The Great Northern Forests of Canada, Russia and Scandinavia are doomed to destruction due to the most severe expected temperature increases from global warming anywhere on Earth which will turn them to savannah within decades with severe consequences for all life on Earth.

(THREAD) The Whitaker scandal is deepening, as it becomes clear that Sessions' Russia recusal was a coordinated sham and his firing an act of obstruction—and that his replacement is a White House plant inside the Mueller probe. I hope you'll retweet and read on for more details.

1/ From 2014-17 Whitaker worked for World Patent Marketing—which during his tenure defrauded consumers out of $26 million and was successfully prosecuted by the feds. His involvement in the scam confirmed he had loose morals and that the feds would never want to employ him again.

2/ Despite the seeming impossibility of a man with Whitaker's background getting a job at Justice ever again—he'd been found to have used his former title as a US attorney to fraudulently threaten consumers with valid complaints with criminal penalties—Whitaker found an opening.

3/ Within 60 days of parachuting out of World Patent Marketing as it was being fined $26 million by the feds, Whitaker was working for CNN and telling a fellow attorney panelist that his purpose in working for CNN was to get noticed by one man—Donald Trump—and thereby get a job.

4/ Whitaker spent his time at CNN making ludicrous statements about the Mueller probe: there was no obstruction or collusion, he said; Mueller had no authority to look into any aspect of Trump's finances or to subpoena him, he said. All the while, he hoped Trump was watching him.

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.

WHO ARE VALAKHILYAS?

Valakhilyas are 60000 Rishis who are thumb-sized. They were born to Kratu and Kriya. Rig Veda says that they sprang from the hairs of Brahma.
They move in front of Surya dev’s chariot as Sun moves daily and
shine like brilliant lights due to severe tapasya.

Tamil literature says that the main task of Valakhilyas is to prevent human beings from being scorched. They absorb the excess heat from the sun by travelling in front of him. They, in turn, get energy from Skanda and Ma Durga. The food of Valakhilyas is only wind.
@SriRamya21

Once, Rishi Kashyap performed a yagna and invited all the Devas and Rishis to help him. Indra brought a whole mountain of trees for firewood. The Valakhilyas were hardly able to lift anything but leaves. Even when they were moving leaves, they fell into rain water puddles.

Indra made fun of them. So they cursed Indra saying that his slayer would be born as the son of Kashyapa. When Indra apologized, they modified the curse that the son shall be initially an enemy of Indra, but later will become his friend.

This son born later to Kashyapa was Garuda. He flew to Indraloka to get Amrita and defeated Indra.
Later, he restored amrit vessel to Indra and was honoured as the King of birds and as the mount of Sri Vishnu.
@JumbuTweeple @artist_rama

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.