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Posted: Tue Apr 12, 2016 2:16 pm     Super secret spam barrier
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Black Box Science Era


So I was reading through TiBS today and came across an interesting phrase that put into words something that I've been thinking about for a couple of years now.

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"Computational modeling, intensive artificial intelligence (AI) systems, and rigorous statistical procedures are increasingly being placed at the heart of biotechnology together with highly innovative methods, techniques, and ideas from engineering, biology, computer science, physics, and chemistry. In addition to the increased breadth of technologies, there is also a rapidly increasing size and velocity of data being generated to the extent that human data supervision is coming to an end [3]. We are entering an era where scientists can no longer check, verify, replicate, or even analyze the deluge of incoming data. Scientific research is becoming a black box that provides us with new knowledge."

Gustafsson, C.,  Vallverdú, J., (2016) The Best Model of a Cat Is Several Cats. TRENDS IN BIOTECHNOLOGY. 34(3). 207-213. DOI: http://dx.doi.org/10.1016/j.tibtech.2015.12.006 

Weird title I know.
I thought it was quite interesting to see that it is being acknowledged that we are moving towards an era in which we will no longer be able to keep a track on exactly what is occurring during the collection of scientific data. No doubt this is a long way off for most fields, and since computers have logs I'm sure people could follow each step, however it seems this verbalises movement in this direction, towards an era where future scientists may become dependent on automated technologies and software/AI they do not fully understand. No doubt a long way off and/or a sci-fi-esque notion, but it looks more and more realistic every year.



[Also the warhammer nerds might see parallels with the Standard Template Constructs from 40k :p] 


Posted: Tue Apr 12, 2016 5:11 pm     Super secret spam barrier
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Read something interesting in NewScientist recently pondering over the issue that most machine-learning projects now, while immensely powerful and successful, are black boxes to us. We know that the output is right, but we have no idea how the bloody hell it produced the output... so are any extensions or predictions it makes valid? Can we ever know without actually testing them? It's a tricky area, but a suggestion is training a machine-learning system to decode the active machine-learning system's method. You may be able to see the issue that emerges though :P


Posted: Tue Apr 12, 2016 6:55 pm     Super secret spam barrier
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You want weird, look at bio-inspired algorithms.  On the face of it they should not work, but instead they prove to be reliable and robust.  The downside is they impossible to prove correct.


Posted: Tue Apr 12, 2016 7:27 pm     Super secret spam barrier
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lifetap wrote:
bio-inspired algorithms.  On the face of it they should not work, but instead they prove to be reliable and robust.

Image


Posted: Wed Apr 13, 2016 3:27 pm     Super secret spam barrier
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Wat

http://www.washington.edu/news/2016/04/ ... -language/

Tweety Bird


Posted: Wed Apr 13, 2016 3:43 pm     Super secret spam barrier
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who are studying business administration and aeronautics and astronautics engineering

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Posted: Wed Apr 13, 2016 3:59 pm     Super secret spam barrier
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Not sure why you find that funny...?


Posted: Wed Apr 13, 2016 4:40 pm     Super secret spam barrier
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For those intereted in AI, check this out. Robots adapting to simulated damage/part failure.

Pretty cool.



Posted: Wed Apr 13, 2016 5:03 pm     Super secret spam barrier
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Nick Seafort wrote:
Not sure why you find that funny...?

Just never heard of it before in my 14 years of engineering. Aero and astronautics is a science, physics specifically, rather than engineering. I guess you had to be there.

Don't deny me my small pleasures Seafort.


Posted: Wed Apr 13, 2016 6:08 pm     Super secret spam barrier
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Speaking as someone with an MSc in Astronauting Engineering, I'd challenge your assertion :P


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