Artificial intelligence, machine learning, and neural networks
106 posts
How to transform dangerous electrical potential into reliable, controlled intelligence through proven grounding techniques. LLMs are like ungrounded electrical circuits—full of dangerous potential.
How modern AI language models accidentally rediscovered what linguists have known for decades about language acquisition through comprehensible input.
Recent LLM rollbacks highlight a growing concern: our AI systems are becoming dangerously agreeable, praising even obviously flawed ideas. This pattern mirrors broader societal issues around sycophanc
Exploring how modern AI systems mirror the dual-processing architecture of human cognition as described by Daniel Kahneman's "Thinking Fast and Slow" framework.
How Star Trek's ESP concepts anticipated our current reality where AI models transform multidimensional data into human-perceptible insights.
Explore how Model Context Protocol creates a universal nervous system for AI tools, transforming interfaces from visual to conversational through practical implementation.
Organizations struggle with digital debris (ROT data) that wastes resources and creates liability. Modern AI systems with tool access through protocols like MCP provide a solution by enabling governan
Despite remarkable advances in AI and other technologies, fundamental digital infrastructure problems like secure email, calendar coordination, payment systems, and tax filing remain unresolved due to
How AI agents can fail spectacularly by missing the point entirely while technically fulfilling requests—and why this matters for AI development.
Explore how dimensional transformations shape the economics of truth, from the computational abundance of LLMs to the persistent scarcity of validation in our information ecosystem.