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Work

Director of Research & Innovation Strategy

Happy Technologies LLC | May 2024 - Present

Led advanced research examining AI cognition and enterprise implementation frameworks, authoring a forthcoming monograph, "On Inference Sophistry" - a technical critique of AI reasoning capabilities and organizational adoption patterns. Placed in top 75 of Scale AI's "Humanity's Last Exam" competition and a named author. Developed strategic frameworks for enterprise AI governance in collaboration with CEO, focusing on actionable implementation methodologies and human-centered design principles.

Principal Consultant, Transformative Services

Stratascale | May 2021 - April 2024

Led enterprise-wide AI transformation initiatives as AI strategy lead, directly advising C-suite executives on strategic AI adoption and governance frameworks. Developed comprehensive AI roadmaps and pioneered internal AI adoption programs that served as proof-of-concept for Fortune 1000 client implementations. Delivered keynote speech "Navigating the AI Paradigm" at the company's annual strategic conference.

Solution Consultant, Cloud Engagement Hub

IBM | June 2020 - May 2021

Served as a futurist in cloud computing, catalyzing client transition to IBM's Hybrid Multicloud platform. Conducted comprehensive application dependency mapping and stakeholder analysis to optimize system performance and guide modernization decisions for Fortune 1000 clients.

IT Service Management Consultant

IBM | July 2017 - June 2020

Led service management transformation initiatives, managing global project teams and implementing end-to-end Service Catalog solutions in ServiceNow. Increased gross profit by over 9% through effective resource planning and successfully mitigated $1M in COVID-19 related impacts as Program Administrator.

Publications

  • On Inference Sophistry: A Philosophical and Scientific Critique - expected 2025

    The monograph explains how the paucity of 'genuine', human-like reasoning in contemporary Large Language Models (LLMs) is being justified and normalized at the societal level through top-down semantic drift. This paper shows both the "what" (LLMs can't reason like humans) and explains the "why" (the definition of reasoning is being changed to accommodate this limitation). In essence, this essay argues that the success of LLMs, despite their limitations, is partly due to a top-down semantic shift that lowers the bar for what counts as "reasoning."

  • Category-Theoretic Resolution of the Discrete-Continuous Paradox: Towards a Unified Framework for Quantum and Classical Systems - 2024

    The interplay between discrete and continuous aspects of physical reality has long presented a paradox in both physics and philosophy. By integrating discrete and continuous processes within a single categorical structure, we address the long-standing discrete-continuous paradox.

  • Adopting Generative AI in the Enterprise - 2023

    Comprehensive enterprise AI implementation framework for Fortune 1000 executives, focusing on governance, risk management, and scalable adoption strategies.

  • Breaking Down Barriers: LLMs and Mental Health - 2023

    Performed a literature review concerning the implementation and adoption of AI solutions in regulated environments, addressing compliance and ethical considerations.

  • Machine Learning for Real-Time Audio Device Profiles - 2021

    Proposed a novel application of a machine learning chip for real-time audio processing and profile storage, addressing critical challenges in assistive hearing technologies and showcasing potential advancements in user experience. [IPCOM/000266083]

  • On the Justification of Unification as a Virtue of Scientific Theories - 2017

    Investigated the philosophical underpinnings and historical trajectory of unification in physics, offering a compelling case for its adoption as a central ideal in scientific inquiry and presenting a nuanced perspective on theory choice and development.

Blog

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