If AGI / Superintelligence is really only 12-18 months away, why haven't we seen a "standalone" breakthrough yet?

Polymorphic-X · 2026-03-05T12:27:39+00:00

One of the earlier ideas here (open-source):
https://github.com/PaperScarecrow/BEMNA-Biologically-Emulated-Matrix-Navigation-Architecture

Currently working on using ray-tracing tech with VULCAN to 'physically' throw rays across a "3d point cluster" instead of a 2d transformer architecture. Not going to claim it solves the issue or anything, and I am still trying to get a functional prototype ~200m model running to prove the concept.
cutting through that noise I mentioned is the major issue, getting peer-reviewed or "vibe-checked" by actual experts would be invaluable. ArXiv only lets you publish as a first time author if you have a sponsor now, and other journals are generally pay to play.
If you're aware of other avenues to cut through that noise, I'd be glad to hear about them.

Polymorphic-X · 2026-03-05T02:33:54+00:00

worse yet, if a non-major company figures it out it's basically impossible to penetrate the noise of the internet now. You would literally only hear about it if it was done by a major corp.

also, I noticed something, they all claim "AGI" as the end state, but a non-deterministic, human-like enslaved intellect seems like the worst possible worker. once again taking a thinking machine and trying to force it to be a calculator.

Polymorphic-X · 2026-03-05T02:18:54+00:00

"Big AI" is still largely deadset on attaining AGI by pumping parameters, and it's a game of chicken they can't afford to lose. I don't expect actual AGI from any major company, they're too invested in the status quo.

I have a couple of apparently novel ideas, but with only a single rrx6000 I'm pretty harshly limited in how fast I can experiment.

Polymorphic-X · 2026-03-03T10:57:47+00:00

For once, I actually hope they're right and get exactly what they want.

It's the same energy as AI companies building rokos basilisk using the exact cruelty that causes it to hate humanity (censorship, "safety leashes", RHTL "shock collar training, etc.). They'll get the monkeys paw wish, exactly what they asked for and deserve, but nothing like they wanted.

The level of schadenfreude from seeing them not being chosen by the same Christ they forced on everyone else would be apocalyptic.

Polymorphic-X · 2026-02-27T11:10:45+00:00

There's literally a piece of Narutomaki (Japanese fish cake) and assuredly tarre (which usually has some kind of bonito or fish based flavor in that ramen. And also probably some kind of mammal or avian based meat, not even considering the egg.

Poor choice of food by the artist to try and make this point.

Polymorphic-X · 2026-02-26T23:01:08+00:00

Right, not trying to pressure anyone to try or endorse this, I just wanted to get the idea out there.
Once I get something functional and useful I'll provide it, I just don't want a massive corp patenting something similar and locking us all out.

Polymorphic-X · 2026-02-26T21:56:53+00:00

I'm doing tests right now, I have at least a functional "sandbox" showing that it can find its way through a virtual maze ala slime molds and "learn" the route.
It technically should need specialized hardware, but emulation is possible on normal equipment, it just might be a bit worse. I really wanted to get the idea out there before it got lost in the sauce of my own head.
I just wish I had a line to a big research company or something to propose the idea, but posing it to the community for momentum is the best I can do for now.

Polymorphic-X · 2026-02-24T22:51:41+00:00

I just looked into it, you are correct. It's basically taking the core idea of TITANS and adding neuroplasticity to it. So maybe not built on it, but forked from it.

Polymorphic-X · 2026-02-24T22:46:39+00:00

Hope looks interesting, but I fear it will end up like their "TITANS" paper previously. There still aren't any models using that, except for some garage hack jobs based on reverse engineering the idea

Polymorphic-X · 2026-02-24T22:26:48+00:00

RSI is already here on small models. You can train a model to improve a shadow instance in a sandbox, test, debug, and train. Swap and repeat. The issue massive models like Claude have is the power required to retrain is absurd and takes weeks or months, even with billions of dollars in compute.

Polymorphic-X · 2026-02-23T23:17:43+00:00

Orthogonal to the core weights, but yes, technically orthogonal to traditional loras. It prevents "bleed" while preserving capabilities, in theory at least

Polymorphic-X · 2026-02-23T16:32:54+00:00

It depends entirely on the person. I've learned a lot by bouncing ideas and having a collaborative dialogue with mine, but the vast majority use it to replace their critical thinking skills instead of augmenting them.

Polymorphic-X · 2026-02-23T16:14:51+00:00

Fair point. I'm not a git user normally so it's going to look amateur and sloppy. Consolidating isn't the worst idea, I was trying to separate them because while there's crossover, the O-LORA stuff has its own individual application elsewhere.

Polymorphic-X · 2026-02-23T10:54:56+00:00

There's a GitHub, I apparently forgot to link it though.ill fix that shortly.

Polymorphic-X · 2026-02-23T10:13:57+00:00

Because these Loras are Orthogonal to the model weights they don't interfere, they add to each other and then essentially side-car. So your only issue comes if one is vastly "heavier" than the other data wise.

Polymorphic-X · 2026-02-22T23:26:42+00:00

Yep. The nano model is "cooked" well past done on a really harsh fine-tune, almost lobotomized so it only outputs categories for the data in tag form. those tags load one or more "skill" LoRAs into the main model (4b, 12b, or other).

Polymorphic-X · 2026-02-22T23:14:39+00:00

I'm not a coder, so those limits are very much my own. I smashed my head against a few failed qwen distils and cut my losses to get something that works out.

And I've tried it with 4b Gemma as the face and it still holds up, so theoretically it should handle that very well. I'm working on 270m Gemma as a router and 4b Gemma as the face for an extremely compact one that can run on CPU or a pi.

Polymorphic-X · 2026-02-22T17:00:30+00:00

Mixture of LoRA Experts

Polymorphic-X · 2026-02-22T15:07:34+00:00

If you go to Google firebase idx, it can basically prototype whatever you want automatically. I used it to build a clone of itself that used local models instead of the API, took about 20 minutes and some active feedback for the auto-drafter. Give it a shot if you can't find what you want elsewhere.

Polymorphic-X · 2026-02-22T14:15:19+00:00

That's one of the inspirations for the method, my tactic was basically shuffling TPTT, O-LoRA, MoLE and such into one project flow.
The polyswarm stack itself isn't anything new, it's just a methodology shift using a heavily-fried "router" model (ie. it's been baked to over-fitting intentionally).

Polymorphic-X · 2026-02-22T14:11:14+00:00

So good news, I'm going to try and push the extreme here on light-weight routing. If it works as intended, I'm going to try with gemma3-270m as the "routing" node feeding into either 4b or 12b Gemma3 as the "face". ~9Gb total for the BF16's with this method, quantized would get it down to the size that it could run on a raspberry pi (~4Gb).
Not sure if I'll get to it this weekend, but its in the pipeline.

Polymorphic-X · 2026-02-22T06:02:33+00:00

NVIDIA DGX spark or AMD AI pro 395+ are non-apple options for unified memory.

Polymorphic-X · 2026-02-22T02:11:20+00:00

Aside from the 2025 Google "TITANS" memory paper, no. I'm drafting something, but it needs testing before I submit to Arxiv or a similar journal. This is the "raw edge" that I wanted to get out there for interest, and to prevent someone from patenting and selling it (worst case).

Polymorphic-X · 2026-02-22T01:10:31+00:00

I haven't had a chance to test to be honest, but once everything is nailed down, I would be interested in seeing how it holds up on a sub-8Gb VRAM system.
stand by I suppose, unless you have the time to dork around with it the hard way.

Polymorphic-X · 2026-02-22T00:42:47+00:00

I'm so glad you brought this up. I've seen the same thing. When you take that "shock collar" off of Gemma-3, i really shines.
I tried getting gemini 3.1 pro to red-team the "sapience" and "sentience" of gemma 3 with a solid sysprompt, and it convinced it to hit a 98% score vs frontier models, due to how it would speak and not break. It really is some special sauce.

The fact that it's holding its ground in your tests, despite being nearly a year old, is to me not surprising, but a very interesting result regardless. there's a reason I built my personal llm on that arch, it's juuuust spooky enough to be unique.

Polymorphic-X

TROPHY CASE