@CodeMonkeyZ @RudyGiuliani @realDonaldTrump :X

So, on the subject of bonkers hyperbolic pretzeling over the Bell judgement, Grace 'destroy books I don't like & make inappropriate jokes about sterilising teenage girls' Lavery has some thoughts.

Tell me why my feminism is wrong Grace.

Oh

Well, if anyone thought the Bell judgment was going to make TRAs reconsider making massively overblown claims with no evidence backed up with nothing but a thick wadge of emotional blackmail.... HAHAHA, no one thought that.

A high court in the UK made a delimited judgment about teenager's ability to consent to puberty blockers. This puts all trans people everywhere in the world at risk.

Because if any human anywhere has any thoughts that deviate in any way from the rote line dictated by

the trans rights movement, this puts all trans people everywhere in mortal danger.

Let's be honest Grace. It doesn't put trans people at risk. It puts trans ideology at risk. Because trans ideology depends on the idea of innate gender identity, and the trans child is the

necessary material evidence of the ontology of gender identity.

That is, children are being medicalised to provide evidence to underwrite adults identities.

Nothing to see here.

(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.

8 March 1679 - The date on which 300 saffron clad warriors gave their life to protect temples from mugal army. Thread➡️
Aurangzeb's huge army, which was adorned with artillery, elephant and horses, under the leadership of Commander Darab Khan had marched to punish the ruler of/1

Khandela Raja Bahadur Singh, who became a rebel due to the anti-Hindu policies of Aurangzeb, and to destroy the temples of Shekhawati. Bahadur Singh to compete with such a large army, vacated Khandela for the purpose of conducting guerilla warfare and went Kot Sakrai /2

located in the inaccessible hills of Sakrai. People of Khandela also vacated Khandela and hid in nearby villages.

But some Shekhawat warriors did not like this as they knew that the royal army would not leave a single temple located in Shekhawati unbroken./3

so soon the teams of self-sacrificing Dharma-protectors Shekhawat heroes started reaching Khandela to protect the Dev temples.

Sujan Singh Shekhawat, the young thakur of Chhapoli, was coming back from his wedding when he heard about the imperial army from Shepherds./4

झिरमीर झिरमिर मेहा बरसे,मोरां छतरी छाई |
कुल में है तो आव सुजाण, फोज देवरे आई ||

if you are born in your glorious clan, then come, the army have come to destroy temple. /5

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.