[No Title Available]

Collet, Celia Letícia Gouvêa

doi:10.1590/s0104-93132012000100013

Cited by 2 publications

(2 citation statements)

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“…From this perspective, we distinguish within the material design practices at the intersection with biology a specific pathway that we can define as "bio-digital fabrication" or "digital biofabrication," which is different from other practices based on the use of living matter. In particular, we can distinguish four macro-fields (Collet, 2013;Camere and Karana, 2017) that also correspond to a more general difference of biofabrication from other living matter-based technological platforms (Mironov et al, 2009): i) "growing design," that matches with biomanufacturing and refers to the possibility to produce sustainable materials and biomolecules harnessing living matter as a raw material through making, crafting and tangible practices; ii) "augmented biology," that matches synthetic biology and refers to the synthesis of new biological entities and materials from genome engineering; iii) "bio-digital fabrication," that complies with biofabrication and stretches the possibilities of biological manipulation adopting computational tools, digital advanced manufacturing technologies and mathematical modeling tools involving nature as object of design processes; iv) "biodesign fiction," which does not properly focus on the productive paradigms of the present, but imagines-often with conceptual visions-far provocative futures for advanced biotechnological developments.…”

Section: The Legacy Of Biological Fabrication: New Material-based Bio...mentioning

confidence: 99%

How the informed relations between physical, digital and biological dimensions are changing the design practice, as well as the sustainability paradigm

Rotondi

2023

Front. Bioeng. Biotechnol.

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In the “century of biotechnology”, a new form of “bio-digital industry” is emerging in which, thanks to increasingly sophisticated and digitized technologies that allow engineering and production on a biological quantum scale, it is possible to analyze and reproduce the generative, chemical, physical, and molecular processes underlying natural mechanisms. Inheriting methodologies and technologies from biological fabrication, bio-digital practices foster a new material-based biological paradigm that, bringing biomimicry to a material level, allows designers to observe substances and logic used by nature for assembling and structuring its materials, developing more sustainable and strategic ways for artifice manufacturing, as well as replicating complex, tailored, and emergent biological qualities. The paper aims to describe the new hybrid manufacturing techniques, demonstrating how the transition from form-based to material-based approaches also leads to the change of logic and conceptual frameworks in design practices, allowing greater alignment with the paradigms of biological growth. In particular, the focus is on informed relations between physical, digital, and biological dimensions, allowing interaction, development, and mutual empowerment between entities and disciplines belonging to them. Such a correlative strategy can help design to apply systemic thinking, from the scale of the material to that of the product and the process, paving the way to sustainable scenarios, not simply to reduce the human impact on the ecosystem but to enhance nature through original cooperation and integration forms between humans, biology, and machines.

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Section: The Legacy Of Biological Fabrication: New Material-based Bio...mentioning

confidence: 99%

How the informed relations between physical, digital and biological dimensions are changing the design practice, as well as the sustainability paradigm

Rotondi

2023

Front. Bioeng. Biotechnol.

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“…Apart from more traditional and general-purpose compression algorithms like LZ4 [20] and LZMA [21], model quantization [22], [23] and sparsification [10], [11], [13] are also referred to as compression techniques in ML. Given that model parameters are floating point numbers, quantization aims at representing such numbers as integers with a smaller bit length.…”

Section: B Communication Compressionmentioning

confidence: 99%

Get More for Less in Decentralized Learning Systems

Dhasade,

Kermarrec,

Pires

et al. 2023

2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS)

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Decentralized learning (DL) systems have been gaining popularity because they avoid raw data sharing by communicating only model parameters, hence preserving data confidentiality. However, the large size of deep neural networks poses a significant challenge for decentralized training, since each node needs to exchange gigabytes of data, overloading the network. In this paper, we address this challenge with JWINS, a communication-efficient and fully decentralized learning system that shares only a subset of parameters through sparsification. JWINS uses wavelet transform to limit the information loss due to sparsification and a randomized communication cut-off that reduces communication usage without damaging the performance of trained models. We demonstrate empirically with 96 DL nodes on non-IID datasets that JWINS can achieve similar accuracies to full-sharing DL while sending up to 64% fewer bytes. Additionally, on low communication budgets, JWINS outperforms the state-of-the-art communication-efficient DL algorithm CHOCO-SGD by up to 4× in terms of network savings and time.

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[No Title Available]

Cited by 2 publications

References 0 publications

How the informed relations between physical, digital and biological dimensions are changing the design practice, as well as the sustainability paradigm

How the informed relations between physical, digital and biological dimensions are changing the design practice, as well as the sustainability paradigm

Get More for Less in Decentralized Learning Systems

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