The revelation of the mystery: BODY OF CHRIST

Ephesians 3:6 KJV
That the Gentiles should be fellow heirs, and of the same body, and partakers of his promise in Christ by the gospel:

Gentiles have become heirs of God and ALL MEMBERS of the same body (Rom 8:17). Just like...

#DoYouKnow -The place where
Lalitha Sahasranamam -1000 names of Devi originated.

It is in Lalithambigai temple -Thirumeeyachur,Near Mayiladuthurai,TN

There is a Legend #story & it is related to this beautiful #sculpture of Kshetrapuraneswarar & Ambal Lalithambigai #Thread 👇

#Legend #story
It is believed that this is birth place of Kashyapa Maharishi’s sons, Arunan& Garudan. Arunan(charioteer of Surya)was physically handicapped.He was a Shiva devotee.Arunan wanted to visit Kailash to have Shiva Darshan,but Surya Dev denied permission.

So Arunan disguised as a girl & was on his way to Kailash.On the way Surya Dev saw this girl & outraged her modesty.Shiva was very angry with Suryan for misbehaviour & cursed him to get darkened. Whole world plunged into darkness.Surya Dev pleaded to Bhagwan Shiv to forgive him.

Shiva Bhagwan asked him to go to Thirumiyachur & worship him there. As advised, Surya Dev performed rigorous penance, placed murthi of Shiva& Parvathy on an elephant & took them to the clouds.Shiva in this temple is known as Meganathaswamy,Devi is known as Lalithambigai

Even after severe penance,Shiva does appear,so Surya Dev cries out in agony.Disturbed by his call, Parvathy protests.Siva pacifies her & offers relief to Surya Dev.The sculpture of Shiva pacifying Ambal shows her sullen from one angle &smiling from another.

SRI CHAMPAKADHAMA SWAMY, BANNERGHATTA HILL, BENGALURU (KAR)
#bharatmandir

The shrine is dedicated to Sri Vishnu along with Devi Lakshmi and Bhoodevi.
It is built in an area full of Champaka trees.
As champaka flowers are offered to Sri Vishnu here, it is called Champakadhama.

It is believed that King Janmejaya had sarpa-dosha. To get rid of it, he took bath in the nearby pond. He emerged with a golden body and sarpa-dosha was also removed. The pond is called Swarnamukhi and believed to have curative powers.
Sri Vishnu murti was consecrated by him.

It is also believed that this forest area was the Dandakaranya where Sri Ram stayed in exile.
Some believe that the original shrine was built by Pandavas.
The pushkarni/pond is emptied once a year so that the rock at the bottom (which has image of Anjaneya) may be worshipped.

A thing which I unironically and enthusiastically believe which is unpopular among smart people of my acquaintance: financial engineering has in the recent past and present contributed substantially to human welfare. We should hope to see more of it.

Maybe more geeks need to meet someone who says “My job is teleporting value across time and space.”

Financial engineering is sort of a squishy term. I don’t primarily mean payments infrastructure or financial rails, although both of those involve substantial engineering.

I mean more “We took a thing and performed some alchemy, and now have a new thing.”

Except instead of alchemy it is generally quite a bit of math, a huge amount of contract law and due diligence, often an impressive amount of ops work, and a dusting of technology that web devs would recognize as such.

Important paper from Google on large batch optimization. They do impressively careful experiments measuring # iterations needed to achieve target validation error at various batch sizes. The main "surprise" is the lack of surprises. [thread]

https://t.co/7QIx5CFdfJ

The paper is a good example of lots of elements of good experimental design. They validate their metric by showing lots of variants give consistent results. They tune hyperparamters separately for each condition, check that optimum isn't at the endpoints, and measure sensitivity.

They have separate experiments where the hold fixed # iterations and # epochs, which (as they explain) measure very different things. They avoid confounds, such as batch norm's artificial dependence between batch size and regularization strength.

When the experiments are done carefully enough, the results are remarkably consistent between different datasets and architectures. Qualitatively, MNIST behaves just like ImageNet.

Importantly, they don't find any evidence for a "sharp/flat optima" effect whereby better optimization leads to worse final results. They have a good discussion of experimental artifacts/confounds in past papers where such effects were reported.