Figuring out who to listen to and what's right/wrong in the world of social media, podcasters, and experts of everything is difficult.

As a scientist and writer here's1 trick & 6 lessons on figuring out if a writer, podcaster, or expert should be listened to or not. 👇👇👇

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.

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.

(THREAD) Pre-election Russia collusion may take down Trump. It's equally possible the Trumps' pre- and post-election collusion with Saudi Arabia, the UAE, and Israel will do it—a course of collusion also connected to the Kremlin. I explain here. I hope you'll read on and retweet.

1/ I must stress how unbelievably complex the "Grand Bargain" theory of the Trump-Russia case is—a different thing from saying it's not substantiated. It's substantiated in *almost every single particular*—it just *also* happens to be very confusing. Not byzantine—just confusing.

2/ The basics: Saudi Arabia, Israel, and the UAE all view Iran as their chief regional enemy. Iran is propped up by Russia. Therefore the Saudis, Israelis, and Emiratis all need a US government willing to find a way to get the Kremlin to *stop* supporting Iran in the Middle East.

3/ The best way to get Russia to stop supporting Iran—or reduce support—was/is to drop all sanctions on Russia over its 2014 annexation of Crimea, as that'd be worth *trillions* to the Kremlin over the next decade. Everyone knew that Clinton wouldn't do this—and that Trump would.

4/ Per the NYT, on August 3, 2016, Donald Trump Jr. met secretly at Trump Tower with a Saudi and Emirati emissary, George Nader, as well as an Israeli intelligence expert, Joel Zamel, with *significant* ties to both Israeli intelligence *and* Russian oligarchs allied with Putin.

Ever notice how the top niches are centered around health, wealth, and relationships?

There's a deep-rooted psychological (and biological) reason why.

And today, I'm gonna to explain all of it so you can start profiting off of this knowledge 💰💰

*Now, this thread is going to be long and in depth. Make sure to favorite the top tweet now so you can come back to it later.

So. Down to the very core of every living being (humans, dolphins, bacteria, aliens), there are only two drivers:
1. To survive
2. To reproduce

Right off the bat, we know that sex is a primary driver to human behavior.

This would also mean that each gender has its own insecurities regarding sex.

Men have a subconscious fear that their woman will leave them for someone more successful

Women have a fear that their man will leave them for someone younger & better-looking

We can conclude that men are attracted to looks, and women are attracted to status.

This is human nature down to its very core.

Crazy, blue-haired feminists will try to argue and say otherwise.

But, 50 years of feminism DOES NOT OVERRIDE millions of years of evolutionary biology.

Here's a quick visualization exercise so you can see how true all this is...