@cjkink @buzz_chronicles Thank you sir and I hope you can somehow save it as I know when it gets too much exposure...twitter will throttle the thread or suspend me (this is my 5th acct).

1/ I am seeing more and more founder secondary in venture rounds (Secondary = founders selling some of their shares before some other shareholders are able). Series B-D. I see both as an investor and through entrepreneur circles.

2/ I like secondary for entrepreneurs. Moderation is key but in a lot of situations I think it helps accelerate the co. Lots of very smart investors disagree. Here are my thoughts.

3/ Magnitude: My basic rule of thumb from what I see is market is 4+ yrs and up to 10% of founder’s equity stake with some $ cap that makes sense given stage etc. (typically <$10m)

4/ The entrepreneurial journey is brutally hard. Giving some financial relief helps remove one piece of pressure. I don’t think that secondary in the magnitude mentioned impacts the drive/persistence of great entrepreneurs.

5/ That secondary means they will be able to just sleep knowing they can pay their kids’ tuition. Secondary will make most founders better at their jobs, thus accelerating the co.

Due to the pandemic you may not have visited your local library in a while. So come with me on a virtual library tour, courtesy of stock photography, to see what we do for a living...

Libraries are of course information resource centres, but in many ways they are so much more. To get the best out of them you need to really know your way around the stacks.

The enquiries desk is normally your first stop in a library, and this is where you will meet The Angry Librarian! Why is she angry? Because you keep asking her stupid questions!

"Are you open?"
"Do you have a toilet?"
"That chair's wobbly!"
"Why isn't it available in audiobook?"
"Someone else is on the computer and that's not fair!"

On and on it goes...

And that's why in the library we insist on silence. It's the only way to stop us swearing at all the idiotic things you ask us. And we've looked up a lot of old swear words: beardsplitter, bescumber, rantallion, smellfungus etc. We're such muckspouts...

हिमालय पर्वत की एक बड़ी पवित्र गुफा थी।उस गुफा के निकट ही गंगा जी बहती थी।एक बार देवर्षि नारद विचरण करते हुए वहां आ पहुंचे।वह परम पवित्र गुफा नारद जी को अत्यंत सुहावनी लगी।वहां का मनोरम प्राकृतिक दृश्य,पर्वत,नदी और वन देख उनके हृदय में श्रीहरि विष्णु की भक्ति अत्यंत बलवती हो उठी।

और देवर्षि नारद वहीं बैठकर तपस्या में लीन हो गए।इन्द्र नारद की तपस्या से घबरा गए।उन्हें हमेशा की तरह अपना सिंहासन व स्वर्ग खोने का डर सताने लगा।इसलिए इन्द्र ने नारद की तपस्या भंग करने के लिए कामदेव को उनके पास भेज दिया।वहां पहुंच कामदेव ने अपनी माया से वसंतऋतु को उत्पन्न कर दिया।

पेड़ और पौधों पर रंग बिरंगे फूल खिल गए और कोयलें कूकने लगी,पक्षी चहकने लगे।शीतल,मंद,सुगंधित और सुहावनी हवा चलने लगी।रंभा आदि अप्सराएं नाचने लगीं ।किन्तु कामदेव की किसी भी माया का नारद पे कोई प्रभाव नहीं पड़ा।तब कामदेव को डर सताने लगा कि कहीं नारद क्रोध में आकर मुझे श्राप न देदें।

जैसे ही नारद ने अपनी आंखें खोली, उसी क्षण कामदेव ने उनसे क्षमा मांगी।नारद मुनि को तनिक भी क्रोध नहीं आया और उन्होने शीघ्र ही कामदेव को क्षमा कर दिया।कामदेव प्रसन्न होकर वहां से चले गए।कामदेव के चले जाने पर देवर्षि के मन में अहंकार आ गया कि मैने कामदेव को हरा दिया।

नारद फिर कैलाश जा पहुंचे और शिवजी को अपनी विजयगाथा सुनाई।शिव समझ गए कि नारद अहंकारी हो गए हैं और अगर ये बात विष्णु जी जान गए तो नारद के लिए अच्छा नहीं होगा।ये सोचकर शिवजी ने नारद को भगवन विष्णु को ये बात बताने के लीए मना किया। परंतु नारद जी को ये बात उचित नहीं लगी।

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.

This day was inevitable. Indian Muslims always lived in La La Land. They bad mouthed real well wishers & slept with the enemy who never considered them as part of them. In Gulf, Indian Muslims were busy with Javed Akhtar & Sonu Nigam. Never interacted with South Asian diaspora

Now when Indian Muslims are thrown to wolves it’s Pakistani & Bangladeshi Muslims with whom they kept distance are the only ones feeling their pain. None of the people who they invited for Eid Milan. Qawali & Mushaira are there for them. Such people invoke wrath upon themselves

Indian Muslims never spoke for Kashmiri Muslims. Distancing from separatist was understandable but we never even bothered to highlight their human rights violation & rapes carried out by forces. We could have sent them humanitarian help we didn’t. Our silence made us complicit.

When Sania Mirza married Shoaib Malik it was something legal. A Muslim married another Muslim. Entire Hindutva media went after her. They launched a witch-hunt for months. No Indian Muslim stood by her. All were silent. Now days come when Muslims are arrested for marrying a Hindu

Indian Muslims particularly the elite downplayed communalism in India by saying it will pass or Hindu majority is good. Fringe are bad. They misguiding others. Muslims were always others. Indians were happy to see Muslims sing & dance & eat their food but never considered as own