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Thread: *Post-Liberal reading list*
1/ Religion and the Rise of Capitalism - R.H. Tawney
Unto This Last - John Ruskin
Liberty, Equality, Fraternity - James Fitzjames Stephen
The Great Transformation - Karl Polanyi
The Quest for Community - Robert Nisbet

2/ Family and Civilisation - Carle C. Zimmerman
Science, Politics and Gnosticism - Eric Voegelin
Liberty Before Liberalism - Quentin Skinner
The Great Debate - Yuval Levin
Lincoln and the Politics of Christian Love - Grant Havers
Where We Are - Roger Scruton

3/ The Humane Vision of Wendell Berry - Various
The Unsettling of America - Wendell Berry
Moral Matters - Mark Dooley
Red Tory - Phillip Blond
Blue Labour - Eds. Ian Geary and Adrian Pabst
Together for the Common Good - Eds. Nicholas Sagovsky & Peter McGrail

4/ The Politics of Virtue - John Milbank & Adrian Pabst
Localism in a Mass Age - Eds. Mark T. Mitchell & Jason Peters
The Antimodern Condition - Peter King
The Principle of Duty - David Selbourne
Nostalgia - Anthony Esolen
A Common Human Ground - Claes G. Ryn

5/ The Politics of Gratitude - Mark T. Mitchell
A Time to Build - Yuval Levin
Remaking One Nation - Nick Timothy
Despised - Paul Embery
Defending Identity - Natan Sharansky
Between Kin and Cosmopolis - Nigel Biggar
The Virtue of Nationalism - Yoram Hazony

1/ Productivity tip: when I keep procrastinating on something I often trick myself by saying, "ok just work on it for the next 20 minutes" or some short period of time, "and then you can chill/relax guilt free" and give myself some treat (sugar, netflix, etc)

2/ Usually at the 20 minute mark (sometimes I set a timer) I'm so engrossed in what I'm doing that I don't want want to stop and end up working on it for the next hour or two. But getting started seems to be the hardest part.

3/ Key to this: you have to actually be ok with stopping after 20 minutes and being guilt free if that's how you feel. So it's not a trick, i have the option every time, I just often don't want to use it once i'm in the zone.

RANI GAIDINLIU:THE LESSER KNOWN FREEDOM FIGHTER

Rani Gaidinliu joined the freedom struggle at 13 &was sentenced to life imprisonment at 16."We r free people—the White should not rule over us.”Thus calling out to her Zeliangrong tribesmen was the voice of 13yr-old Rani Gaidinliu.

She joined the freedom struggle in the present-day Northeast India. Today, her struggle is lost in history as most of her countrymen wouldn’t even have heard her name. B'coz our history textbooks tell us that only Mahatma Gandhi &Pandit Nehru got India its Independence.

At 16 yrs of age, this valiant girl was sentenced to life imprisonment for leading a movement to drive out the colonial rulers from Manipur and Nagaland. Nevertheless, she was released in 1947 after India’s independence and was given the title ,"Rani of Nagas".

EARLY LIFE AND HERAKA MOVEMENT

Gaidinliu belonged to the Rongmei clan of the Zeliangrong tribe in the Tamenglong district of western Manipur. Born on January 26, 1915, she was fifth among eight children.

Her native village was Nungkao, which is present day Tamenglong distt. Brought up in a specially backward region,she couldn't receive any formal education. However,this didn't stop her from joining the freedom struggle. At the age of 10 she came under the influence of her cousin.

1 There's a chasm between an NLP technology that works well in the research lab and something that works for applications that real people use. This was eye-opening when I started my career, and every time I talk to an NLP engineer at @textio, it continues to strike me even now.

2 Research conditions are theoretical and/or idealized. A huge problem for so-called NLP or AI startups with highly credentialed academic founders is that they bring limited knowledge of what it takes to build real products outside the lab.

3 A product is ultimately a thing that people pay for - not just cool technology or user experience. But I’m not even talking about knowledge gaps in go-to-market work. I'm talking purely technical gaps: how you go from science project to performant + delightful user experience.

4 Most commoditized NLP packages solve well-understood problems in standard ways that sacrifice either precision or performance. In a research lab, this is not usually a hard trade-off; in general, no one is using what you make, so performance is less important than precision.

5 In software, when you’re making something for real people to use, these tradeoffs are a big deal. Especially if you’re asking those people to pay for what you’ve made (can’t get away from that pesky GTM thinking). They expect quality, which includes precision AND performance.