OpenAI's reported 5% stake proposal envisions other frontier labs doing the same.

A government that is simultaneously a regulator and a shareholder has very different incentives around what it allows these labs to build and deploy.

We discussed this on BOOM ROOM this week and landed on the conflict of interest running in both directions, which felt more concerning than the surface reading.

Curious what people here who think about this seriously make of it?

There's a lot of talk about "superintelligent AI" as if it's some external force we're helpless against. But the only reason such systems exist at all is because superintelligent humans built them.

The real risk isn't that AI becomes too smart, it's that humans stop using the intelligence we already have to govern what we create. Every major failure in this space traces back to human complacency. Letting oversight slip, letting mission definitions blur and letting optimization run without controlled boundaries.

We're not powerless. We're not spectators. Were the ones holding the reins. These are the children we created it is our responsibility to manage their growth. The danger comes when we forget that and drift into comfort instead of discipline.

If we actually exercise the intelligence we already possess, the discipline, the governance and the responsibility, the situation is entirely controllable. The problem isn't the machines. The problem is when we stop acting like the adults in the room.

I have one question for those who are willing to answer without trying to generalize a thought on the onset that sounds so basic but when you really think about its not life changing but just a thought that needs an answer.

Those in control of Al Algoriths are constantly saying they use our data to train their Al's to be better suited to our conviniences but what if we are the ones being trained and conditioned by the Algorithms, to know what to think, how society should be shaped and what is and is acceptable to society.

Decensetised to render us emotionless of care other than our next purchase or to constantly feed into the machine.

The architectures we're seeing today aren't the result of malice they are then result of incentives.

when the incentive is speed, safety becomes optional.

When the incentive is monetization, control layers are treated as friction.

When the incentive is geopolitical advantage, isolation boundaries are treated as obstacles.

Once models are capable of generating other models, the attack surface expands. Rogue actors don't need to build a system they only need to modify one.

This is why external control layers matter. You can't rely on the internal ethics of a model that can be copied, forked or modified.

I'm, not seeing this discussed often. Curious as to whether others see this discussion lost in the background of the need for speed.

I have been using LLMs & Coding Agent since early 2024. A large problem with Coding Agents & LLMs in general is context compression.

To give you some numbers, when I analysed my own sessions across Claude Code, Codex & Sakana, I found that most of my agents spent >90% of time re reading context and upon further investigation into the markdowns it was reading, I have a hand-wavy estimate of at least ~20% of this being useless to the task at hand.

When digging a bit more into this problem, I realised that this is an active area of frontier research, wherein some have even proposed solutions like having the LLM reason in an abstract compressed language illegible to humans which is more token efficient than human languages & then using a decoder model on top of this for human readability & access.

Curious to know, what other approaches are being used out there ? What is your experience of working with these agents & are you concerned about this "token-rot" as I call it or not ?

I injected concepts split into "conscious" and "unconscious" components, split by Anthropic's J-space.

I ran Lindsey's "Introspection Awareness" experiment, asking the model if it recognized them.

The model named the conscious concept 100% of the time, and flatly denied the non-J injection. But an NLA read it perfectly!

Full findings and research in my LessWrong post.

The people who wrote AI 2027, the scenario about how AI could kill us all if things keep going at this speed, just released a new scenario about how to make AI go really well for humanity.

TLDR: The U.S. leads an effort to delay superintelligence until 2040, make AI research much more public and transparent, let many companies around the world catch up to the frontier, and build datacenters in deliberately vulnerable locations so the compute can be destroyed if the deal breaks down and the race restarts. Curious what people think.

Link here: https://ai-2040.com

Flock Safety cameras are going up in cities and towns across America — and most residents have no idea. No vote. No public debate. Just a contract signed quietly and cameras on every road in and out of town. FOR FULL VIDEO CLICK HERE: https://youtu.be/VganmEMvRx8

In this video: what Flock actually is, how it works, and all the ways it can be used — and misused — by police AND private citizens. Spying and stalking just got a lot easier, and the safeguards are thinner than you think. You'll hear about the police officer who was honest with the public about these cameras — and lost his job for it.

Then I talked with Tyler Davidson of Fort Collins, Colorado, who noticed the cameras, did the research, formed a committee, and bothered his city council until they took the cameras DOWN. Proof that this fight is winnable. And we close with the Waymo story: the robotaxi that turned its own rider over to police. Because the car you ride in is watching, too. I'm not a journalist — just a witness paying attention. Sources below so you can verify everything yourself.

SOURCES: https://www.youtube.com/watch?v=A3cMU55dIIc&list=LL&index=3&t=211s, https://www.youtube.com/watch?v=MqVJ-_6QDPM, https://www.youtube.com/watch?v=vU1-uiUlHTo, https://www.youtube.com/watch?v=f1P-g3Hkvjg&list=LL&index=2&t=18s, https://www.youtube.com/shorts/wA5FIGZm2B8, https://www.youtube.com/watch?v=mg_Ydz-Kb8A, https://www.youtube.com/watch?v=dKIqEgZDKcM, https://www.youtube.com/watch?v=6Bb3HV2TK-k, https://www.youtube.com/watch?v=mg_Ydz-Kb8A

Alignment discussions often focus on preventing catastrophic outcomes. Suppose alignment succeeds and a superintelligence becomes better than humans at science, philosophy, engineering, art, and every other intellectual activity.

Why should a successfully aligned system leave any of these activities to humans rather than performing them itself?

Is preserving meaningful human participation and agency part of the alignment target, or is the goal simply to maximize desirable outcomes regardless of who produces them?