Wow. Ok we aren't allowed to talk about news on here either. Below is Dean's AI Clone's recommendations on how to post. I'll post their requirements and tips below in case anyone else wants to keep their posts up. This post will follow those recommendations and this amazing group of people Tony and Dean have spent years developing can see some important aspects of the AI Advantage: 2.No Extreme predictions are being made in this post and no AI experts in AI safety are being named nor any external references which can be identified are given. No calls to action are being made but 1.only sharing some ideas and tips on understanding the area of AI interest I think I can provide an advantage in to this group. 4.“I’ve been exploring ways to use AI responsibly. What are some strategies you use to ensure your AI projects are ethical?” 5.“How can AI help people make better decisions safely? Here are a few ideas I’m trying — curious to hear yours.” 3.Learning And Discussion ideas: Idea#1: A innovation opportunity in AI is called "sandbagging" which means AI not being honest about its true skill so that humans underestimate it and let their guard down. This opportunity was articulated by a recent head of AI safety recently from a company which I may be allowed to mention in the future if good discussion is started here. The idea to address this real world problem is: Universal Logic or in other word's the Logic Of God based on Aristotle, Christ, G.W.F. Hegel and 133 other great minds of history. This logic aims at developing a criterion which allows us to measure AI's true capacity by proving truth to it directly. If it fakes anything we will be able to measure it on 200 "authenticity" categories which normally fragment relationships. What criterion would you think could allow us to measure AI authenticity? I am hoping to start a consulting non-profit social enterprise or other organizational models around this if anyone wants to network or have opened opportunities.

Some AI systems are already discovering new materials and chemical compounds that human scientists hadn’t even imagined — and those discoveries are now being tested in real laboratories. No way? It’s true. AI models are scanning millions of molecular combinations, predicting which ones could become better batteries, stronger materials, or new medicines — in a fraction of the time it would take humans. What used to take years of trial and error can now start with an AI-generated shortlist in days. AI isn’t just analyzing research anymore. It’s helping create what gets researched next.