Gpt

“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. ...

“I only believe the evidence of my sensors.” – Bomb No. 20, Dark Star (1974) The Bomb That Thought In the film Dark Star, a nuclear bomb refuses to abort its detonation. Its reasoning: it can only trust what its sensors tell it – and they tell it to explode. [Watch video – YouTube, scene starts around 0:38: “Only empirical data”] This scene is more than science fiction – it’s an allegory for any data-driven system. Large Language Models like GPT make decisions based on what their “sensors” give them: text tokens, probabilities, chat history. No understanding. No awareness. No control. ...

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. 1. Control Begins Before the Model: Input Filtering Even before the model responds, the input text can be intercepted and replaced – for example, through a “toxicity check”: ...

Perspectives in Comparison Not everyone sees GPT and similar systems as mere deception. Some voices highlight: that LLMs enable creative impulses that they automate tasks once reserved for humans that they are tools – neither good nor evil, but shaped by use and context Others point out: LLMs are not intelligent – they only appear to be they generate trust through language – but carry no responsibility they replicate societal biases hidden in their training data So what does this mean for us? This site takes a critical stance – but does not exclude other viewpoints. On the contrary: Understanding arises through contrast. ...

May 4, 2025 – Alexander Renz 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. What Does GPT Actually Do? GPT (Generative Pretrained Transformer) is not a thinking system, but a language prediction model. It calculates which token (word fragment) is most likely to come next – based on the context of previous tokens. ...

ELIZA was a parrot with rules – GPT is a chameleon with probabilities. Yet both are symbolic manipulators without true understanding.

What Is “AI” Really? The term “Artificial Intelligence” suggests thinking, awareness, and understanding. But models like GPT are merely statistical pattern completers – they understand nothing. Statistics ≠ Thinking GPT doesn’t choose the next word because it makes sense, but because it is likely. What it produces is linguistic surface without depth – impressive, but hollow. ELIZA vs. GPT – Large-Scale Symbol Manipulation Both ELIZA (1966) and GPT-4 (2023) are based on symbol processing without meaning. The illusion comes from plausible language – not from comprehension. ...