LTTS - A stock that had fallen 26% from Recent High. consolidated around the 200 DMA. Now attempting to rally , making HH and HL. Looks set to seek 5700+ levels. Committed buyers also coming in. By Conventional TA there is a Gap to be filled as well.

November is here, and that means a massive shift is coming. And by "massive" I am of course referring to the redefinition of the kilogram unit of mass that the world has been building up to for more than 100 years. Let me explain:

1/ I've had an unhealthy fascination with metrology (the study of measurement) ever since my 2nd year as a physics major when I took a class devoted to duplicating historic physics experiments, so please indulge me for going into heavy detail (get it?) about the kilogram.

2/ So what actually *defines* a unit of measurement? If you're American, you probably know a mile is 5280 feet and a foot is 12 inches and an inch is 2.54 centimeters etc. But where does this chain of definitions end? Is it turtles all the way down?

3/ It's actually not! For all units (even the imperial units used in America) the answers all end with the Système International (SI) unit definitions established and maintained for over 100 years by the Bureau International des Poids et Mesures (BIMP) in France.

4/ At the base of this tower are the SI base units. Just 7 SI base units define every other unit in existence. They are:

Kilogram, kg (mass)
Meter, m (distance)
Second, s (time)
Kelvin, K (temp)
Ampere, A (electric current)
Candela, cd (luminous intensity)
Mole, mol (quantity)

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.

Rig Ved 1.36.7

To do a Namaskaar or bow before someone means that you are humble or without pride and ego. This means that we politely bow before you since you are better than me. Pranipaat(प्राणीपात) also means the same that we respect you without any vanity.

1/9

Surrendering False pride is Namaskaar. Even in devotion or bhakti we say the same thing. We want to convey to Ishwar that we have nothing to offer but we leave all our pride and offer you ourselves without any pride in our body. You destroy all our evil karma.

2/9

We bow before you so that you assimilate us and make us that capable. Destruction of our evils and surrender is Namaskaar. Therefore we pray same thing before and after any big rituals.

3/9

तं घे॑मि॒त्था न॑म॒स्विन॒ उप॑ स्व॒राज॑मासते ।
होत्रा॑भिर॒ग्निं मनु॑षः॒ समिं॑धते तिति॒र्वांसो॒ अति॒ स्रिधः॑॥

Translation :

नमस्विनः - To bow.

स्वराजम् - Self illuminating.

तम् - His.

घ ईम् - Yours.

इत्था - This way.

उप - Upaasana.

आसते - To do.

स्त्रिधः - For enemies.

4/9

अति तितिर्वांसः - To defeat fast.

मनुषः - Yajman.

होत्राभिः - In seven numbers.

अग्निम् - Agnidev.

समिन्धते - Illuminated on all sides.

Explanation : Yajmans bow(do Namaskaar) before self illuminating Agnidev by making the offerings of Havi.

5/9

Gather round, Gentle Readers. It is time I tell the story of the worst decision I ever made in an office. Some of you have heard this. Some have not. Whatever you do in your office today, this week, the rest of this year, you can console yourself by recalling this tale.

A long time ago, I was a talent agent. I worked for a woman named Susan Smith, who had her own small boutique agency. She was known for three things:

1. She had fantastic taste in clients. If there is someone you admire, odds are good that at some point, she was their agent,

2. She could negotiate a deal like few who have ever trod the earth. Casting would give her all the money they had budgeted for that part, plus a little more, plus promising to get her dog Barnaby groomed. She was magnificent to watch.

3. She was insane.

I'm sure you're thinking, "Quinn, it's the entertainment industry, they are all insane." Yes, many are. So consider this; if you told someone you worked for Susan, people who worked for insane people would look and you and whisper, "I hear she's insane."