Francis Clase
AI Researcher
3 years of research in superintelligence, AI safety, and advanced AI systems. Exploring the theoretical foundations and practical implications of artificial general intelligence.
Research Overview
I focus on understanding the dynamics of advanced AI systems, from theoretical models of superintelligence to practical questions of AI safety and alignment. My work bridges foundational theory with emerging empirical evidence from modern AI development.
Publications
Research contributions to AI safety and superintelligence theory.
The Intelligence Explosion: From Singular Event to Complex System Dynamics
Francis Clase
Independent Research • 2025
A comprehensive analysis synthesizing 60 years of intelligence explosion theory, from I.J. Good's foundational 1965 hypothesis through modern critiques and alternative models.
Unexplored Frontiers in AI Superintelligence Research
Francis Clase
Research Survey • 2025
Systematic identification of theoretical gaps and practical opportunities in superintelligence research. Covers documentation gaps, interdisciplinary connections, and accessible research projects.
AI Safety Frameworks for Advanced Systems
Francis Clase
In Progress • 2025
Developing practical safety evaluation frameworks for AI systems approaching human-level capabilities across multiple domains.
Empirical Analysis of Large Language Model Capabilities
Francis Clase
Technical Report • 2024
Systematic evaluation of reasoning capabilities and emergent behaviors in current large language models.
Value Alignment in Multi-Agent AI Systems
Francis Clase
Working Paper • 2024
Exploring coordination mechanisms and value preservation in systems with multiple interacting AI agents.
Latest Research Highlights
Recent developments and ongoing work in AI safety and superintelligence theory.
Intelligence Explosion Dynamics
Comprehensive analysis of 60 years of theory from Good to modern critiques.
AI Safety Frameworks
Developing practical evaluation frameworks for advanced AI systems.
LLM Capabilities Study
Systematic evaluation of reasoning and emergent behaviors.
Research Specializations
Core areas of focus in artificial intelligence research.
Superintelligence Theory
Analyzing intelligence explosion dynamics, recursive self-improvement, and takeoff scenarios.
AI Safety & Alignment
Exploring control problems, value alignment, and safety measures for advanced AI systems.
Emerging AI Systems
Studying current AI developments and their implications for future superintelligent systems.
Explore Research Topics
From ensuring AI systems align with human values to optimizing performance at scale, modern AI research spans multiple interconnected disciplines. Below are simplified introductions to key research areas.
AI Safety & Alignment
How do we ensure AI systems do what we want them to do? This field focuses on making AI systems that understand human values, follow instructions reliably, and remain safe as they become more capable.
Model Training
Training AI models requires massive amounts of data and computation. Researchers study how models learn, how to make training more efficient, and how model capabilities scale with increased resources.
Performance Engineering
Making AI systems run faster and more efficiently. This involves optimizing hardware usage, reducing memory requirements, and ensuring models can handle real-world workloads at scale.
Interpretability
Understanding how AI systems make decisions. When a model produces an output, can we explain why? This research helps us peek inside the “black box” of neural networks.
ML Infrastructure
Building the systems that power AI research. This includes specialized hardware, distributed training systems, and the software infrastructure needed for large-scale machine learning.
Multimodal & Specialized AI
AI that can understand and work with multiple types of information - text, images, audio, and more. Also includes specialized applications like biology research and scientific discovery.
Research Collaboration
Interested in discussing AI safety, superintelligence theory, or potential research collaborations? Connect with Francis Clase for academic exchanges and research insights.