[HN Gopher] Simulation Intelligence: Towards a New Generation of...
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       Simulation Intelligence: Towards a New Generation of Scientific
       Methods (2022)
        
       Author : fastneutron
       Score  : 58 points
       Date   : 2023-01-19 19:19 UTC (3 hours ago)
        
 (HTM) web link (arxiv.org)
 (TXT) w3m dump (arxiv.org)
        
       | fastneutron wrote:
       | Submission statement: I came across this article earlier today
       | and it hit home on a lot of things that have been swirling in my
       | head lately on the current direction of scientific computing
       | methods. I work in R&D in this space, and would be curious to
       | hear the perspectives of others on the methods surveyed in this
       | paper.
        
         | [deleted]
        
       | nathias wrote:
       | Thanks for sharing, this looks really interesting, the approaches
       | of including AI in theory of science are extremely interesting
       | and will potentially create a new scientific paradigms. Things
       | really are happening right now.
        
       | m0llusk wrote:
       | The idea of improving quality and relevance of simulations with
       | machine learning makes a lot of sense to me and seems like it
       | might help to avoid some of the problems that so called AI can
       | have where they draw dramatically incorrect conclusions from
       | large but flawed data sets. At the same time it seems like these
       | technologies could be used to jump to completely bizarre
       | conclusions that quickly become contaminated with imperfections,
       | distortions, and other analysis about data. In a way it seems
       | like this is starting to duplicate problems humans have with the
       | irregular borders between brilliance and madness.
        
         | fastneutron wrote:
         | From a pragmatic perspective, being able to use AI to
         | accelerate or otherwise enhance computations for science and
         | engineering has a pretty big value proposition. Being able to
         | turn around high fidelity calculations in a fraction of the
         | time would yield much better product designs and scientific
         | results.
         | 
         | On the flip side, like you suggest, the cost of being wrong can
         | much higher than many current uses of AI. This is where
         | research into AI interpretability, robustness, and uncertainty
         | quantification can really help.
        
       | dr_dshiv wrote:
       | I read recently about Francis Bacon's scientific method. It was
       | not the modern method. It focused more on creating lists of
       | contrasting cases, focusing on inductive reasoning. Honestly, I
       | didn't entirely understand. Robert Hooke had a method, too, which
       | he described as a philosophical "superstructure."
       | 
       | Some variety in how knowledge is automatically/systematically
       | developed seems important.
        
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       (page generated 2023-01-19 23:00 UTC)