On Bayesianism, the Many Worlds Interpretation, and personal identity.
Some thoughts worked out in a letter to a friend, which is the kind of thing you do when off Twitter for a glorious week. (🧵)
https://t.co/DhHmN0ndjx
Is there a fact of the matter as to whether the cat is alive before you open the box?
— Avraham Eisenberg (@avi_eisen) November 8, 2020
I would say not, and all your references to how the world "is" are similarly incoherent.
Wait so you disagree with 'quantum splitting means that that there are futures where you become the next US president and futures where you murder your family and futures where you spontaneously combust' takes?
— Peli Grietzer (@peligrietzer) November 8, 2020
Can you defend this distinction between past and future splits?
— Avraham Eisenberg (@avi_eisen) November 8, 2020
You mentioned personal identity, are you going to argue that personal identity splits even if we're unaware of any differences?
My issue is what forks \u201cspace\u201d itself? Obv we need a QG theory, but MWI assumes some background independence or metaphysical substrate in which alternative quantum states can resolve.
— U.S.O.U.S. (@hyperauxetic) November 8, 2020
You think there's a fact of the matter about whether you are Classical Simon1 or Classical Simon2? My instinct is that there isn't, if they are qualitatively identical to each other
— Peli Grietzer (@peligrietzer) November 8, 2020
If both have the exact same memories and you can't tell which one "you" are, then from your perspective there shouldn't be a fact of the matter as to which one you are. At least, that's my view on personal identity. What's the argument against?
— Avraham Eisenberg (@avi_eisen) November 8, 2020
Not sure how that's relevant to personal identity.
— Avraham Eisenberg (@avi_eisen) November 8, 2020
Simon, I don't mean to distract you from your brilliant thread, here, but what would you say to a Meillassouxian-type committed to an arche-fossil as the basis of absolute contingency?
— NAF Loves Meillassoux (@LovesNaf) November 8, 2020
Not sure this is what you\u2019re looking for, but Tegmark uses cosmic rays causing cancerous mutations as one example of quantum splitting have observable macro effects.
— Matt Clancy (@mattsclancy) November 8, 2020
More from Simon DeDeo
Imagine for a moment the most obscurantist, jargon-filled, po-mo article the politically correct academy might produce. Pure SJW nonsense. Got it? Chances are you're imagining something like the infamous "Feminist Glaciology" article from a few years back.https://t.co/NRaWNREBvR pic.twitter.com/qtSFBYY80S
— Jeffrey Sachs (@JeffreyASachs) October 13, 2018
The article is, at heart, deeply weird, even essentialist. Here, for example, is the claim that proposing climate engineering is a "man" thing. Also a "man" thing: attempting to get distance from a topic, approaching it in a disinterested fashion.
Also a "man" thing—physical courage. (I guess, not quite: physical courage "co-constitutes" masculinist glaciology along with nationalism and colonialism.)
There's criticism of a New York Times article that talks about glaciology adventures, which makes a similar point.
At the heart of this chunk is the claim that glaciology excludes women because of a narrative of scientific objectivity and physical adventure. This is a strong claim! It's not enough to say, hey, sure, sounds good. Is it true?
More from Data science
Here is a compilation of resources (books, videos & papers) to get you going.
(Note: It's not an exhaustive list but I have carefully curated it based on my experience and observations)
📘 Mathematics for Machine Learning
by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong
https://t.co/zSpp67kJSg
Note: this is probably the place you want to start. Start slowly and work on some examples. Pay close attention to the notation and get comfortable with it.
📘 Pattern Recognition and Machine Learning
by Christopher Bishop
Note: Prior to the book above, this is the book that I used to recommend to get familiar with math-related concepts used in machine learning. A very solid book in my view and it's heavily referenced in academia.
📘 The Elements of Statistical Learning
by Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie
Mote: machine learning deals with data and in turn uncertainty which is what statistics teach. Get comfortable with topics like estimators, statistical significance,...
📘 Probability Theory: The Logic of Science
by E. T. Jaynes
Note: In machine learning, we are interested in building probabilistic models and thus you will come across concepts from probability theory like conditional probability and different probability distributions.
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Where to begin?
So our new Secretary of State Anthony Blinken's stepfather, Samuel Pisar, was "longtime lawyer and confidant of...Robert Maxwell," Ghislaine Maxwell's Dad.
"Pisar was one of the last people to speak to Maxwell, by phone, probably an hour before the chairman of Mirror Group Newspapers fell off his luxury yacht the Lady Ghislaine on 5 November, 1991." https://t.co/DAEgchNyTP
OK, so that's just a coincidence. Moving on, Anthony Blinken "attended the prestigious Dalton School in New York City"...wait, what? https://t.co/DnE6AvHmJg
Dalton School...Dalton School...rings a
Oh that's right.
The dad of the U.S. Attorney General under both George W. Bush & Donald Trump, William Barr, was headmaster of the Dalton School.
Donald Barr was also quite a
Donald Barr had a way with words. pic.twitter.com/JdRBwXPhJn
— Rudy Havenstein, listening to Nas all day. (@RudyHavenstein) September 17, 2020
I'm not going to even mention that Blinken's stepdad Sam Pisar's name was in Epstein's "black book."
Lots of names in that book. I mean, for example, Cuomo, Trump, Clinton, Prince Andrew, Bill Cosby, Woody Allen - all in that book, and their reputations are spotless.