I was asked yesterday on a coaching call how I’m always positive :)

This has been an intentional choice & something I’ve worked hard at for years now!

🙏You can’t be grateful & grumpy at the same time!!

🔥I curate my entire life around positivity.

Strategies I use: 🧵
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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।

Rhino Barges

One of the dullest, coolest, more bizarre and fascinating pieces of kit used in Normandy.

Which NO ONE REALLY CARES ABOUT.

BUT I DO AND YOU SHOULD TOO.
/1

#WW2 #SWW #History

Planning for Overlord and Neptune had a serious snag, how to get troops from LSTs onto the beach as simply ramming them onto the beaches and dropping the ramp was known to damage the exceptionally vulnerable LSTs and felt to be unsustainable in the mid to long term. /2

LSTs were essential in sustaining Overlord's progress and were a subject of major headaches in the planning phase, and a real subject of friction when it came to launching additional amphibious operations such as Dragoon.

A single LSTs loss represented a capability nick. /3

So, logic dictated, we don't really want these remarkable but rare and highly valuable vessels constantly doing beach landings, we want something to act as a medium between ship to shore, and in came the (mostly) American designed Rhino. /4

I fucking love Rhinos.

Seriously.

Graceful lines of pure industrial pedigree.

Modular.

LOOK AT IT. /5

❤✈️🌎 2 years ago today @JamesIvings and I sold all our belongings and left the UK to travel for a year. We've never been happier and we have no plans to ever return there 🙂

Thread 👇

Since then we've started a remote web dev company @SquarecatWebDev and been lucky enough to have completed several freelance projects 💻 that have kept us on the road.

In the last few months we've become a huge part of this amazing new Maker community and have found so many new friends from @makerskitchen, @women_make_ and several others! 🥰

We love travelling together (even if I'm only a glorified laptop watcher 😒) but we're both much happier being able to share our ideas outside of our own little bubble and our products have benefitted too!

Here's to another year of nomading with my favourite person and to the Maker community continuing to grow with our help! Maybe one day we'll all get to meet each other ✌️ 💛

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.