besterman23

> you’ll have to live in the world as it is instead of playing pretend in AI graphics land!

> you’ll be forced to love your wife for who she is and not her AI generated fake persona!

Seriously…?

Apparently this is some dystopia with or without the AI companies banning you from their services, yet somehow the big scary thing is not having open weight models.

The entire tech world needs to get a grip on reality, like the fact that this random Twitter fanfic gained any traction at all on this site is a massive indictment of the quality of discourse here.

I had an LLM tell me that I mattered once, which I know for objective fact is not represented in the training data.

What would be funny with LLMs, having been purposefully trained to be the best software creating things on earth, wind up inadvertently making software virtually valueless (because it can be made and copied so easily) and undermining the value of the companies that proliferated their use in the first place.

Well you’re not alone, I’m a little more stubbornly optimistic perhaps, but I feel your stress.

My comforting thoughts are, who is this all for, and what would happen if AI actually makes human labor redundant? Labs control the AI sure, but so much stuff is built around humans that it almost becomes comical to think it would be a bad outcome for a the average person.

Farms and land don’t cease to exist, houses/apartments don’t go up in flames instantly, people aren’t reduced to functionless sludge creatures as soon as they’re done being economic drivers. What’s the real plan? All the normal people die and a thousand or so chosen few sit around and watch AI videos and eat grapes until the heat death of the universe?

Nah, we’ll figure it out, perhaps it will be harder temporarily, and perhaps SWEs lose status before everyone else, but it will probably be okay overall.

I don’t think bluefirebrand is in the tribe of “everyone must have a job or die” so much as they’re in the tribe of “everyone says I must have a job or die”. Like yeah if I was forced at gunpoint to possess something or be ostracized from society then I too would be a little perturbed if someone made an automatic “take away the thing” device.

That’s something that I have been thinking about for a while now. Even prior to LLMs, many large companies have essentially been iterating on the same half a dozen ideas over and over again and there doesn’t seem to be much new coming out even post LLMs.

The most recent new things that LLMs have unlocked (regarding software dev) for us is reverse engineering and combining old games, unearthing decade old vulnerabilities, and helping root and debloat consumer hardware. Which are all cool and useful, but none of it being a “next great thing”.

Perhaps LLMs are really doing is highlighting how the software industry was already nearing its economic maturity and this just shifted the timeline from 2040 back to 2027-2030.

I get what you’re saying but I’m just not a fan of this type of argument. It always paints AI as this “in the future” thing which absolves any current criticisms or observations.

LLMs are great and definitely make you more productive, for some reason 493/500 firms haven’t been able to figure that out even though it’s trivially easy to provide employees with frontier models and it’s also trivially easy to use frontier models.

Which is why I say comparing it to personal computers in 1987 is not an apt comparison. That took redefining physical workspaces, new infrastructure, and new personnel which wasn’t easy to come by. Becoming a company that uses AI is just as easy (if not easier) as using any other SaaS.

I can’t speak for everyone, but I would intuitively venture to guess there would be some greater than marginal productivity benefits from say, a $200/m Claude sub for each employee in many organizations outside of tech.

Perhaps they’re all on the $20/m plan which is useless?

Sure it’s useful, but I’m asking who actually pays for this. Sort of a conflict of interest if you’re providing public testing for the companies paying you for the tests no?

Perhaps it’s purely for VC so they can judge which model is best? Also seems a little too conflict of interest-y, but that might just be too cynical.

This seems like a poor comparison, for any given company, benefitting from personal computing in 1987 was a significantly harder task than using AI tools in 2026 is.

The first requires a fundamental shift in not only how you work but expensive and complex infrastructure changes from the company itself just to make it possible (the first Mac for example would cost about $7000 per person in today’s money and would be outdated in maybe a year or two), an office building of The latter requires asking a subscription service to do a task for you on basically any computer connected to the internet.

Sorry I don’t mean to specifically point you out, I believe you’re being genuine.

However this comment got me thinking. Whats up with all the YC backed benchmarking companies? I know there’s only a few, but what is the business model for companies like Robocurve exactly?

This post feels really weird, DreamLabs isn’t some well known project like Anthropic or OpenAI and Dream-1 wasn’t really an awaited release.

But somehow this was pushed to the front page of HN before receiving a single comment with a title reminiscent of a major LLM release. Like I can only find 1 other reference historically to this lab and nobody noticed it or cared.

Is this rooted? Isn’t this just be a side-loaded app over adb?

https://github.com/humblemuzzu/dumbtv

Sure, but the dumb math winds up around $70b more a year in revenue per year with half their gpu output. Like it is actually kind of an absurd number if it’s true. They’re leaving essentially $30-40k on the board with each gpu they sell.

Unless it costs more than that figure to make a near frontier model and serve it, I can’t see how it wouldn’t be a slam dunk after a two or three year period.

They would even have extensive leg up in providing the most efficient inference on their own hardware.

This is all sort of in jest, but my point is, if the gold is real and all it takes is the shovels and money to hire people to use them, then it’s a big question as to why the shovel maker isn’t capitalizing.

Perhaps the gap is just too wide, but to use a more simple analogy. I see this like someone knowing everything about biology, simple mechanics, metallurgy, and human history but never hearing about an axe then assuming that person would never come up with the concept, use case of, or means to create an axe.

There is a ton of questions to ask regarding their removal of cybersecurity data.

First, how much “cybersecurity data” is just standard software knowledge that one can derive cyber security exploits from?

Did they also get rid of all references to hacking in general?

Are they implying that all the recent exploits are just things that were already in the data?

For a model it doesn’t seem that far fetched to make the leap from “I have the knowledge of what hacking is” and “I know how computer systems work” to just being able to exploit stuff anyways.

What’s interesting about Google is, they don’t seem to care to be the best LLM either, and merely maintain comparability to the leading LLMs as they see fit. I think they realize their best position is to serve an LLM as a complement to their search function, and if people want a more LLM heavy experience they can have that as an alternative.

Deepseek claims to be making $38/gpu/hr on deepseek 4.1 flash, and I would say that’s probably marginally close to the frontier, so they don’t have to be as good as OpenAI/Anthropic. Even at half that revenue, NVidia makes back the cost of a b200 cluster in roughly half a year. (19*8*24*5*52 = 948,480)

It’s estimated NVidia sold 4.5-5.2 million gpus in 2025 with total revenue numbers at about $130b.

With this terrible math in mind, they could produce half of that and make substantially more money, basically an infinite money glitch.

It’s not, but for fun I think that depends on if you see the models as just another technology or as a “country of geniuses in a datacenter”. The former means NVidia believes LLMs are fundamentally limited, and if that’s the case OpenAi and Anthropic are basically screwed as their core products become commodities.

This fits, if NVidia fully believed in the LLMs/AGI future, why would they waste their super valuable GPUs by selling them? Why not just make your own LLM with the advantage of being one of the few major compute providers?

A different analogy I would use is “code is now a single use plastic”. Cheap, abundant, easy to mold into any shape, and readily disposable. Sure it might pollute the existing environment and sure that might have massive consequences in the future, but who cares? You can easily make whatever you want right now at marginal costs and there’s no obligation to make sure it’s usable beyond its single individual purpose.

Sometimes it is reusable, much like you can use a butter container as Tupperware.

Possibly used as a mirror for humans prevailing beliefs about themselves to some extent. Hard to say however given that the models have a heaping dose of rlhf on top of their training data.

As an aside, it would be cool to see a raw model training run before the current post-training cycles and see how it compares to earlier LLMs.

Some of the aspects of these pillars need to be fleshed out, this reads like it was slapped together as a last second presentation.

For example, “Help all people, especially those most affected by AI, earn more and feel financially secure.”

How would this work? How does AI do anything but detract from the value of labor? Anything made by AI or through heavy AI involvement can be remade just as easily. It circumvents the moat of expertise and effort.

I wish AI companies would just be honest with the most likely consequences of their products proliferation, instead of these Disney-a** sunshine and rainbow pieces. Then maybe we could have a real conversation.

That’s the hard part with all of this, you’re either of the opinion that there should be some individuals capable of determining if the AI is doing the right thing, and therefore all the previous prerequisites are still necessary, or that we should just let it all ride on the AI, which is probably easier, but certainly more dangerous.

I wonder what the ratio of poster sentiment to comment sentiment is. I figure the sentiment of a post is seen broadly as much more authoritative than the sentiment of comments.

I fear there is a tendency for some people who are against the proliferation of AI to make sweeping gut-reaction comments like this that do more harm to their position than good.

Perhaps everything that you said is 100% correct, but people are easily swayed by things that “sound right” being overly aggressive opens your position (in people’s monkey brains) to “enlightened centrists” that leave the door open for bolder opposition.

Many people have been genuinely helped or feel like they have been genuinely helped by LLMs in coding, they aren’t going to change their opinions based on fiery rhetoric and accusatory tones. Much like I can’t force myself to believe in Santa Claus regardless of how aggressively my nephews claim he is real.

Sorry it’s been a while but this really resonated with me thank you

I think people are struggling to understand the way the world is changing. Entire modern philosophical contexts are being upended, for personal instance, I have been a big advocate of the philosophy described in Albert Camus’ “The Myth of Sisyphus”, particularly the concept of imagining Sisyphus fulfilled by the tedium of pushing the boulder up the hill, and deriving happiness from the struggle itself. But I bet Camus nor Sisyphus accounted for a self-pushing boulder.

Now what are we to derive happiness from? The joy of a boulder being on top of a hill?

I think that will be the most important thing for this transition, defining new purposes and meanings that people can assign themselves.

Wouldn’t that just be a beautiful outcome, LLMs are small enough and the hardware is cheap enough that everyone has their own, large software orgs are rendered obsolete by their own creations… perfect.

So far, it seems like outside of just being a SWE, the value derived from AI coding has been either through influencing, scamming, or devaluing existing things.

For any given product, the instant it is made (using AI or no) and distributed, its value drops to practically zero. It can be remade and modified infinitely at practically zero cost.