So, are there any results of technological achievements from any AI models that show a trend towards increasing solving of scientific and technical problems?
I think you’re going to need to link to some proof or example. You’re clearly using a definition of AI that’s broader than the colloquial definition everyone’s assuming you’re using.
The very first link shows that this is incremental benefit that’s been taking place since 2010. Computational tools are useful, but you’re providing mostly links of algorithms/learning models to sort pictures for medical purposes and diagnosis (useful and cool), and saying that somehow that means fusion will be solved by AI
I’m not saying we should exclude any tools, I’m just skeptical about the trend of calling everything AI, attributing all computational advances to AI, and jumping into the bandwagon of businesses trying to oversell any and all computating as AI.
Like if I go to Journal of Fusion Energy – https://link.springer.com/journal/10894 – the latest article is titled ‘Artificial Neural Network-Based Tomography Reconstruction of Plasma Radiation Distribution at GOLEM Tokamak’ and the 4th-latest is ‘Deep Learning Based Surrogate Model a fast Soft X-ray (SXR) Tomography on HL-2 a Tokamak’. I am sorry if that upsets you but that’s the way the field is.
By fusion, what do you mean?
Nuclear fusion
So, are there any results of technological achievements from any AI models that show a trend towards increasing solving of scientific and technical problems?
Yes. I mean, this is absolute basics.
I think you’re going to need to link to some proof or example. You’re clearly using a definition of AI that’s broader than the colloquial definition everyone’s assuming you’re using.
Here is the latest edition of Nature Machine Intelligence, to give you a basic idea of the sort of research that constitutes the AI field: https://www.nature.com/natmachintell/current-issue
Topics in Frontiers In Artificial Intelligence: https://www.frontiersin.org/journals/artificial-intelligence/research-topics
Foundations and Trends in Machine Learning: https://www.nowpublishers.com/MAL
Please give me the examples
https://www.frontiersin.org/research-topics/66705/the-future-of-oncology-digital-twins-and-precision-cancer-care
https://www.frontiersin.org/research-topics/66585/artificial-intelligence-based-multimodal-imaging-and-multi-omics-in-medical-research
https://www.frontiersin.org/research-topics/65016/deep-learning-for-industrial-applications
etc.: https://www.frontiersin.org/journals/artificial-intelligence/research-topics
https://www.nature.com/articles/s42256-024-00883-x
https://www.nature.com/articles/s42256-024-00882-y
https://engineering.princeton.edu/news/2024/02/21/engineers-use-ai-wrangle-fusion-power-grid
The very first link shows that this is incremental benefit that’s been taking place since 2010. Computational tools are useful, but you’re providing mostly links of algorithms/learning models to sort pictures for medical purposes and diagnosis (useful and cool), and saying that somehow that means fusion will be solved by AI
I’m mostly answering the question I was asked: what are some examples of technical research in the field.
How can we solve plasma control without AI? And why exclude that tool?
I’m not saying we should exclude any tools, I’m just skeptical about the trend of calling everything AI, attributing all computational advances to AI, and jumping into the bandwagon of businesses trying to oversell any and all computating as AI.
Like if I go to Journal of Fusion Energy – https://link.springer.com/journal/10894 – the latest article is titled ‘Artificial Neural Network-Based Tomography Reconstruction of Plasma Radiation Distribution at GOLEM Tokamak’ and the 4th-latest is ‘Deep Learning Based Surrogate Model a fast Soft X-ray (SXR) Tomography on HL-2 a Tokamak’. I am sorry if that upsets you but that’s the way the field is.