Noah’s Latest Research
This policy proposal contains seven policies for secondary schools to increase college matriculation rates (quality education), increase workforce salaries, and improve industry, innovation, and infrastructure. Each policy aligns to one or more Sustainable Development Goals (SDGs) outlined by the United Nations.
This research presents a new model for a neural network structure that is loosely based on the design of atoms and molecules, allowing for a circular flow of data. This has the benefit of allowing for pass-through nodes (increasing efficiency significantly) and allowing us to more accurately predict the binary state of a particular node in advance (0 or 1).
First, we begin with a description of the technical architecture of ChatGPT and how it differs from other large scale artificial intelligence language models. From there, we define the current use cases of ChatGPT, followed by an analysis of some of the current limitations of ChatGPT. In particular, we look at the inability of ChatGPT to be creative, issues of perpetuating biases, and possibility of identification. Finally, we look at some of the likely key impacts of ChatGPT, including copyright considerations and economic ramifications. As much as possible, this analysis is done from a non-technical standpoint, and seeks to show how AI is beginning to connect with daily life.
This paper analyzes both differential privacy and data de-identification. While differential privacy seeks to create differentially private data through the use of mathematics, data de-identification seeks to anonymize data in such a way that it cannot be re-identified at a later date. In addition, we analyze the challenges of both methods of approaching privacy, including the possibility of data re-identification and verification of privacy, before addressing possible methods of mitigating these challenges. Such methods include setting outer bounds of data, utilizing shared central databases with larger datasets, and grouping data into fewer data category buckets. The merits and benefits of both methods are discussed as well.
This paper uses mathematics to analyze the challenges of geometrically noisy environments on triangulation. Given widely accepted algorithmic triangulation methods, such as O (n ln n) or a simpler O (n3) method, we can mathematically prove that triangulation of any two dimensional polygonal region is possible, albeit impractical in some cases. Further, we consider the implications of environments in which a z-axis is present, as seen in cellular triangulation. In many of the cases where consideration of the z-axis is necessary, we recognize the absence of a fixed or known point of origin and consider methods of addressing this challenge.
Traditional computational power calculations rely on the assumption that additional processing power is best achieved by a quantitative increase in transistors, and particularly through a quantitative increase in the number of metal-oxide-semiconductor field-effect transistors (MOSFETs). However, advancements in microprocessor architecture could fundamentally alter the method in which additional processing power is achieved, thus rendering traditional computational power calculations meritless.