Starting a Synthetic Biological Intelligence Lab from Scratch

Wedi'i Gadw mewn:
Manylion Llyfryddiaeth
Cyhoeddwyd yn:arXiv.org (Dec 18, 2024), p. n/a
Prif Awdur: Md Sayed Tanveer
Awduron Eraill: Patel, Dhruvik, Schweiger, Hunter E, Kwaku Dad Abu-Bonsrah, Watmuff, Brad, Azadi, Azin, Pryshchep, Sergey, Narayanan, Karthikeyan, Puleo, Christopher, Natarajan, Kannathal, Mostajo-Radji, Mohammed A, Kagan, Brett J, Wang, Ge
Cyhoeddwyd:
Cornell University Library, arXiv.org
Pynciau:
Mynediad Ar-lein:Citation/Abstract
Full text outside of ProQuest
Tagiau: Ychwanegu Tag
Dim Tagiau, Byddwch y cyntaf i dagio'r cofnod hwn!

MARC

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022 |a 2331-8422 
035 |a 3147267226 
045 0 |b d20241218 
100 1 |a Md Sayed Tanveer 
245 1 |a Starting a Synthetic Biological Intelligence Lab from Scratch 
260 |b Cornell University Library, arXiv.org  |c Dec 18, 2024 
513 |a Working Paper 
520 3 |a With the recent advancements in artificial intelligence, researchers and industries are deploying gigantic models trained on billions of samples. While training these models consumes a huge amount of energy, human brains produce similar outputs (along with other capabilities) with massively lower data and energy requirements. For this reason, more researchers are increasingly considering alternatives. One of these alternatives is known as synthetic biological intelligence, which involves training \textit{in vitro} neurons for goal-directed tasks. This multidisciplinary field requires knowledge of tissue engineering, bio-materials, digital signal processing, computer programming, neuroscience, and even artificial intelligence. The multidisciplinary requirements make starting synthetic biological intelligence research highly non-trivial and time-consuming. Generally, most labs either specialize in the biological aspects or the computational ones. Here, we propose how a lab focusing on computational aspects, including machine learning and device interfacing, can start working on synthetic biological intelligence, including organoid intelligence. We will also discuss computational aspects, which can be helpful for labs that focus on biological research. To facilitate synthetic biological intelligence research, we will describe such a general process step by step, including risks and precautions that could lead to substantial delay or additional cost. 
653 |a Tissue engineering 
653 |a Energy requirements 
653 |a Artificial intelligence 
653 |a Digital computers 
653 |a Digital signal processing 
653 |a Machine learning 
653 |a Biological activity 
653 |a Alternative energy sources 
653 |a Computer programming 
700 1 |a Patel, Dhruvik 
700 1 |a Schweiger, Hunter E 
700 1 |a Kwaku Dad Abu-Bonsrah 
700 1 |a Watmuff, Brad 
700 1 |a Azadi, Azin 
700 1 |a Pryshchep, Sergey 
700 1 |a Narayanan, Karthikeyan 
700 1 |a Puleo, Christopher 
700 1 |a Natarajan, Kannathal 
700 1 |a Mostajo-Radji, Mohammed A 
700 1 |a Kagan, Brett J 
700 1 |a Wang, Ge 
773 0 |t arXiv.org  |g (Dec 18, 2024), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3147267226/abstract/embedded/ZKJTFFSVAI7CB62C?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/2412.14112