3 ms·
The title from AP is misleading. They are not using any "AI" but a simple principle component analysis and a Monte Carlo minimizer. > In this approach, we appl
by sandgiant 4y ago
The title from AP is misleading. They are not using any "AI" but a simple principle component analysis and a Monte Carlo minimizer.
> In this approach, we apply principal components
analysis (PCA) to a large library of high-fidelity, high-
resolution general relativistic magnetohydrodynamic
(GRMHD) simulations and obtain an orthogonal basis of
image components. PRIMO then uses a Markov Chain Monte
Carlo (MCMC) approach to sample the space of linear
combinations of the Fourier transforms of a number of PCA
components while minimizing a loss function that compares the
resulting interferometric maps to the EHT data.
As an exercise in matching up MHD models with real data this can be an interesting study. Too bad the reporting is so off point, as usual. But I guess adding "AI" to your titles gets you more clicks these days.
- mdp2021 4y ago> They are not using any It analyzes data to arrive to a qualitative determination (the "shape"), also enabling further computation based on it (the mass): that counts as AI. "Otherwise you would have had to figure it out through your own direct intellectual effort" counts as AI.
- sandgiant 4y agoI'm not sure what you mean, but the techniques they are using are not new and are not related to artificial intelligence. They use a 120 year old numerical technique to "super-sample" their expensive simulations, which allows them to "fit" the simulations to data in a robust way. They do the calculations in a computer because there are too many numbers to do it on paper. That does not mean it has anything to do with AI.
- mdp2021 4y agoI understood that PCA is there as one of the employed ways to augment the input data, then other ways are employed for the analysis of the data - that is where the literal "Artificial Intelligence" happens. -- Edit: see also, for example: > In contrast, PCA finds correlations between different regions in Fourier space in the training data, which allows PRIMO to generate physically motivated inferences for the unobserved Fourier components ...inferences are drawn on the interpolated data. Automated model building.