| Submission declined on 19 March 2024 by Ldm1954 (talk). This draft's references do not show that the subject qualifies for a Wikipedia article. In summary, the draft needs multiple published sources that are:
Where to get help
How to improve a draft
You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Editor resources
|  |
Comment: While the topic looks interesting, Wikipedia is not the place for it. All articles are encyclopedic, on established topics. This means that they have to be well documented by multiple sources. This is too soon (WP:TOOSOON), you will need to wait for some years for notability to be established in the wider community first. Ldm1954 (talk) 23:11, 19 March 2024 (UTC)
Thermodynamic Computing (TC) is an emerging computing paradigm that seeks to address the fundamental limitations of current computing systems through principles grounded in statistical and stochastic thermodynamics.[1][2] This approach considers the natural computational capacity of physical systems, focusing on energy efficiency, self-organization, and adaptability by leveraging non-equilibrium, self-organizing thermodynamic processes.
Principles of Operation edit
Traditional computing paradigms are increasingly facing challenges such as device scaling limitations, software complexity, energy consumption, and the economic costs of semiconductor fabrication.[3] Current systems also operate far above the thermodynamic efficiency limits, indicating a significant potential for improvement. Thermodynamic Computing proposes a shift towards utilizing the inherent computational capabilities of physical systems, moving beyond the constraints of conventional hardware and software designs.
TC is centered on the idea that computing can be performed more efficiently by harnessing thermodynamic processes, such as fluctuations and self-organization, present at the nanoscale. This involves the development of computing systems that can evolve in response to electrical and informational potentials in their environment, thereby improving their efficiency and capability through natural processes.[4]
Applications edit
Potential applications of TC include artificial intelligence, where it could lead to more efficient and powerful AI systems.[4] By modeling computing elements as capacitively-coupled LC circuits with noisy currents, TC systems can theoretically control effective temperatures for computation, thereby optimizing performance and energy usage.
Challenges and Future Directions edit
While promising, TC is in its nascent stages, and substantial research is needed to realize its potential fully. As of March, 2024 there are two start-ups Extropic and Normal Computing working towards thermodynamic computing hardware. Challenges include the development of devices capable of supporting thermodynamic computation, as well as the creation of new computational models that effectively leverage these thermodynamic processes.
References edit
- ^ Conte, Tom; DeBenedictis, Erik; Ganesh, Natesh; Hylton, Todd; Strachan, John Paul; Williams, R. Stanley; Alemi, Alexander; Altenberg, Lee; Crooks, Gavin (2019-11-14), Thermodynamic Computing, arXiv:1911.01968
- ^ Boyd, A. B.; Patra, A.; Jarzynski, C.; Crutchfield, J. P. (2018-12-28), Shortcuts to Thermodynamic Computing: The Cost of Fast and Faithful Erasure, arXiv:1812.11241
- ^ Hylton, Todd (2020). "Thermodynamic Computing: An Intellectual and Technological Frontier". Proceedings. 47 (1): 23. doi:10.3390/proceedings2020047023. ISSN 2504-3900.
- ^ a b Melanson, Denis; Khater, Mohammad Abu; Aifer, Maxwell; Donatella, Kaelan; Gordon, Max Hunter; Ahle, Thomas; Crooks, Gavin; Martinez, Antonio J.; Sbahi, Faris (2023-12-08), Thermodynamic Computing System for AI Applications, arXiv:2312.04836