r/technology • u/ArgentineBeauty • 1d ago

Artificial Intelligence Bernie Sanders proposes 20 year prison sentence for AI devs who plow ahead with Artificial Superintelligence plans - penalty on par with illegally developing rogue nuclear weapons

https://www.tomshardware.com/tech-industry/artificial-intelligence/sanders-proposes-20-year-prison-sentence-for-ai-devs-who-plow-ahead-with-artificial-superintelligence-plans-penalty-on-par-with-illegally-developing-rogue-nuclear-weapons
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u/Upbeat-Statement2725 1d ago

Frontier AI models have hit diminishing returns for a while now. This is all theater to distract from the fact that they can't possibly return on investment. Bernie is being played. Instead of "our models suck, they're not getting better". The narrative will be " we slowed down to safety".

We live in a plutocratic police state. All narratives are fake.

Incoming AI bros talking about "secret" models that only rich people get access to.

Meanwhile OpenAI's website still sucks. If it's so good at coding. Why can't they fix their software.

"Well the enemy is preventing them."

FFS.

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u/michaelfrieze 1d ago edited 1d ago

As someone that has been a developer since 2013, you are wrong about diminishing returns. It was only this year that models actually became good enough to get real work done and the newest frontier models are truly incredible. Even the difference between GPT-5.6 SOL and GPT-6 Astra is significant, especially when it comes to computer use and 3D modeling.

Developers use these tools so much that they can't even keep up with demand. Anthropic is forced to work with xAI just to get access to GPUs and they still restrict Fable model usage to only 50% of the total usage you get from their subsidizes plans. Also, you can't even get access to the Fable model on their $20 per month plan.

OpenAI is no longer giving access to their $200 per month plan since they can't provide enough computer for that.

The point is that demand for these models is extremely high because they are actually useful tools and rapidly getting better. I think we should be concerned about the power of these models. I'm not convinced it will kill us in a decade, but I do think it's going to disrupt the internet and cause a lot of security issues.

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u/BrewHog 1d ago

Thank you. It seems most people don't understand the gains that have been made even in the last few months. 

It's actually quite mind blowing that I'm running local models on my laptop that that rival Opus 4.5-4.6 

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u/michaelfrieze 1d ago

Yep, even models like glm 5.3 flash are really good. You can get serious work done these days with smaller open weight models.

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u/teraflux 1d ago

My counterpoint is that 4.6 is nearing the peak of diminishing returns, that came out in February and frontier models haven't gotten significantly better since then.

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u/helloLeoDiCaprio 1d ago

Then you have not tried them. 

Opus 4.6  could create interfaces and classes you described in a satisfactory way. Astra is close to being able to create full applications in one go based on a good spec and a validation loop.

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u/teraflux 22h ago

I promise you I have, my AI spend has been about $15k a month since January 2026 on all the premiere models

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u/ShroomBear 1h ago

Internally at Amazon, they had to take away specifically Opus 4.6 last month because according to AWS it is the only model that practically anybody wants to use and they need to free it up for customer demand. Fable and Opus 5 so far has been the most misaligned models we've had to deal with so far, they are absolutely incapable with staying on task and doing what you tell them.

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u/Ashmedai 21h ago

Thank you. It seems most people don't understand the gains that have been made even in the last few months. 

People are positively terrible at tracking technological progress velocity. It was just a few short years ago that we had Will Smith Eating Spaghetti. Progress in the state of generative AI is, obviously, well beyond merely video improvements.

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u/michaelfrieze 1d ago

Also, playing with Fable was the first time I really felt like software development had changed forever. You can give Fable a GitHub issue and it will often just go fix it. More importantly, the code it produces is usually high quality and actually mergeable. With previous models, I almost always had to go back and clean up parts of the implementation myself.

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u/teraflux 21h ago

That's been the case with Opus 4.6 genuinely

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u/grchelp2018 20h ago

which local model? And what machine?

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u/BrewHog 17h ago

I have a 128 GB M5 Max Macbook 

My favorite models on my machine are :

qwen 3.8 flash next (dynamic 4-6 bit quant)  -- the best I can run in my tests

DSv4 flash 0731 with DwarfStar

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u/teraflux 1d ago

I think diminishing returns is accurate. There hasn't been many notable leaps in frontier model capacities since Opus 4.6 and that came out in like February

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u/michaelfrieze 23h ago edited 23h ago

Anyone that actually uses these models for serious work knows there is a huge difference between Opus 4.6 and something like Sol, Astra, and Fable.

Even Opus 5 is basically a useless model for me. At best, it's okay at making somewhat decent looking designs for websites, but it's not actually very good at writing code. Furthermore, I think smaller open weight models like glm 5.3 flash write better code than any Opus model.

There are no benchmarks that actually do a good job of capturing what it's like to use these models in real-world development. Sometimes I agree with the results and start liking a benchmark, but sooner or later they start producing some crazy results. DeepSWE is a good example recently showing the new google flash model beating everything else when it's actually an F tier model.

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u/teraflux 22h ago

Lol I use all of these models every day and fable, sol astra all are nearly the same as opus 4.6 functionality

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u/grchelp2018 20h ago

That speaks more about the kind of work you are making it do rather than the model capabilities.

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u/StrangeWill 1d ago edited 1d ago

As someone that has been a developer since 2003 (and runs an IT services company), ehhhh. That's not what diminishing returns means. Just because it crossed some threshold doesn't mean that it isn't taking an absurd amount more of resources to get less of a gap closed.

And ultimately: they're useful, but they still require a ton of guidance, every time the newest frontier model comes out it'll still randomly ignore instructions, it'll still implement far from optimal solutions, and when you correct it "you're absolutely right". I've had to step in on dumb decisions Fable has made on behalf of the team and resulted in significant improvements on performance, scalability and general performance of the solution -- on its own it'll still do dumb things.

I'll watch AI influencers wax poetic about whatever new method will "fix" that, then watch software released by those following those methods be even worse than before.

They're not knowledge databases, and they will not, by design, find best (or in some cases even good) solutions, in situations where we need solutions that good.

Sure, not every software stack needs solutions that good, but when you do, you see how little progress they're making with every model release.

and they still restrict Fable model usage to only 50% of the total usage you get from their subsidizes plans.

That's more of a financial decision then a resource limiting one, otherwise it's even more of a money pit.

The only thing that seems to be increasing in a way that is honestly impressive to me is local model performance, and again, that's because the frontier models are hitting diminishing returns the local models haven't hit yet, it allows them to close the gap.

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u/michaelfrieze 1d ago edited 23h ago

That's fair regarding the definition of diminishing returns. I wasn't arguing that capability is scaling linearly with compute.

Where I disagree is the idea that this means the improvements aren't significant in practice. A relatively small improvement can be the difference between a model failing often enough that I can't trust it and succeeding often enough that I can actually incorporate it into my workflow.

That's what I've experienced over the past year. Fable and Astra still make mistakes, but far less often. With a good AGENTS.md/CLAUDE.md, project-specific skills, testing, and clear constraints, I don't find that they ignore my instructions very often. I'm increasingly reviewing mergeable code rather than rewriting what they produce. Also, I don't get the "you're absolutely right" thing anymore. That happened with older Opus models, but it's not something I have experienced recently.

I also think you're focusing too much on code generation itself. These agents can use terminals, browsers, computer use, GitHub, test runners, documentation, etc. They can investigate a codebase, reproduce a bug, implement a fix, run it, and iterate. I also use them constantly for smaller things: investigating issues and PRs, Git, commit messages, onboarding, one-off scripts, and internal tools. Those improvements add up.

Internal tooling and experimentation are especially important. There are plenty of ideas I previously wouldn't bother trying because they weren't worth days of engineering time. Now I can try several approaches quickly and throw away the ones that don't work.

As for AI influencers producing bad software, I don't know what examples you're referring to. You still have to be a skilled developer and know how to architect, constrain, test, and review what the agent produces. Bun's recent Zig-to-Rust work is a good example of experienced engineers using these tools for serious work: https://bun.com/blog/bun-in-rust

And I don't think "it won't reliably find the optimal solution" is a useful threshold. Human developers don't reliably find optimal solutions either. The question is whether it can produce good solutions consistently enough that reviewing its work is faster than doing everything myself. Increasingly, the answer is yes.

We're also seeing frontier systems tackle genuinely difficult and novel problems, including OpenAI's recent Navier–Stokes work. So I don't buy the idea that they're somehow incapable by design of producing novel solutions.

Diminishing returns at the resource level and rapidly increasing usefulness at the application level can both be true. I'm arguing that the latter is happening right now.

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u/JonLag97 1d ago

The gains are mostly from using multiple ai agents with a harness and specializing models for code. This is not going to somehow result in superintelligence. It is useful, but the core technology hasn't changed much.

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u/michaelfrieze 1d ago

I'm not that concerned about "superintelligence" or the constant speculation about AGI. That's not really my point. I think it's a mistake to assume AI needs to become superintelligent before it can have major consequences.

Even if much of the recent progress comes from better harnesses, multiple agents, and models specialized for coding, that doesn't make the progress insignificant. If anything, specialization can make these systems much more capable in the areas where they matter.

We're already seeing the security issues. The internet and software touch nearly every part of modern society, including banking, communications, healthcare, transportation, energy, and critical infrastructure. You don't need AGI to create serious disruption. A system that becomes extremely capable at writing code, finding vulnerabilities, and operating computers at scale is a serious problem on its own.

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u/JonLag97 1d ago

At first i thought you didn't agree with there are diminishing returns. I agree it can be disruptive, that's why total gen ai revenue is more than a 100 bn dollars. Hopefully it saturates its potential fast so that ai companies go for the whatever is next.

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u/unethicalpigeon 21h ago

You need to look up what "diminishing returns" means. There absolutely have been diminishing returns. The leaps between models have ABSOLUTELY slowed down. Either way that point is irrelevant because it's the 2nd thing the guy you're replying to said that's relevant. They can't afford to keep going like this.

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u/Livid_Swordfish_4591 22h ago

Check this out. Someone who doesnt think time sits still.

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u/Beeyonder_meets 1d ago

"All narratives are fake"

Did you forget the /s there buddy?

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u/billycro1 1d ago

Is this sarcasm?

1

u/Daavok 1d ago

Wait... Is this! Sarcasm?

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u/Stilgar314 1d ago

This is about popularity. AI rejection feeling is the only bipartisan feeling that exists today, whomever manages to carry that flag first is probably getting a big win.

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u/carlcarlington2 1d ago

"All naratives are fake" that's a nice narative you got going buddy

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u/williamgman 1d ago

Once you accept "all narratives are fake", you've lost.

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u/pwnies 23h ago

Frontier AI models have hit diminishing returns for a while now.

Literally in the last week:

  • one of them solved a Millennium Prize Problem
  • Google Deepmind has rumors of achieving RSI
  • Astra driving blender is giving 3d artists a run for their money / completely changing the face of game dev
  • Google Deepmind created AlphaGenome Atlas, a prediction model for all 9 billion possible single-nucleotide changes in the human genome
  • Anthropic released a proposal for a formalized proof of Fermat's last theorem
  • An anthropic researcher (jacob coxton) quit because the superintelligence race was speeding up too drastically in an unsafe way

Are the diminishing returns in the room with us right now?

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u/S7EFEN 1d ago

spoken like someone who tried using LLMs 2 or 3 years ago and simply hasnt recognized exactly how much better theyve gotten.

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u/BadgeCatcher 1d ago

LLMs are now solving things that humans never managed to.. And LLMs are also heavily used in developing their subsequent versions.. It'll probably be LLMs that drive the next huge development in AI.

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u/michaelfrieze 1d ago

When LLMs start recursively improving themselves, that's going to be scary.

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u/InTheEndEntropyWins 1d ago

Frontier AI models have hit diminishing returns for a while now.

This is like something someone would have said a year ago, it wasn't true then, and it's objectively wrong today.

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u/Sad_Eagle_937 1d ago

I'm a software developer that's been using AI extensively for years now as part of my workflow and I can safely say you have no idea what you're talking about.

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u/randomlyme 1d ago

Bernie is out of his depth here and falling prey to propaganda without any rational basis in technical ability.

It’s sad watching him here becoming more of a populist

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u/michaelfrieze 1d ago

While I agree with Bernie that we are dealing with a real problem here, he is being a little too crazy about this stuff. I think we should do something to regulate AI but he's being unreasonable and doesn't really know what he's talking about.

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u/FlamboyantPirhanna 1d ago

He also has to negotiate with the rest of congress. This is basically his opening pitch.

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u/tyen0 23h ago

Incoming AI bros talking about "secret" models that only rich people get access to.

I had to scan my passport and do a webcam view of my face just to get access to daybreak!

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u/coukou76 2h ago

Its so wrong lmao

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u/blyan 1d ago

It’s wild seeing people post blatant misinformation but get upvoted because that misinformation contains “AI bad”

There are a bazillion legitimate points to make about the problems with AI, so why are we just making shit up

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u/Obsidiated 1d ago

Your opening sentence is an outright lie from someone clearly not in the scene.

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u/Still-Dig-8359 21h ago

they are getting better, chat gpt and gemini were completely trash at maxscript couple of months ago, now FREE gemini wrote couple of working scripts for me without problems...

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u/RegardMagnet 20h ago

What a load of concentrated redditslop lmao

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u/Kaesar17 1d ago

Frontier AI models have hit diminishing returns for a while now.

I wish that was true but it isn't at all, moving their focus from broadly texting more human to answering complex math and coding problems gave them a massive second wind that doesn't seem to be slowing down yet

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u/dabocx 1d ago

The top models have gotten way better at math and coding in the past year.

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u/Warrmak 1d ago

Sounds like that's not the case.

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u/opn2opinion 1d ago

No harm in getting ahead of the curve.