It's a very knowledgeable synthesis of the current and future of AI.
I am fully per the spirit and the argumentative logical pathways in this paper supporting « there is nothing "magic" about human intuition.» I don't see any "magic" in the "Acte de RÉSONNER des Idées." However, I see a significant difference between this resonance and the "Acte de RAISONNER des Pensées." My proposal is taking advantage of the cognitive power (Ϟit) of the Faculty of Intuition, generating real sparks of ignition of the Force of Imagination (ϔfi ) to create multivocal ways (prompts) applied and explorative foresight for the AI next steps. That's why, in the first part of my book, I propose to explore this "Terra incognita" of the Zone of the Unthought. The cognitive power (Ϟit) of the Faculty of Intuition of Homo Sapiens has always sailed there by sight, without a rudder. I invite you to consider the reconciliation of the Intuition faculty to the duo of the faculty of abstraction (mathematical language) and discursive (verbal intelligence). This mind-bogging tripod will master the Homo Sapiens' cognitive powers to navigate the Unthought zone (intuitions/new ideas never thought), where for now, the AI still steers its course in the Thought Zone of the Intelligible. I conclude with this statement. "One step toward the Unthought zone is the next giant step for humanity, keeping Homo Sapiens above any AI. "
The topics of "Large Language Models" and the "Reverse Turing Test" are important for the future of AI because they both address the capabilities and limitations of AI language generation. Large Language Models, trained on vast amounts of text data, have the ability to generate human-like language, making them valuable tools for various applications in natural language processing, chatbots, and content generation. They represent a significant advancement in AI technology.
On the other hand, the Reverse Turing Test challenges the traditional notion of the Turing Test by assessing whether a human can differentiate between a machine-generated response and a human-generated one. This test helps researchers and developers understand the level of sophistication and human-like qualities that AI language models can achieve. By evaluating the performance of AI models in generating text that is indistinguishable from human-generated text, the Reverse Turing Test pushes the boundaries of AI capabilities and aids in advancing the field of natural language processing.
Both topics contribute to the ongoing development and improvement of AI language models, which have the potential to revolutionize various domains and applications in the future.