#E.T. Jaynes

[averycanadianfilm]

But our present QM formalism is not purely epistemological; it is a peculiar mixture describing in part realities of Nature, in part incomplete human information about Nature - all scrambled up by Heisenberg and Bohr into an omelette that nobody has seen how to unscramble. Yet we think that the unscrambling is a prerequisite for any further advance in basic physical theory. For, if we cannot separate the subjective and objective aspects of the formalism, we cannot know what we are talking about; it is just that simple.

E. T. Jaynes 

[arriving-at-new-equilibrium]

E.T. Jaynes pings my gaydar for some reason.

And a quick skim of information online doesn’t turn up any mention of a spouse...

[di--es---can-ic-ul-ar--es]

Even a pure mathematician actually uses weaker forms of reasoning [e.g. induction] most of the time. Of course, on publishing a new theorem, the mathematician will try very hard to invent an argument which uses only the [strong] kind [i.e. deduction]; but the reasoning process which led to the theorem in the first place almost always uses one of the weaker forms (based, for example, on following up conjectures suggested by analogies).

E.T. Jaynes -- Probability: the Logic of Science -- pg6

[weirdlandtv]

READERS’ MAIL

I receive quite a few messages from readers every day, so occasionally I have to answer them all in one go, otherwise I’ll fall too far behind. So here goes...

Have I heard any Lana Del Rey songs? Not consciously. Maybe if one featured in a film or something. I’ve heard her name though; next time I come across her I’ll pay more attention.

@commitdefenestration Have I seen the video of Brigitte Bardot kissing a seal pup? You mean that footage of her visit to Canada in 1977? Oh yeah. She was one of the first celebrities, if not the first, who put animal rights on the map. I hope to see the day that fur gets banned. Obviously if you love animals you don’t want them to get tortured in harrowing ways.

Do I like the B-52s? I only know two songs by them, so I’m not sure.

What do I think of Jayne Mansfield? No opinion honestly. She existed and made some movies, but if she hadn’t existed or hadn’t made any movies, my life would be exactly the same.

Am I male or female? That one again, eh?

What do I think about the recent allegations against Michael Jackson? I’m committed to the belief that he’s innocent. That belief is the result of my having followed the history of the allegations against him, past and present, through the years. When I hear that some radio stations are banning his music, I shake my head. None of this all matters in the long run.

Do I have any favorite books? When I was in my 20s I tried to read every classic in existence, “Don Quixote”, “Lolita”, “Paradise Lost”, Homer’s “Odyssey”, et cetera, but these days I don’t really go there anymore. Generally I like biographies: Rasputin, Jesus, Hitler, Disney, Roald Dahl, Napoleon, Jim Henson, Steve Jobs, whoever. When I read a biography I get very immersed in it and read a lot of stuff around it, always looking up things online: photos, locations, birthplaces, faces, articles, and for a few weeks I become a specialist on the subject, the world’s leading authority, the foremost expert—then, once I’ve finished the book, I forget nearly everything except a few random facts and quotes. (However, I’m an enthusiastic re-reader.) I like books that explain the history behind a phenomenon, company, event; books on art and design, and music; and the unusual. And everything by Dutch author, Harry Mulisch (1927-2010).

What year was I born? You can guess...

And lastly...

What do you really think of the cinematic works (and especially the fantasy adventures) of George Lucas and Steven Spielberg, respectively? Also, what are your favorites among all the works of Lucas and Spielberg themselves? Just asking.

When I grew up in the 1980s, Lucas and Spielberg were gods. They could light up the night skies, which suddenly were teeming with stars and spaceships and distant worlds that beckoned. It’s sometimes said that Star Wars killed cinema, but it saved a generation: because of the genre in which they operated, the works of Spielberg and Lucas beamed out hope, possibilities, exploration, adventure, magic, the power of imagination and dreams. They inspired. Kids in the 1960s had The Beatles, we had Lucas and Spielberg; and it felt like they had a hand in everything that wowed us on the screen, on TV, and in toy stores; and in a way, they did.

The best thing Lucas has ever done of course is the STAR WARS trilogy. Ever since the prequels, efforts have been made to diminish his contribution to it, but he was always the guiding force: Star Wars didn’t come from a studio, not from a group of executives in a room, but from his rogue imagination (and then it became bigger than that).

My favorite Spielberg film has to be E.T. THE EXTRA-TERRESTRIAL. The film itself was like an alien friend to me when I was a kid, a benign presence, both loving and spellbinding. Spielberg has a reputation for producing schmaltzy endings, but when his sentimental finales are justified and not just dutifully tacked on, they make for very powerful cinema. I like the Indiana Jones trilogy (not the fourth one), and SCHINDLER’S LIST, his monochrome monument to the evil that men do. Another personal favorite is DUEL, his version of David and Goliath. Like the shark in JAWS is more than a shark, the truck in DUEL is more than a truck: it’s a force of evil, a roaming demon that attaches itself to an ordinary guy. You can view DUEL as a petty feud between two drivers, or as a clash between good and evil, or both; it’s a simple road thriller that, by the power of suggestion, invites all sorts of theories and interpretations. The tank truck has to be one of my favorite movie villains.

And that’s it for now. I might do this more often; most of the messages I receive are sent anonymously and I don’t always want to reply to all of them separately.

[chrisaldrich]

How Life (and Death) Spring From Disorder | Quanta Magazine

This is a nice little general interest article by Philip Ball that does a relatively good job of covering several of my favorite topics (information theory, biology, complexity) for the layperson. While it stays relatively basic, it links to a handful of really great references, many of which I’ve already read, though several appear to be new to me. [1][2][3][4][5][6][7][8][9][10]

While Ball has a broad area of interests and coverage in his work, he’s certainly one of the best journalists working in this subarea of interests today. I highly recommend his work to those who find this area interesting.

References

[1]

E. Mayr, What Makes Biology Unique? Cambridge University Press, 2004.

[2]

A. Wissner-Gross and C. Freer, “Causal entropic forces.,” Phys Rev Lett, vol. 110, no. 16, p. 168702, Apr. 2013. [PubMed]

[3]

A. Barato and U. Seifert, “Thermodynamic uncertainty relation for biomolecular processes.,” Phys Rev Lett, vol. 114, no. 15, p. 158101, Apr. 2015. [PubMed]

[4]

J. Shay and W. Wright, “Hayflick, his limit, and cellular ageing.,” Nat Rev Mol Cell Biol, vol. 1, no. 1, pp. 72–6, Oct. 2000. [PubMed]

[5]

X. Dong, B. Milholland, and J. Vijg, “Evidence for a limit to human lifespan,” Nature, vol. 538, no. 7624. Springer Nature, pp. 257–259, 05-Oct-2016 [Online]. Available: http://dx.doi.org/10.1038/nature19793

[6]

H. Morowitz and E. Smith, “Energy Flow and the Organization of Life,” Santa Fe Institute, 07-Aug-2006. [Online]. Available: http://samoa.santafe.edu/media/workingpapers/06-08-029.pdf. [Accessed: 03-Feb-2017]

[7]

R. Landauer, “Irreversibility and Heat Generation in the Computing Process,” IBM Journal of Research and Development, vol. 5, no. 3. IBM, pp. 183–191, Jul-1961 [Online]. Available: http://dx.doi.org/10.1147/rd.53.0183

[8]

C. Rovelli, “Meaning = Information + Evolution,” arXiv, Nov. 2006 [Online]. Available: https://arxiv.org/abs/1611.02420

[9]

N. Perunov, R. A. Marsland, and J. L. England, “Statistical Physics of Adaptation,” Physical Review X, vol. 6, no. 2. American Physical Society (APS), 16-Jun-2016 [Online]. Available: http://dx.doi.org/10.1103/PhysRevX.6.021036 [Source]

[10]

S. Still, D. A. Sivak, A. J. Bell, and G. E. Crooks, “Thermodynamics of Prediction,” Physical Review Letters, vol. 109, no. 12. American Physical Society (APS), 19-Sep-2012 [Online]. Available: http://dx.doi.org/10.1103/PhysRevLett.109.120604 [Source]

Syndicated to:

[haohanwang]

Friday Activity Breakdown: (2019-03-08)

起床 Wake Up and Read (4:25 AM)

03/08/2019

Morning Read (4:30-6:30AM): Probability Theory: The Logic of Science by E.T. Jaynes

03/08/2019

早餐 Chinese Learning (6:30-7AM): Morning Cooking Session

03/08/2019

Morning Presentation (7-7:30AM): Probability Theory - Random Variable

03/08/2019

Block 1 (7:30-8:30AM): Sprints Planning Session

03/08/2019

Daily Snack Pack: Celery & Celery Root & Wheat Grass & Kombu & Parsnip | 芹菜 & 芹菜根 & 小麦草 & 防风草 & 海带 3/8/2019

03/08/2019

Morning Deep Learning Lecture (9:10-9:40AM): Mathematics for Computer Science https://www.youtube.com/watch?v=6LOwPhPDwVc

03/08/2019

Morning Deep Learning Lecture (9:10-9:40M): Notes - Mathematics for Computer Science Link: https://github.com/dyadxmachina/study_notes/tree/master/Computation

03/08/2019

Lunch + Mathematics Problem Solving (12:00-12:30PM): Computer Science

03/08/2019

Lunch Break (12:30-1PM): Nap

03/08/2019

锻炼 Block Break Session 1 (9:45-10PM): Exercise

03/08/2019

Block 2 (10-12PM): Model Skeleton Remapping

03/08/2019

锻炼 Block Break Session 2 (3:10-3:30PM): Exercise

03/08/2019

Block 4 (3:30-5PM): Planning

03/08/2019

Daily Block Schedule - 3/9/2019 Saturday

03/08/2019

730 Days of Data Science Code - Day 430

03/08/2019

晚餐 Chinese Learning (5:00-5:50PM): Dinner (Raw)

03/08/2019

Daily 中文学习 Chinese learning (6:00-6:30PM): Conversation

03/08/2019

Evening Deep Learning Lecture (6:35-7:15PM): Mathematics for Computer Science https://www.youtube.com/watch?v=7lQXYl_L28w

03/08/2019

Evening Deep Learning Lecture (6:35-7:25PM): Notes - Mathematics for Computer Science Link: https://github.com/dyadxmachina/study_notes/tree/master/Computation

03/08/2019

Daily Productivity Summary Link: https://datastudio.google.com/u/0/reporting/1nDZG_J_QiC51-XfGIOzaWuPvyUgXv6XL/page/dJkR 3/8/2019

03/08/2019

Weekday Productivity Summary Link: https://datastudio.google.com/u/0/reporting/1nDZG_J_QiC51-XfGIOzaWuPvyUgXv6XL/page/gi0W 3/4/2019-3/8/2019

03/08/2019

Daily Active Listening (7:20-7:55PM): Reflection

03/08/2019

Sleep (shui jiao) (8PM)

[barbarapicci]

(via FotoStoria in bianco e nero [207° invio])

Cosa troverete: un uomo collassato dopo i festeggiamenti per la fine del proibizionismo; George Orwell che tiene un cucciolo in braccio durante la Guerra civile spagnola; E.T. in pausa sul set con Steven Spielberg; Sigourney Weaver che mangia un panino; un gruppetto di geishe festanti; uomini parigini distratti dal passaggio di Geneviève Bujold; la posa (ultra) sexy di Drew Barrymore; la bellezza esagerata di Sophia Loren; una donna afghana armata di tutto punto; Billie Holiday col suo “Mister” canino; il sorriso splendente di Raquel Welch; le rovine di Verdun; una donna che scappa durante l’assedio di Sarajevo; i capelli al vento di Ozzy Osbourne; Jayne Mansfield in relax & more…

Clicca per vedere la gallery: https://barbarapicci.com/2018/10/31/fotostoria-207/

[anthrochristianramsey]

Morning Read (4:30-5AM): Probability Theory - The Logic of Science by E.T. Jaynes > The Quantitative Rules  (Chapter 2)

10/15/2018

[yoshidas-girl-forever]

Thank you so much Anna @annalewis63​!!!!!!!!!! These things are fun!!!!!!!!! The following is in no real order!!!!!!

- Woodstock - Harold and Maude - Rocketman - Dazed and Confused - The Godfather - The Breakfast Club - E.T. - Clueless - American Graffiti - Pulp Fiction i tag @emometalhead​ @autoblast-loud-and-fast​ @what-the-fuck-happened-to-jayne​ @nymphinvelvet​ @omniayosry1​ @pitoftrash​ @my-bad-side-shows​ @fruscianted​ @harley-m-rose​ @speciallyred​ @iggy-theeskimo​ @americaspencil​ @b0hemianbarbie​ @ledzeppelinsbonzo​ and anyone who ants to do this!!!!!!!!!!  :)

Tagged by @chevroletmiserables to list my nine favourite movies!!

Klaus

Psycho

Nine

Ocean’s Eleven

Jersey Boys

Les Misérables (1978)

LotR/Hobbit trilogies (I am Not cheating, I have that 6 disc set and just started them all a little while ago lol)

Die Hard (first is the best, tho I am writing a fic for the 4th one)

Silence of the Lambs (including it’s pre- and sequel)

tagging: @jackolidus @visfar-the-101 and everybody else I usually tag that wants to!!

[haohanwang]

Monday Activity Breakdown: (2019-03-11)

Monday Activity Breakdown: (2019-03-11)

起床 Wake Up and Read (4:25 AM)

03/11/2019

Morning Read (4:30-6:30AM): Probability Theory: The Logic of Science by E.T. Jaynes

03/11/2019

Morning Presentation (7-7:30AM): Probability Theory - ESP Hypothesis Testing

03/11/2019

Block 1 (7:30-8:30AM): Packing for China

03/11/2019

Daily Snack Pack: Celery & Celery Root & Wheat Grass & Kombu & Parsnip | 芹菜 & 芹菜根 & 小麦草 & 防风草 & 海带 3/11/2019

03/11/2019

Morning Deep Learning Lecture (9:10-9:40AM): Mathematics for Computer Science https://www.youtube.com/watch?v=6LOwPhPDwVc

03/11/2019

Morning Deep Learning Lecture (9:10-9:40M): Notes - Mathematics for Computer Science Link: https://github.com/dyadxmachina/study_notes/tree/master/Computation

03/11/2019

锻炼 Block Break Session 1 (9:45-10PM): Exercise

03/11/2019

Block 2 (10-12PM): Packing

03/11/2019

Lunch + Mathematics Problem Solving (12:00-12:30PM): Computer Science

03/11/2019

Lunch Break (12:30-1PM): Nap

03/11/2019

Block 3 (1-3PM): Packing for China

03/11/2019

Block 4 (3:30-5PM): Packing for China

03/11/2019

Daily Block Schedule - 3/12/2019 Tuesday

03/11/2019

730 Days of Data Science Code - Day 433

03/11/2019

晚餐 Chinese Learning (5:00-5:50PM): Dinner (Raw)

03/11/2019

Daily 中文学习 Chinese learning (6:00-6:30PM): Conversation

03/11/2019

Evening Deep Learning Lecture (6:35-7:15PM): Mathematics for Computer Science https://www.youtube.com/watch?v=7lQXYl_L28w

03/11/2019

Evening Deep Learning Lecture (6:35-7:25PM): Notes - Mathematics for Computer Science Link: https://github.com/dyadxmachina/study_notes/tree/master/Computation

03/11/2019

Daily Productivity Summary Link: https://datastudio.google.com/u/0/reporting/1nDZG_J_QiC51-XfGIOzaWuPvyUgXv6XL/page/dJkR 3/11/2019

03/11/2019

Daily Active Listening (7:20-7:55PM): Reflection

03/11/2019

Sleep (shui jiao) (8PM)

[twentyall-blog]

One disadvantage of having a little intelligence is that one can invent myths out of his own imagination, and come to believe them. Wild animals, lacking imagination, almost never do disastrously stupid things out of false perceptions of the world about them. But humans create artificial disasters for themselves when their ideology makes them unable to perceive where their own self-interest lies.

E.T. Jaynes (from Probability Theory as Logic)

[haohanwang]

Weekend Morning Read (4:30-6:30AM): Probability Theory: The Logic of Science by E.T. Jaynes

12/29/2018

[haohanwang]

Morning Read (4:30-6:30AM): Probability Theory: The Logic of Science by E.T. Jaynes

03/06/2019

[haohanwang]

Friday Activity Breakdown: (2019-02-22)

Morning Read (4:30-6:30AM): Probability Theory: The Logic of Science by E.T. Jaynes

02/22/2019

早餐 Chinese Learning (6:30-7AM): Morning Cooking Session

02/22/2019

Morning Presentation (7-7:30AM): Probability Theory - Multiple Hypothesis Testing

02/22/2019

Block 1 (7:30-8:30AM): Model Building and Debugging

02/22/2019

Daily Snack Pack: Celery & Celery Root & Wheat Grass & Kombu & Parsnip | 芹菜 & 芹菜根 & 小麦草 & 防风草 & 海带 2/22/2019

02/22/2019

Morning Deep Learning Lecture (9:10-9:40AM): Mathematics for Computer Science https://www.youtube.com/watch?v=SmFwFdESMHI&t=1531s

02/22/2019

锻炼 Block Break Session 1 (9:45-10PM): Exercise

02/22/2019

Block 2 (10-12PM): Model Testing

02/22/2019

Lunch + Mathematics Problem Solving (12:00-12:30PM): Computer Science

02/22/2019

Lunch Break (12:30-1PM): Nap

02/22/2019

Block 3 (1-3PM): Pair Programming - Data Pipeline Setup

02/22/2019

锻炼 Block Break Session 2 (3:10-3:30PM): Exercise

02/22/2019

Block 4 (3:30-5PM): Weekly Raw Meal Prep

02/22/2019

Daily Block Schedule - 2/23/2019 Saturday

02/22/2019

730 Days of Data Science Code - Day 418

02/22/2019

Block 5 (5:10-5:50PM): Cleaning and Reorganizing

02/22/2019

晚餐 Chinese Learning (5:00-5:50PM): Dinner (Raw)

02/22/2019

Daily 中文学习 Chinese learning (6:00-6:30PM): Conversation

02/22/2019

Evening Deep Learning Lecture (6:35-7:15PM): Mathematics for Computer Science https://www.youtube.com/watch?v=SmFwFdESMHI&t=4s

02/22/2019

Evening Deep Learning Lecture (6:35-7:25PM): Notes - Mathematics for Computer Science Link: https://github.com/dyadxmachina/study_notes/tree/master/Computation

02/22/2019

Daily Active Listening (7:20-7:55PM): Reflection

02/22/2019

Daily Productivity Summary Link: https://datastudio.google.com/u/0/reporting/1nDZG_J_QiC51-XfGIOzaWuPvyUgXv6XL/page/dJkR 2/22/2019

02/22/2019

睡觉 (8PM): Sleep

02/22/2019

Sleep (shui jiao) (8PM)

[haohanwang]

Thursday Activity Breakdown: (2019-01-10)

Thursday Activity Breakdown: (2019-01-10)

Morning Read (4:30-6:30AM): Probability Theory: The Logic of Science by E.T. Jaynes

01/10/2019

早餐 Chinese Learning (6:30-7AM): Morning Cooking Session

01/10/2019

Daily Snack Pack: Celery & Celery Root & Wheat Grass & Kombu & Parsnip | 芹菜 & 芹菜根 & 小麦草 & 防风草 & 海带 (1/10/2019)

01/10/2019

Block 1 (7:30-8:30AM): Storyboard Session

01/10/2019

Morning Deep Learning Lecture (9:10-9:40AM): Mathematics for Computer Science

Block 2 (10-12PM): Storyboard Session

01/10/2019

Lunch + Mathematics Problem Solving (12:00-12:30PM): Computer Science

01/10/2019

锻炼 Block Break Session 2 (3:10-3:30PM): Exercise

01/10/2019

Block 4 (3:30-5PM):Planning

01/10/2019

Day 10 of 365 Days of Data Science Code

01/10/2019

Block Schedule for Jan. 11th, 2019 - Friday Schedule

01/10/2019

Lunch Break (12:30-1PM): Nap

01/10/2019

Block 3 (1-3PM): Storyboard Session

01/10/2019

晚餐 Chinese Learning (5:00-5:50PM): Dinner (Raw)

01/10/2019

Block 5 (5:10-5:50PM): Cleaning and Reorganizing

01/10/2019

Daily Productivity Summary (1/10/2019)

LInk: https://datastudio.google.com/u/0/reporting/1nDZG_J_QiC51-XfGIOzaWuPvyUgXv6XL/page/dJkR

01/10/2019

Daily 冥想 Meditation (6-6:30PM): Headspace

01/10/2019

Daily 中文学习 Chinese learning (6:40-7:10PM): Conversation

01/10/2019

Evening Deep Learning Lecture (7:15-8PM): Mathematics for Computer Science

Evening Deep Learning Lecture (7:15-8PM): Notes - Mathematics for Computer Science

01/10/2019

Sleep (shui jiao) (8PM)

[haohanwang]

Sunday Activity Breakdown: (2019-01-06)

Weekend Morning Read (4:30-6:30AM): Probability Theory: The Logic of Science by E.T. Jaynes

01/06/2019

Weekend 早餐 Chinese Learning (6:30-7AM): Morning Cooking Session

01/06/2019

Weekend Block 1 (7:30-8:30AM): Storyboard session

01/06/2019

Daily Snack Pack: Celery & Celery Root & Wheat Grass & Kombu & Parsnip | 芹菜 & 芹菜根 & 小麦草 & 防风草 & 海带 (1/6/2019)

01/06/2019

Weekend Morning Deep Learning Lecture (9:10-9:40AM): Mathematics for Computer Science

Morning Deep Learning Lecture (9:10-9:40M): Notes - Mathematics for Computer Science

01/06/2019

Weekend 锻炼 Block Break Session 1 (9:45-10AM): Exercise

01/06/2019

Weekend Lunch + Mathematics Problem Solving (12:00-12:30PM): Computer Science

01/06/2019

Weekend Block 2 (10-12PM): Literature Review

01/06/2019

Weekend Lunch Break (12:30-1PM): Nap

01/06/2019

Weekend Block 3 (1-3PM): 2019 Looking Forward Discussion

01/06/2019

Weekend 锻炼 Block Break Session 2 (3:10-3:30PM): Exercise

01/06/2019

Weekend Block 4 (3:30-5PM): Planning

01/06/2019

Block Schedule for Jan 6th, 2019 - Monday Schedule

01/06/2019

Daily Productivity Summary (1/6/2019)

Link: https://datastudio.google.com/u/0/reporting/1nDZG_J_QiC51-XfGIOzaWuPvyUgXv6XL/page/dJkR

01/06/2019

Day 6 of 365 Days of Data Science Code

01/06/2019

Weekend 晚餐 Chinese Learning (5:00-5:50PM): Dinner (Raw)

01/06/2019

Weekend Block 5 (5:10-5:50PM): Cleaning and Reorganizing

01/06/2019

Daily 冥想 Meditation (6-6:30PM): Headspace

01/06/2019

Daily 中文学习 Chinese learning (6:40-7:10PM): Conversation

01/06/2019

Weekend Evening Deep Learning Lecture (7:15-8PM): Mathematics for Computer Science

Weekend Evening Deep Learning Lecture (7:15-8PM): Notes - Mathematics for Computer Science

01/06/2019

Sleep (shui jiao) (8PM)