milagr05o56 karma2018-12-21 02:08:56 UTC
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milagr05o55 karma2021-05-25 15:50:58 UTC
The "American Empire" and the EU for that matter are under threat from long-term-serving (pseudo) elected leaders in Russia and China. Specifically, with the power of their intelligence services, both Russia and China are playing long-term strategies, thus shifting the world economy, subverting democracy, and overall getting away with whatever they wish. Short-term elected representatives seem powerless. Do you foresee an adaptive response to these global threats, one that would/could defend America from all enemies, foreign and domestic?
milagr05o52 karma2015-03-20 17:15:47 UTC
Would you consider this Roach character a practitioner of Dark Dharma?
Is the "dark night" similar to experiences described in the Dark Night of the Soul?
milagr05o52 karma2021-10-08 16:56:16 UTC
John, I purchased and read the hard copy of "The End of Science". As a postdoc, I seriously considered changing my profession (thankfully, I did not). Twenty-five years later, I am inclined to revisit my impressions of that book as being overly pessimistic, though I admit it has influenced my way of thinking, perhaps just as much as "Fooled by Randomness".
For the past eight years, I've grappled with fundamental questions that most people active in the AIML arena willfully ignore. "What is truth?" (and when is something true)... "What is knowledge" (and when do we know it)... Things of this sort. It vexes me that scientists just keep happily churning their experimental papers, without a second thought to such matters. And that AIML model developers plug those in, and spew out results, without consideration to what's true vs scientific artifact. (reproducibility in cancer biology - eLife series comes to mind, and analyses from John Ioannidis, C. Glenn Begley, Khusru Asadullah, etc.). Data, facts, even knowledge have a limited shelf life. From my perspective, AIML will benefit humanity only as far as we can feed models truth. Else, GIGO...
Clearly, you've struggled with similar questions. How do you deal with it? How do you reconcile "what we think we know" with "what is true"? And how to train the next generation of AIML researchers to develop algorithms / models that are more likely to point towards the truth?
BTW, I was very disappointed when some clever mathematicians informed me that there's no way for AIML to discern "true data" from "false data"...
milagr05o51 karma2019-07-16 12:01:24 UTC
Manned mission to Mars: Government or private sector? Or both? Did you think we'd still be Earth-bound five decades after the Moon landing?
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