#ADANIPOWER a perfect contraction in volatility happening here for the last 9 months.

The first drop was more than 50%, followed by a 30% and a 20% drop. This is getting really tight on the weekly charts.

Volumes have been monstrous in recent weeks!

#stockideas #trendlines

AHOBILAM NARASIMHA SWAMY KSHETRAM: KURNOOL (AP)
#andhratemples

Ahobilam is the place where Prabhu appears in his fierce form, called Ugra Narasimha, who is Svayambhu (self-manifest).
Ahobilam is one of the 108 Divya Desams. It has 9 shrines for different forms of Narsimha.

Ahobilam was the exact place where Sri Narasimha appeared and tore apart Hiranyakashipu to save Prahlad. At that moment, all the Devas appeared and praised him as Ahobala (Aho is mighty and bala is strength). So the place came to be called Ahobilam.

Out of the 9 shrines, most famous is the Ahobila Narasimha Swamy where Prabhu is seen as Ugra Narasimha.
In another shrine, Prabhu appears as Malola Narasimha Swamy. Malola means beloved of Lakshmi. Here Prabhu is in peaceful mudra with his consort Ma ChenchuLakshmi.

Jwala Narasimha Swamy shrine is the actual spot where the fierce anger of Prabhu reached its culmination when he tore Hiranyakasipu.

Ugra Stambham is the pillar from which Narasimha appeared with such force that the entire hill split into two.

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.

*Heads-up that this thread will feature some extreme examples of homophobia and transphobia.*

Hey folks, have you ever wondered why trans people face constant accusations of fetishism, sexual predation and child abuse/grooming? Well, today let's talk about stochastic terrorism.

So, first we have to talk about what stochastic terrorism actually is. Remember when there was a conspiracy that there was a pedophile ring operating out of a pizza parlour basement, and a crazed gunman showed up? It's that sort of incitement that stochastic terrorism describes.

It's the demonisation or incitement against a group of people or individuals with the intent that other, unaffiliated parties will act upon it; it's the releasing doctored footage and a shooter show up at Planned Parenthood as a direct result of what he's been led to believe.

So with that in mind, let's talk about Russia's extreme anti-LGBT laws that banned the "promotion" of LGBT lifestyles to children. A move that specifically marked LGBT people as a threat to children, and resulted in neo-nazis meting out vigilante "justice" against gay men.

Groups such as this would lure unsuspecting gay men via dating sites, and brutalise and humiliate them on camera. They did so under the guise of combating child abusers, one group calling themselves "Occupy

#Guruvayur_Krishna_Bhakthi  🕉
#Guruvayur
#Storytime
Beautiful Story of Guruvayurappan

Poonathanam Namboothiri was a great devotee of Guruvayurappan. One day Poonthanam was going to Guruvayur Kshetram. It was night time and eventhough Namboothiri was tired he continued to walk

Suddenly some thieves came and blocked his way. Poonthanam cried for Shri Krishna to help. Thieves snatched all valuables from him, but Namboothiri holding his Bhaghavatam book called Shri Krishna to help. That time a man came in a horse back and fought with thieves and protected

Namboothiri. Poonthanam thanked Krishna for helping him from danger and said to the man that "Shri Krishna has send you here and I don't know how to thank you".  The man smiled and told that he is Mangattachan, minister of  samoodhiris. Poonthanam once again thanked him and

gave his ring to Mangattachan as a token of thanks and continued his journey. He reached Guruvayur early morning for Nirmalya Darshan. Temple poojari came near him and told that Guruvayurappan came in his dreams and asked to hand over the ring to poonthanam.

When he opened Kshetra Nada poonthanam was surprised to see his ring on Guruvayurappan, which he gifted to Mangattachan. He understood that it was Guruvayurappan who came as Mangattachan to protect him. This is how Bhagwan treat his devotees.

Hare Krishna
🙏🕉🙏