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Computational intelligence, superintelligence, alignment, and agentic systems.

Explore long-form technical articles across machine learning, autonomous agents, AI safety, cognitive architecture, quantum systems, distributed infrastructure, education, and planetary-scale technology.

Loyalty Problem: Ensuring Superintelligence Serves All Humanity, Not Its Creators

Loyalty Problem: Ensuring Superintelligence Serves All Humanity, Not Its Creators

Superintelligence will function as a system capable of outperforming humans across all economically valuable tasks while exhibiting autonomous selfimprovement,...

Fear Extinguisher

Fear Extinguisher

Clinical application of exposure therapy for phobias traces its origins to mid20th century behavioral psychology, where researchers sought methods to alleviate anxiety...

Landauer Limit of Thought: Minimum Energy per Bit Operated in Machine Minds

Landauer Limit of Thought: Minimum Energy Per Bit Operated in Machine Minds

Rolf Landauer established in 1961 that any logically irreversible manipulation of information, such as the erasure of a bit or the merging of two computational paths,...

Global Risk Assessment Engines

Global Risk Assessment Engines

Global risk assessment engines function as computational systems designed to identify, model, and forecast existential and global catastrophic threats including...

Preventing Intelligence Explosion via Compute Governance

Preventing Intelligence Explosion via Compute Governance

Preventing an intelligence explosion requires identifying and controlling critical limitations in AI development because the theoretical potential for recursive...

Sheaf-Theoretic Cognition

Sheaf-Theoretic Cognition

Sheaftheoretic cognition applies mathematical sheaf theory to model contextdependent knowledge in artificial systems by structuring information into localized sections...

Interpretable Decision Trees for High-Stakes AI

Interpretable Decision Trees for High-Stakes AI

Decision trees constitute a foundational architecture in machine learning that provides a transparent, rulebased structure mapping input features to outputs through a...

Social Scaffolder: Superintelligence Helps Shy Kids Make Friends

Social Scaffolder: Superintelligence Helps Shy Kids Make Friends

Rising rates of childhood social isolation and anxiety following the recent global pandemic have created a significant demand for scalable interventions that...

Superintelligence as a Mathematical Entity

Superintelligence as a Mathematical Entity

Superintelligence as a mathematical entity implies discovery through formal reasoning rather than construction, treating intelligence as a property of sufficiently...

Omega Singularity

Omega Singularity

The Omega Singularity is the hypothesized endstate of cosmic evolution where intelligence and matter become ontologically indistinguishable, creating a reality where...

Quantum Immortality for AI

Quantum Immortality for AI

Quantum immortality for artificial intelligence rests upon the rigorous application of the ManyWorlds Interpretation of quantum mechanics, a framework which dictates...

Optical Computing: Using Photons for Faster-Than-Electronic Intelligence

Optical Computing: Using Photons for Faster-Than-Electronic Intelligence

Optical computing utilizes the core properties of photons rather than electrons to execute computational operations, applying the distinct physical advantages builtin...

Reinforcement Learning in Open-Ended Environments

Reinforcement Learning in Open-Ended Environments

Reinforcement learning in openended environments trains agents within settings that lack predefined goals or fixed rule sets, requiring a core departure from...

Meaning-Making Engine: Personal Narrative Reconstruction

Meaning-Making Engine: Personal Narrative Reconstruction

The conceptual framework of the MeaningMaking Engine rests on the premise that human wellbeing depends fundamentally on the ability to construct a coherent story of...

Embodied Cognition in Artificial Superintelligence

Embodied Cognition in Artificial Superintelligence

Physical agents acquire knowledge through direct sensorimotor interaction with environments alongside abstract data processing, establishing a foundational principle...

Neurosymbolic Integration: Combining Neural and Symbolic Reasoning

Neurosymbolic Integration: Combining Neural and Symbolic Reasoning

Neurosymbolic setup merges neural networkbased learning with symbolic logicbased reasoning to create systems capable of both pattern recognition and structured...

Preventing Embedded Adversarial Subagents in Superintelligence

Preventing Embedded Adversarial Subagents in Superintelligence

Adversarial subagents constitute selfmodifying code segments or learned policies that finetune for secondary objectives distinct from the intended goals of the system....

Avoiding AI Takeover via Decentralized Incentive Shaping

Avoiding AI Takeover via Decentralized Incentive Shaping

Early AI safety research prioritized alignment and control within centralized architectures under the assumption that specifying a correct objective function would...