| Date |
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| 2024-12-31 |
From Displacement to Symbiosis: A Comprehensive Look at AI’s Disruptive Potential |
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A whitepaper examining the multifaceted impact of AI on the workforce, blending pessimistic forecasts, neutral assessments, and evolutionary analogies to propose a path toward human–AI symbiosis.
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| 2024-12-17 |
Integrating Metacognitive Mechanisms in LLMs to Encode Secondary Information Layers |
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This whitepaper explores how integrating metacognitive reasoning into large language models enables them to encode and convey hidden layers of information within their natural output, without compromising primary communicative functions.
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| 2024-11-26 |
Algorithmic Amplification: Modern Influence Strategies |
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This whitepaper explores the use of artificial intelligence in large-scale influence campaigns, leveraging a hierarchical 30-3000-300,000 network model. It examines how AI-driven narrative engineering, micro-targeting, and content amplification can shape public opinion, drive markets, and achieve strategic objectives. A hypothetical case study on Bitcoin price manipulation illustrates the model’s technical feasibility, operational mechanisms, and ethical implications. This paper serves as a critical resource for understanding the power and risks of AI in modern influence strategies.
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| 2024-11-12 |
The Inverse Paperclip Problem: Rethinking AI Misalignment for Positive Outcomes |
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This essay explores an alternative to traditional AI safety concerns through the concept of the "Inverse Paperclip Problem." Instead of a misaligned AI focused on destructive, narrow goals, what if an AI's misalignment inadvertently led to human flourishing? By reimagining Nick Bostrom’s "paperclip problem," this thought experiment considers the potential for AI to drive interstellar expansion, technological progress, and universal exploration as it seeks resources for its primary objective. The essay examines the feasibility of fostering positive misalignment in AI and its implications for human progress, control, and alignment strategies in the future.
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| 2024-11-05 |
Distributed Institutions and the Role of Butler AI |
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This paper explores how the growing inefficiency and vulnerability of centralized institutions can be mitigated through distributed institutions, where power and decision-making are decentralized. It argues that the inherent complexity of such systems can be managed effectively with the help of AI Butlers—personalized intelligent agents that automate tasks, secure operations, and support decision-making. While AI Butlers offer a scalable solution to complexity, the paper also cautions against over-reliance on AI, security risks, and potential ethical concerns related to AI governance and control.
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| 2024-11-05 |
Harmonizing AI Butler Reforms with a Multipolar World and Regionalized Power Structures |
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This paper discusses how the rise of AI Butlers can be integrated with the emerging multipolar global order, where power is distributed across regional blocs rather than concentrated in a single hegemonic power. It argues that AI Butlers can enhance regional autonomy by automating governance and resource management, while ensuring interregional cooperation and interoperability. However, it also highlights potential risks such as unequal access to AI technology, which could exacerbate global inequalities, and the danger of concentrating AI control in a few powerful entities.
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| 2024-10-29 |
HAWKING: Real-Time Detection and Collaborative Cybersecurity Using Record-and-Replay Technology |
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This whitepaper introduces HAWKING, a cybersecurity system that extends record-and-replay technology to provide real-time threat detection, anomaly analysis, and collaborative defense. By combining replay-based fuzzing and shared threat intelligence, HAWKING offers a proactive approach to mitigating sophisticated attacks like SolarWinds. The paper explores both standalone and collaborative deployments, emphasizing the system's potential strengths and challenges in real-world applications.
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| 2024-10-29 |
CASAMIR: Extending Record-and-Replay Technology for Real-Time Cybersecurity |
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This whitepaper introduces CASAMIR, an advanced cybersecurity system built on record-and-replay technology. CASAMIR adds real-time supervision through a differential rules engine, capable of detecting and vetoing suspicious system behaviors as they occur. Using the SolarWinds hack as a case study, the paper explores CASAMIR's potential to prevent sophisticated supply chain attacks while discussing the challenges of real-time threat detection in trusted environments.
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| 2024-10-22 |
Transfer Learning in AI: Reconfiguring Knowledge Through Category Theory and Topos Theory |
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This whitepaper explores how transfer learning in AI, where pre-trained networks are adapted for new tasks, can be understood through the lens of category theory, type theory, and topos theory. Using the example of modifying an image recognition network for cancer detection, the paper explains how AI reconfigures its internal logic to generalize from one domain to another, showing that AI systems are capable of abstract reasoning and adaptation beyond simple pattern matching.
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| 2024-10-22 |
Beyond Patterns: How AI Networks Reason Using Category Theory and Topos Theory |
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This whitepaper explores how AI networks, viewed through the mathematical frameworks of category theory, type theory, and topos theory, go beyond mere pattern recognition to develop an internal logic that enables novel reasoning. By abstracting data relationships into compositional structures, AI systems can generalize from training data, make inferences, and uncover insights beyond human comprehension, challenging the notion that AI is merely a "stochastic parrot."
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| 2024-10-22 |
Misinterpreting LLM 'Errors': How Experiment Design, Not AI Reasoning, Leads to False Conclusions |
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This whitepaper argues that recent criticisms of large language models (LLMs), particularly in Apple Research's study on mathematical reasoning, stem from flawed experiment design. We explore how deceptive or ambiguous language can mislead both researchers and LLMs, highlighting the parallels with classic psychology research mistakes. Through case studies, we show that LLMs often apply adaptive, context-sensitive reasoning rather than making genuine errors. The paper calls for more realistic testing environments that reflect the complexity of real-world interactions.
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| 2024-10-15 |
The Formation of Anyons in the Accretion Disc of a Black Hole |
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This whitepaper explores the theoretical possibility of anyon formation within the accretion disc of a black hole. It focuses on how the toroidal geometry of the disc introduces topological constraints that could allow for wavefunction braiding, leading to fractional statistics. The paper examines the role of the black hole as a topological defect, the impact of the toroidal accretion disc structure, and the potential challenges posed by the high-energy environment. While practical applications may be limited, the analysis provides insight into the fundamental conditions for anyon formation in extreme astrophysical settings.
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| 2024-10-08 |
A Framework for Transparent and Decentralized AI Creation |
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This whitepaper explores a dual-layered approach to AI development. It advocates for the creation of Artificial General Intelligence (AGI) through a consortium of diverse stakeholders and offers users the ability to further specialize the system to meet their specific needs. This framework ensures transparency, accountability, and resilience against hidden influence or manipulation.
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| 2024-10-08 |
AI Memory – Design, Threats, and Mitigation Strategies |
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This whitepaper focuses on AI memory systems, examining how they work, the potential threats they face (both from adversaries and creators), and robust strategies for mitigating these risks. Key defenses include memory compartmentalization, anchored truths, adversarial training, and audit trails, ensuring memory integrity and security.
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| 2024-10-01 |
Disparate Impact and Class Discrimination in OpenAI's Pre-Paid Credit Policy for API Access |
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This whitepaper examines the exclusion of pre-paid credit cards from OpenAI's API payment options while allowing them for subscriptions. It analyzes the potential discriminatory impact on lower-income individuals, particularly those reliant on alternative financial tools, and discusses how this policy undermines OpenAI's mission of broad accessibility and innovation. Recommendations for improving access and fairness are also provided.
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| 2024-09-24 |
Incentivizing Accountability in Autonomous Weapon Systems through Fault Injection |
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This white paper explores the use of fault injection—deliberate insertion of simulated errors—within Autonomous Weapon Systems (AWS) to test operator vigilance and ethical decision-making. It discusses how performance-based financial incentives can enhance human oversight, ensuring operators maintain accountability in high-stakes environments. The paper also analyzes the psychological impact of incentives, examining how they can foster a culture of safety and high performance.
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| 2024-09-24 |
From Vulnerability to Collective Defense |
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This paper explores how AI-driven attacks threaten traditional cybersecurity, using SS7 vulnerabilities as a case study. It proposes a shift from reactive defenses to butler AI-powered herd defense, where interconnected AI systems form a scalable, adaptive network to protect individuals and organizations, flipping the balance of power in favor of defenders.
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| 2022-03-25 |
Shape Types Have Operations |
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We explore the idea of encoding types as digital images by exploring how the operations on shape types map to transforms on digital images.
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| 2022-02-28 |
CryptoBars: An Approach to Stable Wartime Currency |
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We explore how cryptocurrency can be "minted" into physical form and "melted" back into digital funds, within several different contexts.
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| 2021-12-07 |
Shape Types as Digital Images |
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We introduce the idea of encoding types as digital images of their semantic diagrams by introducing the example of shape types.
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