📢Superstar Shareholders Portfolio as of Dec-2021 (Latest Data available)

⚡️Arranged with Highest Holding Amount on Top !

So it's their Highest Conviction as per their Allocation/Action/Karma.

Hope this helps in your decision in picking companies during this downturn.

Arya Samaj Exposed ( A Thread)

Today I'm going to expose these so called reviver of Sanatan dharma.

Arya samaj's main book which they treat as their bible is Satyarth Prakasha. Which was written by "Maharishi" Dayanand Saraswati.

Dayanand Condemned Idol worship and blamed it on jains . like really??

The book peddles hate against several Hindu sects.

here is hate against Vaishnavas

Wracając do sedna dzisiejszego zamieszania z artykułem autosportu / motorsportu. Kubica mówi w nim, że podejmie swoją decyzję w ciągu kilku dni. Rozważa opcję z Williamsem lub posadę kierowcy symulatora w Ferrari. Więc za kilka dni dowiemy się co go czeka za rok. #F1PL

Autosport / motorsport zmienił nagłówek swoje tekstu, bo pierwotnie sugerował on że Kubica jest numerem jeden na liście Williamsa na tytuł mówiący tylko tym, że nadal jest na liście kandydatów. Zrobili to po interwencji zespołu. Same wypowiedzi Kubicy z wywiadu się nie zmieniły.

Trudno powiedzieć czy autor się pośpieszył i wyciągnął inne wnioski niż powinien, a może wie coś więcej, ale nie mógł tego otwarcie napisać. Słowa Kubicy brzmią jednak jednoznacznie: decyzję podejmie w ciągu kilku dni.

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.

Ok, I'll hop on this Elizabeth Warren/Native American testing bandwagon (gently and non-politically).

I've been a @23andMe customer for a while, and have followed their ancestry updates closely.

All is more or less as expected....except for this bit about Native American.

The family is almost completely composed of Spanish peasants (from various regions) who emigrated, along with a massive wave in the late 19th-cent./early 20th-cent., to Cuba back when it was a booming economy (richer than Spain's) and worth emigrating to (Communism killed that).

Also, the native population of Cuba was annihilated early on---was the first place the Spanish colonized after all. Having a native background in Cuba would be like having the same in, say, Massachusetts, particularly if you're (say) mostly Irish. Just really, really unlikely.

(Note: the North African/Arab background is less mysterious. The Iberian peninsula was part of the Muslim world for centuries. It would be odd *not* to have some Arab/Middle Eastern background coming from Spain. Given the family is mostly from Northern Spain, it's small though.)

I have a Spanish passport, have been back to the ancestral villages in Spain, seen the church where my grandmother was baptized, my grandfather told me stories about growing up as the child of Spanish colonists in rural Cuba. The native bit just clashes with all the family lore.