Research Notes

Parameter-Efficient Domain Adaptation: Thinking about the Specialization Dilemma

Exploring techniques for fine-tuning large language models with minimal parameter updates, enabling efficient adaptation to specific tasks.

Apr 25

Error Correction Circuit: When AI Systems Learn to Debug Their Own Thinking

Exploring the potential of self-reflective language models to identify and correct their own errors, enhancing reliability and trustworthiness.

Apr 20

Language9 min read

Compositional Language Generation: Building Complex Ideas from Simple Components

Developing architectures that generate text through explicit composition of conceptual building blocks, enabling more controllable and logical text generation.

Apr 16

Causal Reasoning: Moving LLMs Beyond Correlation

Developing architectures and training methods to enhance causal reasoning in language models - the ability to understand and reason about cause and effect relationships.

Apr 11

Frameworks7 min read

The Error Correction Circuit: How Nyāya's Error Theory Can Solve AI Self-Correction

How the Error Correction Circuit in Ātma-Bodha models implements principles from Nyāya's theory of error.

Apr 10

Epistemology7 min read

Beyond Certainty: The Role of Negative Knowledge in Intelligent Systems

Exploring the concept of negative knowledge and its implications for self-reflective language models.

Apr 9

Enhanced Language Generation Through Self-Reflection: Connecting Epistemology to Communication

Exploring the epistemological implications of language models, focusing on how they represent and access knowledge structures.

Apr 6

Reflective Language Generation: LLMs that Think Before They Speak

Developing language generation mechanisms that incorporate explicit reflection and revision before producing final outputs.

Apr 4

Frameworks7 min read

Catuṣkoṭi Logic: How Buddhist Four-Valued Logic Can Transform Our Approach to AI Uncertainty

Implementing the four-valued logic system of Catuṣkoṭi to enable more nuanced reasoning about uncertainty in language models.

Apr 1

Cognition8 min read

Neuroscience Perspectives on Metacognition in AI Systems

Exploring parallels between human metacognitive neural circuits and the Ātma-Bodha architecture.

Mar 30

Language7 min read

Separating Knowledge from Language: Towards More Factually Accurate LLMs

Exploring architectural approaches that separate factual knowledge representations from linguistic generation to reduce hallucination in language models.

Mar 28

Emergence8 min read

Emergent vs. Engineered Metacognition: Beyond Hope-Based AI Development

Comparing emergent metacognitive behaviors in conventional LLMs with engineered metacognition in self-reflective architectures.

Mar 15

Epistemology8 min read

Cross-Domain Calibration: When Models Know Different Things with Different Confidence

Addressing the challenge of calibrating model confidence across diverse knowledge domains with varying levels of certainty and evidence.

Mar 15

Cognition8 min read

Cognitive Architecture Constraints: How Structure Shapes Capability

Exploring how the structure of cognitive architectures fundamentally constrains and enables different types of intelligence and reasoning.

Mar 15

Transparency7 min read

Transparent Reasoning Paths: Making LLM Thought Processes Visible

How self-reflective language models can provide visibility into their reasoning processes.

Mar 12

Emergence8 min read

Modular Emergence: Why I'm Betting Against Monolithic AI

Exploring how specialized architectural modules can interact to produce emergent capabilities greater than the sum of their parts.

Feb 27

Epistemology8 min read

Meta-cognitive Capabilities in Self-Reflective Language Models

Exploring how self-reflective architectures enable LLMs to monitor and regulate their own reasoning processes.

Feb 20

Bayesian Reasoning Frameworks for Language Models

Implementing explicit Bayesian reasoning capabilities in LLMs to handle uncertainty and update beliefs based on new evidence.

Feb 18

Enhanced Language Generation Through Self-Reflection

How self-reflective capabilities improve language generation quality and reliability.

Feb 10

Structured Analogical Reasoning in Large Language Models

Developing explicit analogical reasoning capabilities in LLMs through structured representation and mapping techniques.

Feb 9

Reasoning4 min read

Self-Recognition Module: The Heart of Ātma-Bodha

Exploring the Self-Recognition Module (SRM) of the Ātma-Bodha architecture, which enables language models to track their own reasoning processes.

Feb 8

Reasoning3 min read

Reflective Attention Mechanism: How Ancient Wisdom Revolutionized My AI Architecture

An in-depth exploration of the Reflective Attention Mechanism component of the Ātma-Bodha architecture.

Feb 5

Emergence7 min read

Multi-Level Emergence in Cognitive Architectures

Investigating how emergent properties manifest across different levels of abstraction in language model architectures, from token statistics to high-level reasoning.

Jan 30

Transparency7 min read

Metacognitive Explanations: LLMs that Explain Their Own Reasoning

Developing language models capable of explaining their own reasoning processes and sources of knowledge to create more transparent AI systems.

Jan 25

Cognition8 min read

Abstract Reasoning Mechanisms in Large Language Models

Investigating the cognitive mechanisms that enable language models to perform abstract reasoning across diverse domains.

Jan 21

Introducing Ātma-Bodha: Self-Reflective Language Models

Introducing a novel architecture that embeds metacognitive capabilities in large language models.

Jan 9

Frameworks7 min read

Nyāya Inference Framework: Ancient Logic for Modern AI Reasoning

Adapting the five-part syllogism structure from Nyāya philosophy to create more robust reasoning frameworks for language models.

Jan 8

Frameworks5 min read

Pratyabhijñā Philosophy: How Ancient Wisdom Transformed My Approach to Self-Reflective AI

Exploring how the Recognition (Pratyabhijñā) school of Kashmir Shaivism offers profound insights for designing self-reflective AI systems.

Jan 3

Emergence6 min read

Validating Emergent Abilities: Rigorous Frameworks for Testing Emergence Claims

Developing rigorous evaluation methodologies to validate claims of emergent capabilities in increasingly powerful language models.

Jan 2

Reasoning4 min read

Code as Reasoning: Enhancing LLM Logic Through Programming Languages

Investigating how programming languages can provide a structured medium for language models to express and verify complex reasoning.

Dec 23

Abductive Reasoning: Teaching AI the Art of Explanation

Exploring techniques to enhance abductive reasoning in language models - the ability to infer the most likely explanation from incomplete information.

Dec 20

Counterfactual Reasoning: My Journey Teaching LLMs to Explore Alternate Realities

Enhancing language models with the ability to reason about events that didn't happen but could have - a crucial aspect of human cognition.

Dec 20

Epistemology5 min read

Pramāṇa-Based Knowledge Acquisition in Language Models

Applying the Nyāya theory of valid knowledge sources (pramāṇas) to create more epistemically robust language models.

Dec 20

Epistemology7 min read

The Knowledge-Behavior Gap: Bridging Epistemology and Action in Intelligent Systems

Exploring the disconnect between epistemological awareness and behavioral action in AI systems, and early approaches to bridge this gap.

Dec 15

Cognition6 min read

Neural-Symbolic Integration in Cognitive Architectures

Exploring hybrid architectures that combine neural network flexibility with symbolic reasoning guarantees for more robust cognitive capabilities.

Dec 14