James E Dobson
Dados Biográficos
| ID | 3625147 |
|---|---|
| NOME | James E Dobson |
| PRENOMES | James E |
| SOBRENOME | Dobson |
| ASSINATURA | DOBSON J E |
| AFILIAÇÕES | Dartmouth College |
| ORCID | 0000-0001-8357-7240 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 6 |
| TOTAL DE CITAÇÕES | 0 |
| OBRAS COMO AUTOR | 6 |
| OBRAS COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2020 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 0 |
Neural network computing before GPUs
This article reconstructs the media archeology of the graphics processing unit (GPU) by locating this device in a history of neural co-processors that begins with early learning machines such as Frank Rosenblatt’s Mark I Perceptron and runs through massively parallel systems, systolic arrays, and Google’s Tensor Processing Unit to contemporary multi-core GPUs and embedded neural accelerators. These co-processing devices have been ubiquitous in th…
Beyond Computational Formalism or, Architecture Matters
Despite frequently avowed commitments to formalist methodologies, computational literary studies (CLS) has insufficiently accounted for the importance of the formal architectures of the computational models it employs—particularly deep learning neural networks. Arguing against the tendency to treat neural networks with an abstract gloss of their operation or to focus attention on the outputs, this article posits that architecture is not merely a …
On Personal and Impersonal Data
This article historicizes the concept of personal data by turning to a mid-twentieth-century autobiographical encounter with everyday data, E. B. White’s 1945New Yorker essay “About Myself.” In tracking crucial differences that mark the contemporary quantification of the self as distinct from earlier modes of numerical self-understanding, the author argues that the data presented in White’s essay are information that index an individual within a …
On the Confusion Matrix
Confusion matrices are graphical objects used in machine learning to demonstrate the efficacy of models. They frequently take the form of brightly colored figures adorning scientific reports and technical documents. Guiding readers of these texts through an interpretation of models with their special affordances, such as diagonal lines that draw the eye from one corner to the other, confusion matrices function as graphical arguments. That they in…
Objective Vision
Convolutional neural networks (CNNs) are a key technology powering the automated technologies of seeing known as computer vision. CNNs have been especially successful in systems that perform object recognition from visual data. This article examines the persistence of a mid-twentieth-century ontology of the digital image in these contemporary technologies. While CNNs are multidimensional, their ontology flattens distinctions between background an…
Interpretable Outputs
There are a number of risks to interpretability found in the growing use of complicated computational methods within the humanities. Greater attention needs to be given to the format and presentation of the underlying data and the interpretation of any data-derived results. Visually appealing graphic renderings of data, high classification accuracy and confidence scores, and impressive summary statistics can be rhetorically structured to appeal t…
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Interpretable Outputs
There are a number of risks to interpretability found in the growing use of complicated computational methods within the humanities. Greater attention needs to be given to the format and presentation of the underlying data and the interpretation of any data-derived results. Visually appealing graphic renderings of data, high classification accuracy and confidence scores, and impressive summary statistics can be rhetorically structured to appeal t…
Objective Vision
Convolutional neural networks (CNNs) are a key technology powering the automated technologies of seeing known as computer vision. CNNs have been especially successful in systems that perform object recognition from visual data. This article examines the persistence of a mid-twentieth-century ontology of the digital image in these contemporary technologies. While CNNs are multidimensional, their ontology flattens distinctions between background an…
On the Confusion Matrix
Confusion matrices are graphical objects used in machine learning to demonstrate the efficacy of models. They frequently take the form of brightly colored figures adorning scientific reports and technical documents. Guiding readers of these texts through an interpretation of models with their special affordances, such as diagonal lines that draw the eye from one corner to the other, confusion matrices function as graphical arguments. That they in…
Beyond Computational Formalism or, Architecture Matters
Despite frequently avowed commitments to formalist methodologies, computational literary studies (CLS) has insufficiently accounted for the importance of the formal architectures of the computational models it employs—particularly deep learning neural networks. Arguing against the tendency to treat neural networks with an abstract gloss of their operation or to focus attention on the outputs, this article posits that architecture is not merely a …
On Personal and Impersonal Data
This article historicizes the concept of personal data by turning to a mid-twentieth-century autobiographical encounter with everyday data, E. B. White’s 1945New Yorker essay “About Myself.” In tracking crucial differences that mark the contemporary quantification of the self as distinct from earlier modes of numerical self-understanding, the author argues that the data presented in White’s essay are information that index an individual within a …
Neural network computing before GPUs
This article reconstructs the media archeology of the graphics processing unit (GPU) by locating this device in a history of neural co-processors that begins with early learning machines such as Frank Rosenblatt’s Mark I Perceptron and runs through massively parallel systems, systolic arrays, and Google’s Tensor Processing Unit to contemporary multi-core GPUs and embedded neural accelerators. These co-processing devices have been ubiquitous in th…
Artificial Intelligence (2 obras) · Computer Science (2 obras) · Cybernetics and Technology in Society (2 obras) · Psychology (2 obras) · Advanced Mathematical Theories (1 obra) · Aesthetic Perception and Analysis (1 obra) · Architecture (1 obra) · Art (1 obra) · Artificial neural network (1 obra) · Big Data Technologies and Applications (1 obra)