Ai Prediction #14, Ai will predict the Future. No, Ai will Create the Future.

By Greg Walters

​The models are being trained how to train itself, improving the process, not the data.​

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What is the primary function of LLMs?  PREDICTING THE NEXT word.  It isn't a search engine, sifting data and pulling out relevant content. The LLM is predictive in nature. 

As the predictive model gets better, it will outrun 'historical data'(anything older than now), thriving on live feed, real time reality. And because the models are tuned to optimum, it will predict not just words, sentences, and images, but actions, based on all the patterns of all histories, real and imagined, at the quantum and universal scale. 

​ These capabilities will become so precise that it will blur the line between predicting the future and shaping it. We will not distinguish whether AI is merely foreseeing events or actively molding the future.

​Ai won't see the future, it will create it.

"The best to predict the future, is to create the future."

The evolution of AI towards a state where it not only predicts but also influences future events is rooted in the rapid advancement of predictive analytics and machine learning algorithms. AI systems have progressively moved from descriptive analytics, which explain what has happened, to prescriptive analytics, which suggest actions that could shape future outcomes.
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• Supporting Evidence: In the business realm, AI-driven predictive models are already optimizing supply chains, forecasting market trends, and personalizing customer interactions. The leap to a scenario where AI's recommendations become so integral that they shape future business strategies is plausible.
• Societal Impact: On a societal level, AI's role in influencing public policy, healthcare decisions, and educational methodologies is emerging. If AI systems can accurately predict social trends and public responses, they could become instrumental in policy-making, effectively shaping societal futures.
• Ethical Considerations: The critical issue here is the delegation of decision-making to AI systems. The risk of diminishing human agency and the ethical implications of AI-driven decisions necessitate robust frameworks to ensure that AI acts in alignment with human values and societal good.

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This is an example of what I mean

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"AI can now predict your future. New program eerily similar to Marvel’s fictional Project Insight" - By Chris MeloreBy Chris Melore

Researchers Jonah Berger and Olivier Toubia found that students who made connections between diverse concepts in their essays tended to achieve higher grades in college.

The study introduces two key concepts:

"Semantic volume": This refers to the breadth of ideas and concepts covered in an essay. Students who explored a wider range of topics and connected distant ideas were more likely to have higher GPAs.

"Semantic speed": This measures how smoothly writers transition between different ideas. Top-performing students moved logically between concept clusters rather than jumping erratically.
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The AI system analyzes the "semantic geography" of admissions essays using natural language processing. It can predict future academic performance more accurately than traditional metrics like test scores or family income levels.

​I asked an AI expert, "What happens when the AI doesn't need our data anymore?"  reflecting on how AI will know all of our historical patterns, up to this very second.  He candidly responding, "If that happens, we won't be around anymore."  He had no idea how right he was. GW - 2024