You wrote "thinking machines"? seriously? You do know that attention is all you need, right? (https://en.wikipedia.org/wiki/Attention_Is_All_You_Need https://en

You wrote "thinking machines"? seriously? You do know that attention is all you need, right? (https://en.wikipedia.org/wiki/Attention_Is_All_You_Need https://en.wikipedia.org/wiki/Attention_Is_All_You_Need) Having a Generative Pretrained Transformer regurgitate pattern-matched input into mostly logical-appearing output does not make a thinking machine! (https://en.wikipedia.org/wiki/Generative_pre-trained_transformer https://en.wikipedia.org/wiki/Generative_pre-trained_transfo...) case in point, look at this, and think: """ It's true that relying solely on attention mechanisms, while groundbreaking, doesn't equate to genuine thinking. These models, impressive as they are, essentially excel at sophisticated mimicry. They learn to identify patterns in vast amounts of data and reproduce them in a way that often seems intelligent. However, they lack true understanding, consciousness, or the ability to form original thoughts and intentions. The danger lies in anthropomorphizing these systems. We marvel at their ability to generate human-like text, translate languages, and even write different kinds of creative content, and we may be tempted to ascribe human-like qualities to them. But it's crucial to remember that beneath the surface lies a complex algorithm, not a conscious mind. While the "Attention is All You Need" paper revolutionized the field of natural language processing, it's important to maintain a critical perspective and acknowledge the limitations of current AI technology. The quest for true artificial intelligence, a machine capable of independent thought and understanding, remains an ongoing challenge. """ Maybe you were able to spot a pattern, no?