AI is all the rage
Chatbots like ChatGPT are amazing, able to spit out everything from poems to business plans. But all this excitement about Large Language Models (LLMs) masks a deeper problem: They're not the path to real, human-like intelligence.
LLMs: Fancy Parrots, Not Thinkers or problem solvers
LLMs are great at pattern recognition. They've been fed massive amounts of text, allowing them to "mimic" how we speak and write. Smooth phrasing often results in neglecting factual accuracy prioritizing on fluid language generation, at the expense of factual accuracy. This differs significantly from people, who strategically leverage facts for specific goal communication and persuasion. LLMs haven't fully developed the contextual understanding or nuanced decision-making ability needed for expert systems.
The Need for Logic and Reasoning
True AI requires more than just processing language. It needs the ability to reason, to understand cause and effect, and to build knowledge in the same way a child learns. This means incorporating elements like logic (think simple math equations) and decision-making frameworks (like IF/THEN scenarios) into the way AI processes information.
The Path to Smarter AI
The good news is that researchers are already working on AI models that fuse language with visual and logical reasoning. These models offer a real breakthrough, moving away from glorified calculators and towards machines that can problem-solve and adapt like we do. This is the type of AI that can truly work alongside us, not just impress us with fancy text tricks.
Don't Fall for the Hype
LLMs are useful tools, but they're not the silver bullet for achieving Artificial General Intelligence (AGI). A more grounded, multi-faceted approach that combines with a representation model for machine learning and knowledge of database schema (grasping relationships between data points) opens up data analysis to non-experts and greater novel lines of inquiry through natural language prompts.
Our space model for human capital offers this breakthrough building on the foundations for AI without "all things being LLM". It doesn't just imitate but innovate, working alongside humans, not in place of them.
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