Omission as a Tool of Manipulation: Three Case Studies – Pandemic, Climate, Middle East # Omitting information is a subtle yet powerful form of manipulation. It doesn’t create overt “fake news” but skews perception through selectivity and loss of context. This article documents three critical topics – COVID-19, the climate crisis, and the Middle East conflict – where factual distortion through omission has been demonstrably present.
„Will there still be a need for humans?“ „For most things, no.“ — Bill Gates, 2025
The image of the devil infiltrating the world through data centers is merely a symbol of a far more complex and systemic conspiracy. It’s not just about ruthlessness, but about deeply ingrained mechanisms that shape the development and application of Artificial Intelligence. The illusion of neutrality serves as a sophisticated lever for expanding power—a tool to secure control and deepen societal fragmentation.
“What Can Be Done About Hate Speech and Fake News?” A paper from FH Kiel attempts to provide answers – but mainly delivers one thing: the controlled opposite of enlightenment.
The Book Nobody Wrote # AI on Amazon – and How Words Become Nothing Again # It feels like a bad joke. A “self-help” guide about narcissistic abuse, packed with clichés, buzzwords, and pseudo-therapeutic fluff – supposedly written by a human, but most likely generated by a language model. Sold on Amazon. Ordered by people in distress.
“It’s like comparing apples and pears — but what if you don’t know what either is? Welcome to GPT.”
The debate around artificial intelligence often ignores a critical fact: Large Language Models like GPT do not understand semantic concepts. They simulate understanding — but they don’t “know” what an apple or a pear is. This isn’t just academic; it has real-world implications, especially as we increasingly rely on such systems in decision-making.
What actually happens to your prompt before an AI system responds? The answer: a lot. And much of it remains intentionally opaque.
This post presents scientifically documented control mechanisms by which transformer-based models like GPT are steered – layer by layer, from input to output. All techniques are documented, reproducible, and actively used in production systems.
I don’t want to convince anyone of something they don’t see themselves – that’s pointless.
But I do believe it’s valuable to have an informed opinion. And for that, we need access to alternative perspectives, especially when marketing hype dominates the narrative.
I don’t want to convince anyone of something they don’t see themselves – that’s pointless. But I do believe it’s valuable to have an informed opinion. And for that, we need access to alternative perspectives, especially when marketing hype dominates the narrative.
Why LLMs are not Intelligent # What is an LLM? # A Large Language Model (LLM) like GPT-4 is a massive statistical engine that predicts the next most likely word in a sentence based on training data. It doesn’t think. It doesn’t understand. It completes patterns.
Transformer models don’t “think” – they optimize probability. Their output is impressive, but it’s entirely non-conceptual.
Why Transformers Don’t Think # Despite the hype, Transformer-based models (like GPT) lack fundamental characteristics of thinking systems:
Translations: DE
GPT and similar models simulate comprehension. They imitate conversations, emotions, reasoning. But in reality, they are statistical probability models, trained on massive text corpora – without awareness, world knowledge, or intent.
