful tool, but it's just a tool. It's not a replacement.
They will never beat the human instinct tho, but they can be great tools sometimes. Unfortunately, LLMs mostly produce garbage.
In real life pathology is a spectrum not a binary and physicians are not trained to be 100% accurate instead optimizing sensitivity and specificity considering pretest probability as well as the harms of overdiagnosis and under diagnosis for a given scenario.
For something like melanoma which is relatively easy to diagnose with a superficial, extremely low risk skin biopsy and where early staging dramatically improves outcomes you would want to design around overcalling (high sensitivity) rather than maximize accuracy given the significant harms with false negatives and minimal harms with false positives.
An AI may be more accurate at classifying melanoma/not melanoma but if it does not meaningfully improve on the clinical threshold of biopsy/no biopsy or result in less biopsies that accuracy is wasted and may even be detrimental.
Note: I am just using this as an example to illustrate the considerations.
Essentially the cutting edge reaches up to 99% of human performance on the task it is trained, which is good enough for triage but not for a final diagnosis. However, magic sometimes happens when you train a model to detect something, which you already know is there, on an examination that is cheaper, faster or less invasive than the human"gold standard". Conveniently, this dataset exists since it's common to first do a cheap examination like an X-ray, and then escalate if nothing is found (or if something is found that you want to see better, or a number of other possibilities).
Examples of AI outperforming humans like this includes AI detecting sacral fractures on x-rays better than radiologists (who normally take a CT to conclusively exclude it), detecting potential precursors to pancreatic cancer on non-contrast CTs (where contrast or an MRI is usually required) and detecting an occluded coronary artery on an ECG without the archetypical "ST-elevation changes".
See the link below for references: https://pmc.ncbi.nlm.nih.gov/articles/PMC9478257/ https://www.nature.com/articles/s41591-023-02640-w https://rebelem.com/a-winning-hand-in-cardiology/
So AI, as a general rule, doesn't usually match or exceed the upper bound of the "gold standard" medical performance. But it tends to carry the quality of the upper bound downwards towards the faster, less expensive and invasive methods. In some cases, like in the case of EKGs, that's huge. In some cases it saves time, in some cases it decreases miss rates from tired radiologists or triages their review feed. And in some cases it's not very useful.
LLMs doesn't come close to specialized radiology models at the moment, because LLMs are more about applying knowledge than creating new correlations. Of course that's also hugely useful, but that's a bit of a different topic to unpack.
A self driving car doing better than a drunk on the freeway doesn't reassure me that it'll do better than sober me in a snowstorm.
I also question if the kind of person who actually drives while drunk - knowing perfectly by thousand of society inputs and peer pressure that it is wrong - will care enough to buy a self-driving car.
A whole lot of doctors, if not most, didn’t pick their profession out of an interest in medicine…
Also, keep in mind that a stock price discounts expected future cash flows. Is it likely that SpaceX will have a near-peer competitor within a few years? No, it's not, and that market share is being priced-in.
If there exists sufficient demand for the product of space launches then it's probably reasonable to expect their to be a near-peer competitor soon, but that's only if SpaceX were to be profitable, which it isn't, even with the subsidization by Starlink on the order of many billions.
Space is not that easy. Even with unlimited money, it'll probably take 10 years to build a rocket like starship. Going from nothing to orbit needs a lot of money but more money doesn't make that faster.
But other than that, yeah - outside of China, progress has been horrendously slow & Blue Origin, the only other US company that demonstrated a partially reusable rocket just had a devastating pad explosion, destroying one of their 2 rockets and their only launchpad.
This can't be treated as meaningful, given other projections and goals (Mars colony, etc.).
Although realistically this will be built from lunar materials, you still need to lift a lot of mass to build the necessary industrial processing and mass drivers to launch it from the Moon to some Lagrange point.
And there are many other useful space megastructures that can be built in space from common materials, like giant solar arrays beaming power down via microwaves: https://en.wikipedia.org/wiki/Space-based_solar_power
Most of these proposals date from even 1980s.
Were we struggling to do this before? Was the overall percentage reduction in costs? Was some other achievement held back because we couldn't accomplish this? What is now enabled?
> to get any payload into space.
A limited set of payloads into space. No vehicle can get "any payload" to space at a fixed price.
> The benefits are easy to miss,
You've listed a bunch of reasons to publish papers. What is the actual ground level change that's occurred? Are those antibiotics produced? Do they actually work just as predicted? Why is that first world problems are exclusively listed but basic problems like world hunger are never even approached?
> or wouldn't have within our lifetimes.
And your life, your actual life, benefits, how?
We literally couldn't.
> Was the overall percentage reduction in costs?
Starship will bill NASA 1/20th what SLS does.
> What is now enabled?
LEO. Artemis. Out of all of these companies, being confused about SpaceX is super weird.
But now he's also trying to get the indexes to pay for the giant cash fire called X.ai and the far right huddle Twitter too.
I have zero interest in owning anything of either of those companies.
Yes. The thing that’s going public is almost entirely an AI play.
Is that before or after the program achieves profitability?
Starlink has made connectivity cheaper and more available. Earth imaging has made various food production processes more efficient. Weather forecasts have become more accurate.
If you’ve genuinely missed the massive economy that LEO has become, it will be a fun thing to catch up on.
Yeah that's working out great for the average American isn't it (https://natlawreview.com/press-releases/2026-consumer-trust-...)
> Earth imaging has made various food production processes more efficient.
I'm not even going to bother sourcing the fact that food prices have only massively gone up negating any gains in productivity. The average American struggling to buy basics like eggs and meat aren't feasting on more efficient food production.
> Weather forecasts have become more accurate.
I'm sure the growing homeless population is happy to know they can better predict the weather they'll be sleeping in.
This is all totally worth supporting a nazi billionaire
Yeah. It did. My neighbour’s rates went up. He switched to Starlink.
> not even going to bother sourcing the fact that food prices have only massively gone up negating
This is like arguing fertilisers are useless because prices went up.
> homeless population
Not super relevant!
> all totally worth supporting a nazi billionaire
Nobody said that. But it doesn’t mean the benefits go away.
SpaceX’s main customer is Starlink. With that in mind: if Starlink takes over all the ISPs in the world its market value should be comparable to Comcast - $89 Billion.
It has massively improved both. The cost, resolution and frequency of imaging has decreased alongside launch cost.
> if Starlink takes over all the ISPs in the world its market value should be comparable to Comcast - $89 Billion
Why? Comcast isn't "all the ISPs in the world." (And Comcast doesn't get defence contracts to build and maintain military networks.)
Reusing rockets reliably rather than "throwing them away" is a great achievement and I'm surprised people have to justify it on HN
You can milk a cow only a set number of times!
What probability you assign to arrive at that expected value and how you adjust for risk is on you.
I haven't found anything out of LLM's that has improved my life. It was a fun little toy but could never find a use case. But clearly, your mileage varies greatly from mine. That's cool.
I just personally don't the use in more when what I think many need is less. But that comes from essentially this point of view - “Better than a thousand hollow words is one word that brings peace.” ― Buddha
I wouldn't say it "significantly improved my life" however. Everything AI has done for me right now is a "Nice to have" but it doesn't fulfill my needs.
What’s the long term plan? Make it up on margin? 100% tariffs on Chinese open weight models?
I don’t plan on pulling from my 401k for decades, so the long term plan is the part I care about.
- Significantly increased my productivity as a software engineer.
- Using it daily for Chinese-English translation. Significantly better than pre-LLM translation software. Also, great at teaching grammar, nuances, etc.
- General Q&A. Like "Googling" but much faster. This is probably the most common use case for me.
This is exactly the point that keeps coming up that folks are struggling to grasp, myself included. How are you measuring this? It certainly makes me feel productive, but I'm not sure I can confidently say it has actually made me more productive. It's made the easy stuff a no-brainer (e.g. boilerplate, simple logic) and the moderate stuff really hard. Never mind the hard stuff. Vetting the code has become a whole other job on its own. The only folks I've found who confidently claim it increases productivity appear to be online (and without evidence), because no one in person is willing to claim that and show it.
For me, the killer use case is debugging. I hate wasting time debugging something that should work except for mistakes, and now I do that probably 75% less than I used to because AI does it for me.
I don't know if it makes me that much more productive, but I certainly enjoy my work more not having to do as much tedious debugging, and it feels like I waste a lot less time doing it.
- a VST audio plugin
- a wedding website with RSVP functionality
- a relaxing game for my wife
At work, I've been able to build much more than I would have been capable of in the past. I'm a backend eng, and it allows me to build much much nicer frontends than I've ever been able to do in the past.
And before you tell me that the code is crap - it doesn't matter! It may or may not be good code, but it works and serves it's purpose very well. Anyways, I'm I'm not launching a rocket, or putting software into cars.
I've never been a developer. Dabbled in frontend web for a bit (HTML/CSS/JS, no large frameworks) and felt like if I really dedicated some time to learning how to code, I'd be pretty decent at it. It's always intrigued me, and I've always had an itch to build things, but just never found the time. I'm in marketing now - I own an agency.
Over the last 6 months since the coding models really began to step up and get good, I've built several dedicated apps to support my business:
-Profitability optimizer and forecaster based on unit economics and current ad efficiency.
-Creative strategy tool that ingests brand and product data and helps explore primary and secondary personas and emotional motivators.
-Reporting tool that processes natural language queries and connects to multiple data sources to fetch results. Can schedule reports to post directly to Slack or email.
All robust and hosted on Railway. Team members can use them. Clients can use them. OAuth via Google.
Would any of this have been possible for me before the rise of frontier LLMs? Absolutely not. Learning the frameworks alone would have taken me longer than it's taken to just... build. Rapidly build and deploy. Total game changer for me.
Oh - and I'm building a game on the side. LLMs know Godot.
Not everyone has the same requirements, skills, usage patterns, and outcomes. It's that simple.
I attempt a programming task with and without LLM assistance. The attempt with LLM assistance is pretty much always completed faster and cleaner.
Another example: https://news.ycombinator.com/item?id=43991777
You’re going to have to define productivity as it applies to software engineering. With LLMs we’ve primarily seen the number of PRs over time being discussed as a proxy for LoC, as well as the speed of bootstrapping a small project. None of these have a known correlation with economic output. They just feel good, to the programmer, their manager, or both.
> Using it daily for Chinese-English translation. Significantly better than pre-LLM translation software. Also, great at teaching grammar, nuances, etc.
Yes dealing with language is the one area LLMs are actually designed for. But what’s the TAM for machine translation?
> General Q&A. Like "Googling" but much faster. This is probably the most common use case for me.
And now you’re missing any kind of traceability for the information that you “learn,” since it all gets spaghettified and then recombined into a pile of plausible slop with no attribution. Where before you had to do slightly more work to find the information you needed, now it’s available faster but you’re at complete mercy of literally 3 American companies plus the CCP for the accuracy of that information. Most people somehow seem happy with this arrangement.
I meant it in a colloquial way. I just get more done, faster.
> And now you’re missing any kind of traceability for the information
Modern LLM assistants provide sources and references. While it can sometimes be just "slightly faster", it can genuinely save hours of research on complex ones. Also the "slightly faster" can add up to hours saved with frequent use.
An LLM correctly diagnosed it, and figure out that we could treat them with Nutri-drench Sheep Supplement, since Tractor Supply was sold out of the chicken version, and they are very similar.
Of course it then immediately recommended we use hemp bedding that would kill them a different way, but the saleswoman sanity checked all of the above,
100% survival rate.
Everyone’s thriving. Chickens would follow the medical advice again, I guess.
Gemini also told me about some obscure procedures to fix my wedding paperwork after it’d been submitted with typos.
I don't understand this. It increased productivity of every developer in the western world, so it didn't really give you an advantage. Your output is more valuable, but your colleagues' output is more valuable too, and your competitors' output too, and so on. So you're doing more things at the same salary and it's not like your company or your employer is making more money than usual or awarding you more eoy bonus. If your "life-change" is "I'm writing more code" without any other advantage (and with the possible disadvantage of your role changing, or being at risk), why is it desirable?
Interpreting reports, avoiding drug interactions, or knowing when to seek medical care. And before people object- I can literally use the same LLM my doctor does to check these things, without waiting 2 weeks for an appointment.
I helped my parents work through bacterial culture results when my dad was hospitalized with sepsis, and had them ask their doctor for specific follow up tests.
I rebuilt my gas furnace and fixed my dishwasher with AI as an assistant.
Those aren't the fun parts tho. My favorite is touring art museums ancient historical sites with an LLM guide. It can give me a short academic essay about every artist, painting, or artifact. It can pull out details quirky stories about the history that I specifically would find interesting.
I cant recommend this enough. Its like visiting with a 10 PhD docents in art history.
How do you trust the placards under a piece of art?
The short answer is you accept that it isn't perfect and move on with life. I have found multiple errors in all of those things. Human tour guides are especially the worst at making things up.
Part of navigating life is dealing with imperfect information and uncertainty.
Just like with a friend, coworker, or spouse, you use your judgment and track records to decide when to trust what is being said based on subject matter and stakes.
Domain matters. I have found it good at history, but less trustworthy in others. For examle, the llm gave me a bunch of bogus advice as I repaired my dishwasher based on weather models that weren't accurate. There is also a lot of bad information on Reddit and Appliance blogs. Repairman are almost as bad as the tour guides, willing to lie straight to your face. I deal with it the same way.
does "das man" know they are part of the crowd?
Literally saved his dog's life.
Let me rephrase that to you: The vast, vast majority of people, even in the western world, even the white-collar part of the population, are not whales or power users of AI models.
I use ChatGPT daily. And I never spend more than $25/month. If I lost it, it would suck, but it would not affect my life significantly. I then see people spending $100 / day on Claude Code tokens, programmers in startups / tech companies rack up thousands a month in bills. These people are literally spending 100x more than me, a casual user.
Yeah, I suspect they follow some sort of whale economics - where a relatively small userbase (in the big picture) and providing them with a huge chunk of their revenue.
But still these companies are being valued as if they're some omnipresent companies which humanity simply can't live without.
No body who has a choice is using Grok
> Is Grok solving Erdos problems?
Mēh! At a slower rate than models a fraction of the price
The Grok app had over 100 million downloads in 2025, over 60 million active users, and generated $350 million in revenue. That’s a lot of people being forced to use it.
Eventually your employer benefitted too, from more & happier paying customers.
Finally you indirectly befitted as well - through continued employment, salary and bonuses and stock (if you own any).
Clients - I don't see anyone delighted that apps are better, or cheaper, or more secure. If anything, I see more enshittification, more half-baked ideas and more fear that security is worse now that we let AIs write almost all code.
Employers - They didn't really sell more or expanded their customer base. They would have, if they had the exclusive advantage, but now everyone has AI. They can cram more features in their software quicker, but so can their competitors, and AI is not magically opening any untapped market. If anything, everyone is now doing the same thing - trying to get their software on the AI train, with mediocre results so far.
You - did you benefit really? The job market is shit due to the death of ZIRP, the nature of the job itself is changing and there's a lot of uncertainty around. If anything, employees are now laid off more, not less, and salary and bonuses are not increased in any measurable way.
It looks like to me that we have to dance this particular dance because if we don't do we're left behind. That's fine, it happens every now and then. It might even be that in the future we will have tangible advantages from LLMs - better automated health care, better learning opportunities come to mind. That has to be demonstrated. But now, in year 2026, what's one advantage of AI? Having less and pricier RAM? Being able (and expected) to write more code in less time?
And when pushed all we get is another teaser of "Significantly increased my productivity"
Final sad note about Starlink: It is helping Ukraine to win the war. It makes their mid- and long-range drones almost impossible to jam. (Most short-range drones use fibre optics these days to avoid jamming.)
The more dollars there are, the more deeply in debt we are. If these were interpersonal debts where we all owe the dollars to each other such that they go away when whatever promise is eventually kept, that would be a tight knit society. But instead we're all indebted to the banks, so instead we have a lot of collateral at risk, and a lot of uncertainty about whether it's a stable arrangement.
If there isn't enough money to satisfy the asking prices set by the owners of these abstractions, then we can always go deeper into debt until there is. Or we could have a debt jubilee and let the prices re-settle to something more in tune with reality.
2. There's a potential to optimize a lot of economic activity in there.
Stored in pension funds in the hope that by the time the current working class goes to pension age, there is enough left.
I think these IPOs are going to mint tens of thousands of new millionaires or something. That, in turn, will generate massive tax windfalls for all levels of government.
> other than the ability to produce more crap?
This is a big "other than." (And to be clear, the jury is still out on whether AI will let us produce more in the long run.)
I think it’s very likely AI is a technical improvement. But there is still a chance it’s a small improvement being massively overbuilt.
There is going to be a well-deserved shitshow when these IPO proceeds start hitting real estate markets.
The only answer is to make it unacceptable socially, more costly economically (taxes, etc), or the third option which involves pitchforks (perhaps that also falls under "unacceptable socially") that I hope we can avoid at all costs. (is this the show you mention?)
Feels like folks used to understand the balance a bit better - but I think I made that up. This next governance cycle is going to be a trust-busting, wealth-confiscating one I think.
I think there will be a tremendous political opportunity in the next 6 months to capitalize on rage in cities against new tech wealth driving up housing costs.
Where? Rents and home prices are increasing in most American markets.
Starlink and Claude are both awesome and huge QoL improvements for me!
If you are upset about people spending their extra productivity and labor hours on poision and mental laxitives, i would mostly agree. This is a failure of culture to adapt to distratcions and shiny objects
And what's more crap exactly? it feels like your grasping at straws to take one set of things and associate them with others. yeah, lots of terrible products out there, lots of enshittification, lots of topics of discussion there. But AI and GPUs are being used in such a diverse way it is impossible to have one opinion on it all like how you're trying to.
I'm not even disagreeing (or agreeing with you), I'm just saying that's a lazy comment to make. if these companies making profits without paying taxes, that's a voter problem (not even politics, just people being shitty voters, self not excluded).
For everyone else who might think they have a better formed opinion on this topic, I only ask that you apply the same level of passion to how the US national debt is now 120% of the GDP. The government is fighting wars and printing money, devaluing your wealth, and indebting your country to previously unseen levels. At least the banks and VCs are using their money (unless they get a bail out again), not your actual tax money, and the tax money and wealth of generations of Americans. You have a president literally stealing billions of dollars in broad day light from literally you.
What you thought your life would improve? Didn't you hear, wages are only increasing, why don't you invest some of that sweet cash into @JumpCrissCross' fund, it'll be alright. What were you going to do with healthcare anyway?
A society should be judged by how it treats those at the bottom and by that metric our current society is pretty awful.
The vast majority of people I've known who have worked for minimum wage were much harder workers and frankly just much better humans (who happened to have less privileged starts in life) than the vast majority of people I've known who are financially secure.
But even if you don't believe they deserve more inherently, it would still be dumb for us to continue to let income inequality grow at the ridiculous rates it has been over the last 40 years. This pattern never turns out well for society.
1. The federal minimum wage is not the solution to any of your complaints.
A good portion of that[1] is what alot of people might call fake money--valuation inflation, etc. And global wealth, even just financial wealth, isn't quite as mobile across borders as one might assume. So marshalling a trillion dollars stateside is gonna make at least some moderate waves. Still, in the grand, global scheme of things a trillion dollars is a rounding error. A trillion isn't what it used to be, and there's trillions to be had even without any realized productivity gains from AI.
[1] I'm no financial analyst, but judging by the last few recessions and the overall trajectory over the past 30 years, I'd ballpark at most about 1/3 of that to go up in smoke if we had a severe downturn tomorrow. It's not all fake money. The whole world has industrialized over the past 30 years on a scale that is still unfathomable for most people today.