The idea of imperfect competition leading to technological advancement can be mapped onto education/early learning and social determinants of health. /2
A very nice piece by @joshganshttps://t.co/0nUPKGeeMG
— Paul Romer (@paulmromer) October 8, 2018
last tweet: more spending (and, critically, *more revenues as a % of GDP) ...
This makes GBA+ analysis more important than ever because it links outcomes to outlays
More from All
Viruses and other pathogens are often studied as stand-alone entities, despite that, in nature, they mostly live in multispecies associations called biofilms—both externally and within the host.
https://t.co/FBfXhUrH5d
Microorganisms in biofilms are enclosed by an extracellular matrix that confers protection and improves survival. Previous studies have shown that viruses can secondarily colonize preexisting biofilms, and viral biofilms have also been described.
...we raise the perspective that CoVs can persistently infect bats due to their association with biofilm structures. This phenomenon potentially provides an optimal environment for nonpathogenic & well-adapted viruses to interact with the host, as well as for viral recombination.
Biofilms can also enhance virion viability in extracellular environments, such as on fomites and in aquatic sediments, allowing viral persistence and dissemination.
Curated the best tweets from the best traders who are exceptional at managing strangles.
• Positional Strangles
• Intraday Strangles
• Position Sizing
• How to do Adjustments
• Plenty of Examples
• When to avoid
• Exit Criteria
How to sell Strangles in weekly expiry as explained by boss himself. @Mitesh_Engr
• When to sell
• How to do Adjustments
• Exit
1. Let's start option selling learning.
— Mitesh Patel (@Mitesh_Engr) February 10, 2019
Strangle selling. ( I am doing mostly in weekly Bank Nifty)
When to sell? When VIX is below 15
Assume spot is at 27500
Sell 27100 PE & 27900 CE
say premium for both 50-50
If bank nifty will move in narrow range u will get profit from both.
Beautiful explanation on positional option selling by @Mitesh_Engr
Sir on how to sell low premium strangles yourself without paying anyone. This is a free mini course in
Few are selling 20-25 Rs positional option selling course.
— Mitesh Patel (@Mitesh_Engr) November 3, 2019
Nothing big deal in that.
For selling weekly option just identify last week low and high.
Now from that low and high keep 1-1.5% distance from strike.
And sell option on both side.
1/n
1st Live example of managing a strangle by Mitesh Sir. @Mitesh_Engr
• Sold Strangles 20% cap used
• Added 20% cap more when in profit
• Booked profitable leg and rolled up
• Kept rolling up profitable leg
• Booked loss in calls
• Sold only
Sold 29200 put and 30500 call
— Mitesh Patel (@Mitesh_Engr) April 12, 2019
Used 20% capital@44 each
2nd example by @Mitesh_Engr Sir on converting a directional trade into strangles. Option Sellers can use this for consistent profit.
• Identified a reversal and sold puts
• Puts decayed a lot
• When achieved 2% profit through puts then sold
Already giving more than 2% return in a week. Now I will prefer to sell 32500 call at 74 to make it strangle in equal ratio.
— Mitesh Patel (@Mitesh_Engr) February 7, 2020
To all. This is free learning for you. How to play option to make consistent return.
Stay tuned and learn it here free of cost. https://t.co/7J7LC86oW0
Introducing Voltron: Language-Driven Representation Learning for Robotics!
Paper: https://t.co/gIsRPtSjKz
Models: https://t.co/NOB3cpATYG
Evaluation: https://t.co/aOzQu95J8z
🧵👇(1 / 12)
Videos of humans performing everyday tasks (Something-Something-v2, Ego4D) offer a rich and diverse resource for learning representations for robotic manipulation.
Yet, an underused part of these datasets are the rich, natural language annotations accompanying each video. (2/12)
The Voltron framework offers a simple way to use language supervision to shape representation learning, building off of prior work in representations for robotics like MVP (https://t.co/Pb0mk9hb4i) and R3M (https://t.co/o2Fkc3fP0e).
The secret is *balance* (3/12)
Starting with a masked autoencoder over frames from these video clips, make a choice:
1) Condition on language and improve our ability to reconstruct the scene.
2) Generate language given the visual representation and improve our ability to describe what's happening. (4/12)
By trading off *conditioning* and *generation* we show that we can learn 1) better representations than prior methods, and 2) explicitly shape the balance of low and high-level features captured.
Why is the ability to shape this balance important? (5/12)
But don't limit yourself to just ChatGPT.
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