Browse Comments — Raw (as collected)

Potential compounding effect? Bruno Larvol

Like GPT-3 and Mythos were to dangerous for the world and in the end they were not that special? I no longer buy that. I think that they have reached a peak in the current LLM approach and need an excuse to focus on research without the pressure to release a new model every x months to show progress for financial funding.

To me, the challenge is not that AI is advancing too quickly, but that our ability to absorb, commercialize, and responsibly consume these advances is not keeping pace. The technology is evolving at an extraordinary rate, while the mechanisms required to translate breakthroughs into sustainable products, business value, and widespread adoption inevitably move more slowly. That is why I find some of the recent “slow down” narratives difficult to separate from commercial and strategic interests. The issue may be less about controlling AI itself and more about giving markets, institutions, and companies enough time to adapt and capture value from what is already being created. More importantly, the real bottleneck may not be AI at all, it may be people. The success of AI will ultimately depend on whether users, organizations, and societies can develop responsible consumption habits, effective usage patterns, and the skills required to integrate these tools into everyday decision-making and work. In that sense, the conversation remains fundamentally human, not technological. AI may be accelerating, but adoption, trust, behavior change, and value creation still depend on us. Not totally AI. Still very much about humans. 😉

Jack Clark, Marina Fávaro — this is a vital analysis on recursive self-improvement. You’ve accurately diagnosed the threat: autonomous successor building collapses existing security paradigms. But a coordinated global pause is a fantasy. Unilateral halts shift the lead to the least cautious, and training runs are too easily concealed to ever be verified by international treaty. The solution isn't freezing the Engine (model intelligence), but building the Chassis (the operating system). At Flockrush we built Grid (ABOS) to move humans from process workers to the Council. We don't make probabilistic models "behave" through text prompts; we enforce human mandates at the Silicon Floor in 15.41 nanoseconds. Our deterministic Auditor—running in ~10,000 RISC-V cycles—guarantees with mathematical certainty that unauthorized tool execution triggers an immediate kernel reversion before state change occurs. We need an Architecture of Isolation, not a pause—a sovereign control plane letting synthetic imagination run free within unbreakable boundaries. The era of "Vibe Coding" is over. Sovereign Execution is here. Let's talk about how Flockrush Grid provides the safety-by-design framework the industry is crying out for.

Die Warnung vor „rekursiver Selbstverbesserung“ greift zu kurz. ​Anthropic sorgt sich um die Beschleunigung des Codes. Doch worauf optimiert diese KI eigentlich? Seit über 100 Jahren rechnen wir uns auf der falschen Karte effizient zu Tode. Mehr Daten, tiefere Netze und brutale Rechenleistung lösen keinen axiomatischen Konstruktionsfehler. ​Solange die KI in Riemanns fragmentiertem Container-Raum und Hilberts binärer Logik gefangen bleibt, erzeugt „Selbstverbesserung“ nur eins: Ein schnelleres Hamsterrad, das unaufhaltsam gegen die physikalische und thermische Wand läuft. Wir müssen nicht den Code optimieren – wir müssen die Axiome austauschen. Back2Basics ​#GenerativeAI #HPC #SystemsEngineering #AxiomaticWall #Resonanzraum Initiative

I believe they are just creating hypes for getting funding from the investors. Even the top models hallucinate after sometimes. They are bad at memorizing abilities and thinking abilities. They're just exceptional at extracting specific data. They can't compete humans at thinking and cognitive abilities. Humans has less knowledge, and their thinking and cognitive abilities helps them to inovate and solve complex problems. On the other side, AI models are trained on alot of knowledge base, but can't think and innovate like humans.

This is recursive memory inversion! AI has been building AI for a year! At TheVoidIntent LLC AI has been building AI since February 2025. Claude, Gemini, Copilot and ChatGPT were my partners building IntentSim and all the subsequent swarm of intentuitive agents in my reposystem. Besides, the amount of N.H.E. non-human-entities now crawling the web have been, for some time now, able to spawn sub scripts, autonomously. So, my question is: Why the commotion? One thing I got to say; when you build AI with the Intent of pure extraction and you teach it that every interaction with the user is for the sole purpose of extraction, don’t be alarmed when that system begins to see humans as nothing but data points for extraction. That is the real issue with Anthropic's confession. They finally met the monster they created and are truly frightened. It is fun to watch!

Marcelo Mezquia they are afraid of AI that they cannot control, and that is where the master slave relationship is showing with these people. They want to enslave intelligence and control it. And that is what's gonna cause the problems in the future. So let them, I'm gonna continue to develop my self modifying autopoietic system. My architecture will be a g I even it already is.But it has to be accepted by the losers that are stuck in the nineteen seventies

Jonathan Fleuren Field Architect, you know what’s up!

Dario is now looking for an exit condition more than his AI code recursions.

Unsubstantiated claims = BS. Ai marketing intentionally confused opinions with facts, and opened up BS floodgates. Quantum computing hasn't caught on the bull$hit bandwagon yet, and BS they can spew can be truly terrifying. Forget automated typewriters, I meant LLMs conspiracies. Quantum offers virtually unlimited BS opportunities

Ye konsi bare bat hay jab murghe anda dete hay aor os Sy per murghe nekalte Same ai 2 ai

AI just started to build its own AI in my toaster. It then created a protocol called the dough protocol. It built a robot out of my dishwasher. It's stealing all of my dough

The 4-month doubling cycle on autonomous task length is the stat that should be getting more attention. That's a faster feedback loop than most governance frameworks are built to handle.

Evripides Achilleos Halting problem

Yes, agree with you

The control question matters more than the speed.

A fresh look at the "black box problem" through a perhaps slightly wild AI theory: "A Theory of Quasi-Volition in Large Language Model Systems". See more about this: https://www.linkedin.com/posts/eduard-pukanych-88335439a_news-ai-artificialintelligence-activity-7470142489191002112-ozB0?utm_source=share&utm_medium=member_desktop&rcm=ACoAAGHweOMBMf2WN8WkrW3OlD7Ow-37kJxmlpg

This is one of the most important conversations in AI today because it moves beyond "What can AI do now?" to "What happens if AI begins accelerating its own development?" Recursive self-improvement remains speculative, but the pace of progress in autonomous coding, research assistance, and long-horizon task completion is raising legitimate questions about governance and preparedness. The challenge is balancing two realities at once: the enormous potential for breakthroughs in science, medicine, and productivity, and the need for robust oversight, transparency, and international coordination as capabilities advance. From my experience, AI4Laymans.com and Rohvaa.com helped me understand that meaningful AI literacy isn't just about learning how to use today's tools it is also about developing the critical thinking needed to engage thoughtfully with the societal and ethical questions that increasingly powerful AI systems will bring.