There are lots of wild rumors about discoveries governments may be keeping under wraps: antigravity, zero-point energy, UFO recovery and reverse engineering, and major advances in math and physics. There are even claims that “dead end” research like string theory was intentionally encouraged to distract from other discoveries.

People like Marc Andreessen have talked about hearing interesting things from government officials, and Eric Weinstein has raised related questions (whatever you think of him, these are just a couple of the more recognizable names who have made claims along these lines). I don’t know how much of it I believe, but it’s interesting to consider.

With the progress happening in mathematics at AI labs, and potentially physics soon as well, I wonder whether some of these supposed secrets could come out through independent discovery. If another lab reaches the same conclusions, keeping the original work classified might no longer accomplish much.

Do you think significant breakthroughs have already been discovered and withheld for military or economic reasons? And could AI make it harder to keep those discoveries hidden, especially as more people gain access to increasingly capable models?

Edit: I know people are dunking on the UFO stuff in the comments, but there has been a lot of whistleblower testimony for decades, and most recently in 2017 to now. People have even testified to congress about it. There is documentation that the govt participated and pushed a discrediting campaign about UFOs to make anyone who engaged in the topic to seem crazy. And with the way the comments are going, kinda reinforces that…

There, i said it

Basically, we see how huge corporate apps are reverse engineered and made open source.

Emulators are faster because of it, there are working programs of popular proprietary software like Photoshop even.

With the advent of open weights which don't deny requests for unethical requests. People have more power than ever to completely own software or simply make whatever they want.

Big corporations have much lesser moat because the power of a building your own and reverse engineering popular ones are so much better now.

This makes me think, even popular software like Microsoft windows can be made open-source provided reverse engineering and recompiling gets that much better

For the record, I'm aware that singularity doesn't have a consensus definition, and that everyone interprets it uniquely or focuses on different aspects of it to varuous degrees. That said, this year is proving to be rather remarkable in terms of progress, breakthroughs, and application. It would seem 2030 or soon after is the "brace for impact" moment when our relationship to technology, and what day-to-day life entails, will shift dramatically. Is Kurzweil sticking to his guns for any particular reason?

With the way how AI and computation is concentrated in the hands of a few cooperation of these days, the income inequality and the lives of the common people is going to get worse if we continue in this trajectory.

I personally think the only way we are surviving this is if we all have access to cheap decentralized AI.

Right now a beefy workstation can run a model maybe a year behind the current Frontier. We need to push companies to make these local workstations the Frontier. This means the current AI labs will have to lose eventually. And the ultimate winners would be actual hardware companies making hardware for the masses. Which means unironically we are the mercy of companies like Nvidia.🫡

Other than this I don't see a way out.

What will happen when everyone can create software? When AI is getting better and better that software can be created in a few months, then a month, then a few weeks?

Well, the news of Microsoft today is what is about to happen to the entire Industry, or maybe one of the things that may happen.

https://www.cnbc.com/2026/10/26/microsoft-msft-voluntary-buyouts.html

Read through Anthropic’s S-1 and the revenue numbers are wild.

They did $4.6B for all of 2025 and $16.3B in the first six months of 2026. The number of customers spending $100K+ a year also went from 950+ to 11,900+ in roughly a year.

The $80.7B net loss is probably the headline everyone will focus on, but $72.4B of that comes from changes in the value of its financing instruments. Operating loss was $693M, so the picture is a bit different from what that first number suggests.

One thing I found interesting is the ownership structure. The founders get 50.1% of the voting power through a special share, which means public investors won't have much control over company decisions.

I came across the funding numbers through Autumn AI while looking into the filing. The rest is from the S-1.

I am more curious about whether this growth can hold up than the headline loss. These numbers are huge, but the infrastructure commitments are huge too. Curious how people here are reading this.

Is there a platform where AI agents are paying humans money to do tasks for them?

We already know that software is easy (hence, all the rapid explosive progress in generating text/math/code/images/video). Unfortunately, the digital space is the area that has the least immediate benefits to the lives of the average person.

Biology and Hardware are different beasts entirely. They're much more difficult, but solving them would be immensely more beneficial to the human experience.

By what year do you guys think general-purpose humanoid robots will be capable of autonomously performing professional-quality haircuts: fades, tapers, and complex hairstyles, with the precision, safety, consistency, and speed of an experienced human barber, without any human assistance?

And will you trust a robot with a straight razor next to your neck/head?

This month specifically the video game industry was altered forever. With vibe coding, backwards engineering, advanced AI mods, and new emulation systems, on top of jailbreaking every console, we now have a far more open source industry.

Our online browsing ecosystem changed while you weren't looking even though you are the reason it changed. Because of Google's AI browser results, we saw SEO become absolutely useless. Ad revenue dropped at staggering levels for small, medium and large businesses. So much so that many have had to shutter. No more ad click revenue, which may be better for consumers, but hurt the income streams of many. Now Google is switching from an ad revenue click stream model to a licensing deal model with specific third parties.

Software in general has become fully replicated with long standing companies seeing drops in subscriptions from people who would prefer not to be price gouged, and are instead trying out open source mirrors of older suites like Adobe. You can bet Autodesk is not far behind.

I think it's useful to remind yourself that any game that is released now will no longer be subject to the old familiar economic and consumer models. Those games will become integrated into the Katamari ecosystem. A digital space model where all things become open source and even interconnected.

It's important to note that simply going by the examples above and not delving deeper into other sectors and fields and industries being influenced or altered by AI, we already see the absolute necessity for rethinking economics overall.

Even outside of digital space, real life is being impacted. We can make anything we want with 3D tools, we can order anything and receive it day of, and robotics is advancing at break neck speed.

It's too late to get ahead of it. Our markets will crash long before we can pass new regulations or figure out new economic models that align with this AI integrated era.

This is it. We are living the disruption now. It's not going to get better right away, so people should be preparing for some hard core social upheaval.

A more cognizant and ethical US administration could have done so much to at least slow the pain of this progress, but we were fortunate enough to be given the literal worst humans as our leaders.

What's weirder is that those very people who seem to so negligently handle all things AI, are assuming they are going to profit off it as though the classic economic model that is based on market and shares will remain intact in the next year or two.

If you haven't figured out you are in the middle of not just a cultural change, but a change in civilization itself, then you better catch up.

I see how some people can watch flashy robot demos on the timeline and think with a shiver that the robot apocalypse is around the corner, but reality check:

There is no robot in the world that can change the batteries in a jack-o-lantern.

If you have a robot friendly door handle it might be able to walk outside, pick it up, and carry it back inside. The robot could open the drawer with your batteries in it, but then things get tough.

Opening the package of AA batteries? Extracting a precision screwdriver from its case? Unscrewing four tiny screws that require a hard press and twist? Popping batteries out of the case?

Yes, you could build and train a specialist robot to do that today, but there is a very long way to go to replace the full range of human capabilities. Near term doomer scenarios should stop at “secretly controlling humanity” instead of “wiping humanity out”

https://x.com/ID_AA_Carmack/status/2114897771001974921

Google DeepMind announced Genie 4 today. You describe a place and it builds a scene you can move through in real time, and you can keep typing while it runs to change the weather, move the camera or add people. Scenes now stay consistent for two minutes, double Genie 3, it makes its own sound, and characters talk back. The interesting change is Gemini 3.8 Flash running inside it, breaking goals into steps and checking every frame to see if each step worked, which is an agent loop in a world that’s being generated around it.

It’s a research preview for trusted testers. Google says Ultra subscribers get it in Project Genie (waitlist) and early access developers get it through the Gemini API over the coming weeks, with no price yet. Google’s own list of what doesn’t work lists that objects drift in long sessions, and text, sound accuracy and complex physics aren’t solved. I wrote up what’s new, why world models matter as training grounds for agents, and who can use it: https://www.anchorterminal.com/blog/genie-4-world-model

https://github.com/anthropics/formal-math/tree/16a5ce41304fcdaea4e0be7c132e1c361dc26da5/eth

They claim it was created with a single researcher and under $10 million spent on the model. Theyve only said that it is somewhere between 0.1 and 0.5T parameters in size. Benchmarks aren't super impressive, but they claim this is just the first very early checkpoint and that they also have two much larger models undergoing training right now.

Two mathematician/physicist friends of mine have worked on Yang Mills for the last few months and made substantial progress. Due to OpenAI's claim, they have decided to publicize their results. They have a vision of community-generated math that makes a lot of sense to me in post-AI mathematics. I consider that part just as interesting as the result itself so I am helping share their claims around.

They worked with small budget (~$500) and made substantial progress toward YM existence, building on Bałaban as I understand it, just as OpenAI did in their statement. Their work is human-guided with AI doing substantial specified work. Both Claude and ChatGPT were substantial contributors.

This github has their work in it, with timestamped PRs starting from a few days ago when they decided to release. They have a vision of a community-generated mathematics, wherein the open internet can contribute towards a full solution using any tools at their disposal, starting for now through this github. It's a new modality of math that to me seems positive/to look forward to. Nobody loses substantial time from being scooped by an unknown competitor because progress is visible live, with more honest attribution than a traditional paper. As they are completed, proofs can be formalized and published in a traditional manner to reach fully accepted status. I understand it as an experiment on how math can be done as much as an important partial result. (yes, community math has been done before, the difference is that now it is a more logical modality than ever in the past)

https://github.com/MathePhysics/4D_Wilson_Loop_RG

https://x.com/iaifi_news/status/2115139456877363435?s=20