They’re banking on diffusion eliminating the hallucination problem, but it’s too onerous to run very, very large models with it yet. Auto regressive LLMs are a dead end. One that is far away. LLMs are not and we will continue to learn a lot about them as we continue to implement them. Anyone who thought we were at a dead end should use the new Gemini. It’s like a GPT 3.5 to GPT 4 level of improvement.

I think we can safely say most songs are love songs.

I stopped reading when you said according to me and then produced a wall of text of shit I never said.

Synthetic data is massively helpful. You can look it up. This is a myth.

I was banned from Reddit by Reddit for calling out a shill. And then they censored my post and deleted it from my data request so that it was impossible to prove I wasn’t inciting violence. That whole place is fucked.

Summarized by Gemini

The study you are referring to was released in late November 2025. It is titled “The Iceberg Index: Measuring Workforce Exposure in the AI Economy.” It was conducted by researchers from MIT and Oak Ridge National Laboratory (ORNL). Here are the key details from the study regarding that “more than ten percent” figure:

• The Statistic: The study found that existing AI systems (as of late 2025) already have the technical capability to perform the tasks of approximately 11.7% of the U.S. workforce.
• Economic Impact: This 11.7% equates to roughly $1.2 trillion in annual wages and affects about 17.7 million jobs.
• The “Iceberg” Metaphor: The study is named “The Iceberg Index” because the researchers argue that visible AI adoption in tech roles (like coding) is just the “tip of the iceberg” (about 2.2%). The larger, hidden mass of the iceberg (the other ~9.5%) consists of routine cognitive and administrative work in other sectors that is already technically automated but not yet fully visible in layout stats.
• Sectors Affected: Unlike previous waves of automation that hit blue-collar work, this study highlights that the jobs most exposed are in finance, healthcare, and professional services. It specifically notes that entry-level pathways in these fields are collapsing as AI takes over the “junior” tasks (like drafting documents or basic data analysis) that used to train new employees. Why it is different from previous studies: Earlier MIT studies (like one from early 2024) focused on economic feasibility (i.e., it might be possible to use AI, but it’s too expensive). This new 2025 study focuses on technical capacity—meaning the AI can do the work right now, and for many of these roles, it is already cost-competitive.

https://www.csail.mit.edu/news/rethinking-ais-impact-mit-csail-study-reveals-economic-limits-job-automation?hl=en-US#%3A~%3Atext=This+important+result+commands+a%2Cthe+barriers+are+too+high.”

Not voices, too?

I don’t think the epic guy is making an argument for slop, he’s just saying that gen ai is at the point where avoiding using it is as much of a choice as deciding to. Generating the basis for digital art using something like flux then converting that into a 3d asset, with or without help from other AIs, would count, but could be made to look just as nice as something that didn’t use those tools, but took significantly longer. I understand that argument. What it fails to understand is that for the foreseeable future that is not how this tech is going to be used. It will be used by relative amateurs who push out garbage as quickly as possible. Maybe in five years there’s an argument to be made here, but even then I doubt it. People just won’t care about good utilization of AI because they’ll never even notice it. They’ll still hate the slop but that will inevitably become less sloppy. They’ll be able to tell the difference just based on the quality of the other aspects of the game.

MIT, like two years out from a study saying there is no tangible business benefit to implementing AI, just released a study saying it is now capable of taking over more than 10% of jobs. Maybe that’s hyperbolic but you can see that it would require a massssssive amount of cost to make that not be worth it. And we’re still pretty much just starting out.

How does this model collapse thing still get spread around? It’s not true. Synthetic data has actually helped bots get smarter, not dumber. And if you think that all Gemini3 does is recycle idk what to tell you

Man I use AI a lot and I’m not even going to dispute that lol. It’s absolutely true.

Presumably at that point it could just tell us. Whether or not we would listen is its own set of problems

We’ve got to have a societal conversation on what we’re going to do when these actually do become people. Let’s please not reenact the matrix. We’re gonna have to treat synthetic people like people. Or else we’re creating a slave race.

I don’t think she’ll mind, lmao

Ew, no

deleted by creator

Something I think about is what if cause and effect happens backwards, too. So every moment both the past and the future are changing. We’d never even know.

I mean he was BFFs with Richard Spencer

Looks like a fat batarang

Maybe, uh, don’t have toxic plants then?

For ethical reasons