Maker movement is doing to startups what startups did to corporations.

Here is why 👇

BANASHANKARI AMMA, NEAR BADAMI (KAR)
#bharatmandir #navratri2021

Originally built by Chalukyas in 7th century. Devi Banashankari was their family deity. This image of Banashankari Amma was installed by Jagadekamalla I in 630 AD.

Later renovations were done by Marathas.

Once, a demon Durgamasur was troubling the people of this area. Answering the prayers of Devas, Ma Parvati emerged from the yajna fire as Banashankari and killed Durgamasur.
This area has rich forests of coconut, betel nut and other trees.
@GunduHuDuGa

It is said that during a severe famine, Devi provided vegetables and fruits to the people of this area.
Hence, she is also worshipped here as Shakambhari.
In the annual festival called Banashankari jatre, a Rath yatra takes place and Devi moves around the city in the chariot.

Beautiful story of Shri Krishna, Mata Rukmini & Satyabhama which teaches the importance of Bhakthi.
Devotion is important than anything.
#bhakthi
🕉
Satyabhama, royal princess was very proud of herself. Rukmini was very humble, her devotion was pure to Shri Krishna.

One day, Rishi Narada( Kalahapriya) arrived in Dwaraka and met Sathyabhama. In between the conversation he hinted that Krishna exhibits affection more to Rukmini than her. Worried Sathyabhama asked what can should be done to gain Krishna's undivided attention.
@SriramKannan77

Narada asked Satyabhama to make a vow, that she will hand over Krishna to him as a slave, if she cannot trade wealth equivalent to Krishna's weight. Narada thus convinces Sathyabhama that Krishna will admire her for sacrificing all her wealth for him.

Sathyabhama was sure that she have enough wealth to balance Krishna.

She went to Krishna and told about her vow to Narada. Krishna patiently listened to her and accepted the challenge. Satyabhama arranged to bring large scales to weigh and brought all her precious jewels.

Krishna patiently sat on one plate of the Scales (tula). Sathyabhama started piling up the gold, jewels on the other plate. She kept adding more and more wealth, but the pan with Krishna did not even budge. Even after keeping all her jewels the scale did not move a little

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.

One thing that goes unremarked about Wikipedia: the vast majority of the content was written over 12 years ago—which means (given turnover) that the editors dominant today were not directly involved in that creation.

Put another way, the editors who built the dominant nodes in this network...

...have little overlap with the ones who made this much more recent managerial flowchart.

Internet time runs at hundred-fold speed—the difference between the people who painted what's in the Uffizi, and the people in charge of keeping those paintings from deteriorating. Very different tasks, and (one presumes) very personalities as well. @PaulSkallas?