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Ryan Weeks

Ryan Weeks

3 years ago

Terra fiasco raises TRON's stablecoin backstop

After Terra's algorithmic stablecoin collapsed in May, TRON announced a plan to increase the capital backing its own stablecoin.

USDD, a near-carbon copy of Terra's UST, arrived on the TRON blockchain on May 5. TRON founder Justin Sun says USDD will be overcollateralized after initially being pegged algorithmically to the US dollar.

A reserve of cryptocurrencies and stablecoins will be kept at 130 percent of total USDD issuance, he said. TRON described the collateral ratio as "guaranteed" and said it would begin publishing real-time updates on June 5.

Currently, the reserve contains 14,040 bitcoin (around $418 million), 140 million USDT, 1.9 billion TRX, and 8.29 billion TRX in a burning contract.

Sun: "We want to hybridize USDD." We have an algorithmic stablecoin and TRON DAO Reserve.

algorithmic failure

USDD was designed to incentivize arbitrageurs to keep its price pegged to the US dollar by trading TRX, TRON's token, and USDD. Like Terra, TRON signaled its intent to establish a bitcoin and cryptocurrency reserve to support USDD in extreme market conditions.

Still, Terra's UST failed despite these safeguards. The stablecoin veered sharply away from its dollar peg in mid-May, bringing down Terra's LUNA and wiping out $40 billion in value in days. In a frantic attempt to restore the peg, billions of dollars in bitcoin were sold and unprecedented volumes of LUNA were issued.

Sun believes USDD, which has a total circulating supply of $667 million, can be backed up.

"Our reserve backing is diversified." Bitcoin and stablecoins are included. USDC will be a small part of Circle's reserve, he said.

TRON's news release lists the reserve's assets as bitcoin, TRX, USDC, USDT, TUSD, and USDJ.

All Bitcoin addresses will be signed so everyone knows they belong to us, Sun said.

Not giving in

Sun told that the crypto industry needs "decentralized" stablecoins that regulators can't touch.

Sun said the Luna Foundation Guard, a Singapore-based non-profit that raised billions in cryptocurrency to buttress UST, mismanaged the situation by trying to sell to panicked investors.

He said, "We must be ahead of the market." We want to stabilize the market and reduce volatility.

Currently, TRON finances most of its reserve directly, but Sun says the company hopes to add external capital soon.

Before its demise, UST holders could park the stablecoin in Terra's lending platform Anchor Protocol to earn 20% interest, which many deemed unsustainable. TRON's JustLend is similar. Sun hopes to raise annual interest rates from 17.67% to "around 30%."


This post is a summary. Read full article here

More on Web3 & Crypto

Isaac Benson

Isaac Benson

3 years ago

What's the difference between Proof-of-Time and Proof-of-History?

Blockchain validates transactions with consensus algorithms. Bitcoin and Ethereum use Proof-of-Work, while Polkadot and Cardano use Proof-of-Stake.

Other consensus protocols are used to verify transactions besides these two. This post focuses on Proof-of-Time (PoT), used by Analog, and Proof-of-History (PoH), used by Solana as a hybrid consensus protocol.

PoT and PoH may seem similar to users, but they are actually very different protocols.

Proof-of-Time (PoT)

Analog developed Proof-of-Time (PoT) based on Delegated Proof-of-Stake (DPoS). Users select "delegates" to validate the next block in DPoS. PoT uses a ranking system, and validators stake an equal amount of tokens. Validators also "self-select" themselves via a verifiable random function."

The ranking system gives network validators a performance score, with trustworthy validators with a long history getting higher scores. System also considers validator's fixed stake. PoT's ledger is called "Timechain."

Voting on delegates borrows from DPoS, but there are changes. PoT's first voting stage has validators (or "time electors" putting forward a block to be included in the ledger).

Validators are chosen randomly based on their ranking score and fixed stake. One validator is chosen at a time using a Verifiable Delay Function (VDF).

Validators use a verifiable delay function to determine if they'll propose a Timechain block. If chosen, they validate the transaction and generate a VDF proof before submitting both to other Timechain nodes.

This leads to the second process, where the transaction is passed through 1,000 validators selected using the same method. Each validator checks the transaction to ensure it's valid.

If the transaction passes, validators accept the block, and if over 2/3 accept it, it's added to the Timechain.

Proof-of-History (PoH)

Proof-of-History is a consensus algorithm that proves when a transaction occurred. PoH uses a VDF to verify transactions, like Proof-of-Time. Similar to Proof-of-Work, VDFs use a lot of computing power to calculate but little to verify transactions, similar to (PoW).

This shows users and validators how long a transaction took to verify.

PoH uses VDFs to verify event intervals. This process uses cryptography to prevent determining output from input.

The outputs of one transaction are used as inputs for the next. Timestamps record the inputs' order. This checks if data was created before an event.

PoT vs. PoH

PoT and PoH differ in that:

  • PoT uses VDFs to select validators (or time electors), while PoH measures time between events.

  • PoH uses a VDF to validate transactions, while PoT uses a ranking system.

  • PoT's VDF-elected validators verify transactions proposed by a previous validator. PoH uses a VDF to validate transactions and data.

Conclusion

Both Proof-of-Time (PoT) and Proof-of-History (PoH) validate blockchain transactions differently. PoT uses a ranking system to randomly select validators to verify transactions.

PoH uses a Verifiable Delay Function to validate transactions, verify how much time has passed between two events, and allow validators to quickly verify a transaction without malicious actors knowing the input.

CyberPunkMetalHead

CyberPunkMetalHead

2 years ago

I talked to ChatGPT about the adoption of cryptocurrencies.

OpenAI's ChatGPT is an amazing AI-powered chatbot. It can write poetry, fiction, and marketing ideas. I was impressed how well ChatGPT followed the interview, albeit there were a few classics “I’m afraid I can’t do that”.

Full interview below.

Me: I'm your interviewer. We'll discuss crypto. Thanks for being interviewed. What do you think about cryptocurrency?

CGPT: Cryptocurrency is an innovative technology that could transform money and financial activities. It might boost the efficiency and security of financial institutions and let consumers deal directly without banks. Cryptocurrency is still a new and untested technology with many unknowns and hurdles before it can be broadly accepted.

Me: Over 22,000 cryptocurrencies exist, and many have little use. We need how much cryptocurrencies?

CGPT: The appropriate quantity will rely on a multitude of factors, including each cryptocurrency's use cases, adoption rate, and market rivalry. Only a few cryptocurrencies will likely receive widespread adoption and be successful. Many existing cryptocurrencies may not survive since they can't deliver new or valued solutions or compete with more established cryptocurrencies.

Me: Will cryptocurrencies grow? What's next for worldwide adoption?

CGPT: It's hard to forecast the future of cryptocurrencies because the acceptance of new technologies is unpredictable. I believe cryptocurrencies will expand and acquire popularity in the future years. Regulatory ambiguity, security concerns, and scalability issues must be overcome for this to happen. Cryptocurrency companies and organizations must engage together with governments and authorities to address these obstacles and establish a growth-friendly climate. Continued innovation and improvement of the technology, including public education and awareness, will drive acceptance.

Me: Do bear markets affect bitcoin adoption?

CGPT: On the one hand, a bear market might induce uncertainty and hesitation among potential consumers. Bear markets can present opportunities for long-term investors who can acquire cryptocurrencies at cheaper prices and are more likely to hang onto their assets. A bear market can also test the tenacity and power of the underlying technology and community, which can boost long-term confidence and adoption. A bear market might have profound and nuanced effects on bitcoin adoption.

Me: What are some likely outcomes if Bitcoin reaches $100,000 by next year?

CGPT: If Bitcoin saw rapid growth, it would undoubtedly have repercussions for the cryptocurrency market and economy. Possible scenarios include increased public interest and awareness of cryptocurrency, a surge in demand for Bitcoin and other cryptocurrencies, and a growth in the cryptocurrency industry's market value. By shifting their focus and cash to the cryptocurrency market, investors and traders may also affect other asset classes, such as traditional equities and commodities. Governments and financial organizations may focus more on the cryptocurrency sector as they try to grasp Bitcoin's rapid rise.

Me: Will other countries accept crypto as currency?

CGPT: It's hard to say if additional governments will adopt cryptocurrencies as legal tender. Some countries have recognized the promise of bitcoin and are exploring its use, while others are cautious. Adoption of bitcoin as legal cash may vary by country, based on financial infrastructure, rules, and political atmosphere. As cryptocurrency technology evolves and becomes more accepted, more governments may embrace it as legal tender.

Me: Final question: will the recent cryptocurrency hacks affect long term adoption?

CGPT: Hacks might tarnish cryptocurrency's reputation and public faith in its security, the technology underpinning it is continually improving. Many cryptocurrency projects have developed strong security mechanisms to prevent hacks and other dangers, and these safeguards will undoubtedly improve over time. The decentralized nature of cryptocurrency makes it more resistant to attacks. Hacks and other security breaches are a concern, but they may not affect cryptocurrency adoption.

CyberPunkMetalHead

CyberPunkMetalHead

3 years ago

It's all about the ego with Terra 2.0.

UST depegs and LUNA crashes 99.999% in a fraction of the time it takes the Moon to orbit the Earth.

Fat Man, a Terra whistle-blower, promises to expose Do Kwon's dirty secrets and shady deals.

The Terra community has voted to relaunch Terra LUNA on a new blockchain. The Terra 2.0 Pheonix-1 blockchain went live on May 28, 2022, and people were airdropped the new LUNA, now called LUNA, while the old LUNA became LUNA Classic.

Does LUNA deserve another chance? To answer this, or at least start a conversation about the Terra 2.0 chain's advantages and limitations, we must assess its fundamentals, ideology, and long-term vision.

Whatever the result, our analysis must be thorough and ruthless. A failure of this magnitude cannot happen again, so we must magnify every potential breaking point by 10.

Will UST and LUNA holders be compensated in full?

The obvious. First, and arguably most important, is to restore previous UST and LUNA holders' bags.

Terra 2.0 has 1,000,000,000,000 tokens to distribute.

  • 25% of a community pool

  • Holders of pre-attack LUNA: 35%

  • 10% of aUST holders prior to attack

  • Holders of LUNA after an attack: 10%

  • UST holders as of the attack: 20%

Every LUNA and UST holder has been compensated according to the above proposal.

According to self-reported data, the new chain has 210.000.000 tokens and a $1.3bn marketcap. LUNC and UST alone lost $40bn. The new token must fill this gap. Since launch:

LUNA holders collectively own $1b worth of LUNA if we subtract the 25% community pool airdrop from the current market cap and assume airdropped LUNA was never sold.

At the current supply, the chain must grow 40 times to compensate holders. At the current supply, LUNA must reach $240.

LUNA needs a full-on Bull Market to make LUNC and UST holders whole.

Who knows if you'll be whole? From the time you bought to the amount and price, there are too many variables to determine if Terra can cover individual losses.

The above distribution doesn't consider individual cases. Terra didn't solve individual cases. It would have been huge.

What does LUNA offer in terms of value?

UST's marketcap peaked at $18bn, while LUNC's was $41bn. LUNC and UST drove the Terra chain's value.

After it was confirmed (again) that algorithmic stablecoins are bad, Terra 2.0 will no longer support them.

Algorithmic stablecoins contributed greatly to Terra's growth and value proposition. Terra 2.0 has no product without algorithmic stablecoins.

Terra 2.0 has an identity crisis because it has no actual product. It's like Volkswagen faking carbon emission results and then stopping car production.

A project that has already lost the trust of its users and nearly all of its value cannot survive without a clear and in-demand use case.

Do Kwon, how about him?

Oh, the Twitter-caller-poor? Who challenges crypto billionaires to break his LUNA chain? Who dissolved Terra Labs South Korea before depeg? Arrogant guy?

That's not a good image for LUNA, especially when making amends. I think he should step down and let a nicer person be Terra 2.0's frontman.

The verdict

Terra has a terrific community with an arrogant, unlikeable leader. The new LUNA chain must grow 40 times before it can start making up its losses, and even then, not everyone's losses will be covered.

I won't invest in Terra 2.0 or other algorithmic stablecoins in the near future. I won't be near any Do Kwon-related project within 100 miles. My opinion.

Can Terra 2.0 be saved? Comment below.

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Edward Williams

Edward Williams

3 years ago

I currently manage 4 profitable online companies. I find all the generic advice and garbage courses very frustrating. The only advice you need is this.

A man playing chess.

This is for young entrepreneurs, especially in tech.

People give useless success advice on TikTok and Reddit. Early risers, bookworms, etc. Entrepreneurship courses. Work hard and hustle.

False. These aren't successful traits.

I mean, organization is good. As someone who founded several businesses and now works at a VC firm, I find these tips to be clichés.

Based on founding four successful businesses and working with other successful firms, here's my best actionable advice:

1. Choose a sector or a niche and become an expert in it.

This is more generic than my next tip, but it's a must-do that's often overlooked. Become an expert in the industry or niche you want to enter. Discover everything.

Buy (future) competitors' products. Understand consumers' pain points. Market-test. Target keyword combos. Learn technical details.

The most successful businesses I've worked with were all formed by 9-5 employees. They knew the industry's pain points. They started a business targeting these pain points.

2. Choose a niche or industry crossroads to target.

How do you choose an industry or niche? What if your industry is too competitive?

List your skills and hobbies. Randomness is fine. Find an intersection between two interests or skills.

Say you build websites well. You like cars.

Web design is a *very* competitive industry. Cars and web design?

Instead of web design, target car dealers and mechanics. Build a few fake demo auto mechanic websites, then cold call shops with poor websites. Verticalize.

I've noticed a pattern:

  • Person works in a particular industry for a corporation.

  • Person gains expertise in the relevant industry.

  • Person quits their job and launches a small business to address a problem that their former employer was unwilling to address.

I originally posted this on Reddit and it seemed to have taken off so I decided to share it with you all.

Focus on the product. When someone buys from you, you convince them the product's value exceeds the price. It's not fair and favors the buyer.

Creating a superior product or service will win. Narrowing this helps you outcompete others.

You may be their only (lucky) option.

Leonardo Castorina

Leonardo Castorina

3 years ago

How to Use Obsidian to Boost Research Productivity

Tools for managing your PhD projects, reading lists, notes, and inspiration.

As a researcher, you have to know everything. But knowledge is useless if it cannot be accessed quickly. An easy-to-use method of archiving information makes taking notes effortless and enjoyable.
As a PhD student in Artificial Intelligence, I use Obsidian (https://obsidian.md) to manage my knowledge.

The article has three parts:

  1. What is a note, how to organize notes, tags, folders, and links? This section is tool-agnostic, so you can use most of these ideas with any note-taking app.
  2. Instructions for using Obsidian, managing notes, reading lists, and useful plugins. This section demonstrates how I use Obsidian, my preferred knowledge management tool.
  3. Workflows: How to use Zotero to take notes from papers, manage multiple projects' notes, create MOCs with Dataview, and more. This section explains how to use Obsidian to solve common scientific problems and manage/maintain your knowledge effectively.

This list is not perfect or complete, but it is my current solution to problems I've encountered during my PhD. Please leave additional comments or contact me if you have any feedback. I'll try to update this article.
Throughout the article, I'll refer to your digital library as your "Obsidian Vault" or "Zettelkasten".
Other useful resources are listed at the end of the article.

1. Philosophy: Taking and organizing notes

Carl Sagan: “To make an apple pie from scratch, you must first create the universe.”

Before diving into Obsidian, let's establish a Personal Knowledge Management System and a Zettelkasten. You can skip to Section 2 if you already know these terms.
Niklas Luhmann, a prolific sociologist who wrote 400 papers and 70 books, inspired this section and much of Zettelkasten. Zettelkasten means “slip box” (or library in this article). His Zettlekasten had around 90000 physical notes, which can be found here.
There are now many tools available to help with this process. Obsidian's website has a good introduction section: https://publish.obsidian.md/hub/

Notes

We'll start with "What is a note?" Although it may seem trivial, the answer depends on the topic or your note-taking style. The idea is that a note is as “atomic” (i.e. You should read the note and get the idea right away.
The resolution of your notes depends on their detail. Deep Learning, for example, could be a general description of Neural Networks, with a few notes on the various architectures (eg. Recurrent Neural Networks, Convolutional Neural Networks etc..).
Limiting length and detail is a good rule of thumb. If you need more detail in a specific section of this note, break it up into smaller notes. Deep Learning now has three notes:

  • Deep Learning
  • Recurrent Neural Networks
    - Convolutional Neural Networks

Repeat this step as needed until you achieve the desired granularity. You might want to put these notes in a “Neural Networks” folder because they are all about the same thing. But there's a better way:

#Tags and [[Links]] over /Folders/

The main issue with folders is that they are not flexible and assume that all notes in the folder belong to a single category. This makes it difficult to make connections between topics.
Deep Learning has been used to predict protein structure (AlphaFold) and classify images (ImageNet). Imagine a folder structure like this:

- /Proteins/ 
     - Protein Folding
- /Deep Learning/
     - /Proteins/ 

Your notes about Protein Folding and Convolutional Neural Networks will be separate, and you won't be able to find them in the same folder.
This can be solved in several ways. The most common one is to use tags rather than folders. A note can be grouped with multiple topics this way. Obsidian tags can also be nested (have subtags).

You can also link two notes together. You can build your “Knowledge Graph” in Obsidian and other note-taking apps like Obsidian.


My Knowledge Graph. Green: Biology, Red: Machine Learning, Yellow: Autoencoders, Blue: Graphs, Brown: Tags.


My Knowledge Graph and the note “Backrpropagation” and its links.


Backpropagation note and all its links

Why use Folders?

Folders help organize your vault as it grows. The main suggestion is to have few folders that "weakly" collect groups of notes or better yet, notes from different sources.
Among my Zettelkasten folders are:


My Zettelkasten's 5 folders

They usually gather data from various sources:

MOC: Map of Contents for the Zettelkasten.
Projects: Contains one note for each side-project of my PhD where I log my progress and ideas. Notes are linked to these.
Bio and ML: These two are the main content of my Zettelkasten and could theoretically be combined.
Papers: All my scientific paper notes go here. A bibliography links the notes. Zotero .bib file
Books: I make a note for each book I read, which I then split into multiple notes.

Keeping images separate from other files can help keep your main folders clean.

I will elaborate on these in the Workflow Section.

My general recommendation is to use tags and links instead of folders.

Maps of Content (MOC) 

Making Tables of Contents is a good solution (MOCs).
These are notes that "signposts" your Zettelkasten library, directing you to the right type of notes. It can link to other notes based on common tags. This is usually done with a title, then your notes related to that title. As an example:

An example of a Machine Learning MOC generated with Dataview.

As shown above, my Machine Learning MOC begins with the basics. Then it's on to Variational Auto-Encoders. Not only does this save time, but it also saves scrolling through the tag search section.
So I keep MOCs at the top of my library so I can quickly find information and see my library. These MOCs are generated automatically using an Obsidian Plugin called Dataview (https://github.com/blacksmithgu/obsidian-dataview).
Ideally, MOCs could be expanded to include more information about the notes, their status, and what's left to do. In the absence of this, Dataview does a fantastic job at creating a good structure for your notes.
In the absence of this, Dataview does a fantastic job at creating a good structure for your notes.

2. Tools: Knowing Obsidian

Obsidian is my preferred tool because it is free, all notes are stored in Markdown format, and each panel can be dragged and dropped. You can get it here: https://obsidian.md/

Obsidian interface. 

Obsidian is highly customizable, so here is my preferred interface:


The theme is customized from https://github.com/colineckert/obsidian-things

Alternatively, each panel can be collapsed, moved, or removed as desired. To open a panel later, click on the vertical "..." (bottom left of the note panel).

My interface is organized as follows:

How my Obsidian Interface is organized.

Folders/Search:
This is where I keep all relevant folders. I usually use the MOC note to navigate, but sometimes I use the search button to find a note.

Tags:
I use nested tags and look into each one to find specific notes to link.

cMenu:
Easy-to-use menu plugin cMenu (https://github.com/chetachiezikeuzor/cMenu-Plugin)

Global Graph:
The global graph shows all your notes (linked and unlinked). Linked notes will appear closer together. Zoom in to read each note's title. It's a bit overwhelming at first, but as your library grows, you get used to the positions and start thinking of new connections between notes.

Local Graph:
Your current note will be shown in relation to other linked notes in your library. When needed, you can quickly jump to another link and back to the current note.

Links:
Finally, an outline panel and the plugin Obsidian Power Search (https://github.com/aviral-batra/obsidian-power-search) allow me to search my vault by highlighting text.

Start using the tool and worry about panel positioning later. I encourage you to find the best use-case for your library.

Plugins

An additional benefit of using Obsidian is the large plugin library. I use several (Calendar, Citations, Dataview, Templater, Admonition):
Obsidian Calendar Plugin: https://github.com/liamcain
It organizes your notes on a calendar. This is ideal for meeting notes or keeping a journal.

Calendar addon from hans/obsidian-citation-plugin
Obsidian Citation Plugin: https://github.com/hans/
Allows you to cite papers from a.bib file. You can also customize your notes (eg. Title, Authors, Abstract etc..)

Plugin citation from hans/obsidian-citation-plugin
Obsidian Dataview: https://github.com/blacksmithgu/
A powerful plugin that allows you to query your library as a database and generate content automatically. See the MOC section for an example.
Allows you to create notes with specific templates like dates, tags, and headings.

Templater. Obsidian Admonition: https://github.com/valentine195/obsidian-admonition
Blocks allow you to organize your notes.

Plugin warning. Obsidian Admonition (valentine195)
There are many more, but this list should get you started.

3. Workflows: Cool stuff

Here are a few of my workflows for using obsidian for scientific research. This is a list of resources I've found useful for my use-cases. I'll outline and describe them briefly so you can skim them quickly.
3.1 Using Templates to Structure Notes
3.2 Free Note Syncing (Laptop, Phone, Tablet)
3.3 Zotero/Mendeley/JabRef -> Obsidian — Managing Reading Lists
3.4 Projects and Lab Books
3.5 Private Encrypted Diary

3.1 Using Templates to Structure Notes

Plugins: Templater and Dataview (optional).
To take effective notes, you must first make adding new notes as easy as possible. Templates can save you time and give your notes a consistent structure. As an example:


An example of a note using a template.

### [[YOUR MOC]]
# Note Title of your note
**Tags**:: 
**Links**::

The top line links to your knowledge base's Map of Content (MOC) (see previous sections). After the title, I add tags (and a link between the note and the tag) and links to related notes.
To quickly identify all notes that need to be expanded, I add the tag “#todo”. In the “TODO:” section, I list the tasks within the note.
The rest are notes on the topic.
Templater can help you create these templates. For new books, I use the following template:

### [[Books MOC]]
# Title
**Author**:: 
**Date::
**Tags:: 
**Links::


A book template example.

Using a simple query, I can hook Dataview to it.

dataview  
table author as Author, date as “Date Finished”, tags as “Tags”, grade as “Grade”  
from “4. Books”  
SORT grade DESCENDING


using Dataview to query templates.

3.2 Free Note Syncing (Laptop, Phone, Tablet)

No plugins used.

One of my favorite features of Obsidian is the library's self-contained and portable format. Your folder contains everything (plugins included).

Ordinary folders and documents are available as well. There is also a “.obsidian” folder. This contains all your plugins and settings, so you can use it on other devices.
So you can use Google Drive, iCloud, or Dropbox for free as long as you sync your folder (note: your folder should be in your Cloud Folder).

For my iOS and macOS work, I prefer iCloud. You can also use the paid service Obsidian Sync.
3.3 Obsidian — Managing Reading Lists and Notes in Zotero/Mendeley/JabRef
Plugins: Quotes (required).

3.3 Zotero/Mendeley/JabRef -> Obsidian — Taking Notes and Managing Reading Lists of Scientific Papers

My preferred reference manager is Zotero, but this workflow should work with any reference manager that produces a .bib file. This file is exported to my cloud folder so I can access it from any platform.

My Zotero library is tagged as follows:

My reference manager's tags

For readings, I usually search for the tags “!!!” and “To-Read” and select a paper. Annotate the paper next (either on PDF using GoodNotes or on physical paper).
Then I make a paper page using a template in the Citations plugin settings:


An example of my citations template.

Create a new note, open the command list with CMD/CTRL + P, and find the Citations “Insert literature note content in the current pane” to see this lovely view.


Citation generated by the article https://doi.org/10.1101/2022.01.24.22269144

You can then convert your notes to digital. I found that transcribing helped me retain information better.

3.4 Projects and Lab Books

Plugins: Tweaker (required).
PhD students offering advice on thesis writing are common (read as regret). I started asking them what they would have done differently or earlier.

“Deep stuff Leo,” one person said. So my main issue is basic organization, losing track of my tasks and the reasons for them.
As a result, I'd go on other experiments that didn't make sense, and have to reverse engineer my logic for thesis writing. - PhD student now wise Postdoc

Time management requires planning. Keeping track of multiple projects and lab books is difficult during a PhD. How I deal with it:

  • One folder for all my projects
  • One file for each project
    I use a template to create each project
### [[Projects MOC]]  
# <% tp.file.title %>  
**Tags**::  
**Links**::  
**URL**::  
**Project Description**::## Notes:  
### <% tp.file.last_modified_date(“dddd Do MMMM YYYY”) %>  
#### Done:  
#### TODO:  
#### Notes

You can insert a template into a new note with CMD + P and looking for the Templater option.

I then keep adding new days with another template:

### <% tp.file.last_modified_date("dddd Do MMMM YYYY") %>  
#### Done:  
#### TODO:  
#### Notes:

This way you can keep adding days to your project and update with reasonings and things you still have to do and have done. An example below:


Example of project note with timestamped notes.

3.5 Private Encrypted Diary

This is one of my favorite Obsidian uses.
Mini Diary's interface has long frustrated me. After the author archived the project, I looked for a replacement. I had two demands:

  1. It had to be private, and nobody had to be able to read the entries.
  2. Cloud syncing was required for editing on multiple devices.

Then I learned about encrypting the Obsidian folder. Then decrypt and open the folder with Obsidian. Sync the folder as usual.
Use CryptoMator (https://cryptomator.org/). Create an encrypted folder in Cryptomator for your Obsidian vault, set a password, and let it do the rest.
If you need a step-by-step video guide, here it is:

Conclusion

So, I hope this was helpful!
In the first section of the article, we discussed notes and note-taking techniques. We discussed when to use tags and links over folders and when to break up larger notes.
Then we learned about Obsidian, its interface, and some useful plugins like Citations for citing papers and Templater for creating note templates.
Finally, we discussed workflows and how to use Zotero to take notes from scientific papers, as well as managing Lab Books and Private Encrypted Diaries.
Thanks for reading and commenting :)

Read original post here

Liam Vaughan

Liam Vaughan

3 years ago

Investors can bet big on almost anything on a new prediction market.

Kalshi allows five-figure bets on the Grammys, the next Covid wave, and future SEC commissioners. Worst-case scenario

On Election Day 2020, two young entrepreneurs received a call from the CFTC chairman. Luana Lopes Lara and Tarek Mansour spent 18 months trying to start a new type of financial exchange. Instead of betting on stock prices or commodity futures, people could trade instruments tied to real-world events, such as legislation, the weather, or the Oscar winner.

Heath Tarbert, a Trump appointee, shouted "Congratulations." "You're competing with 1840s-era markets. I'm sure you'll become a powerhouse too."

Companies had tried to introduce similar event markets in the US for years, but Tarbert's agency, the CFTC, said no, arguing they were gambling and prone to cheating. Now the agency has reversed course, approving two 24-year-olds who will have first-mover advantage in what could become a huge new asset class. Kalshi Inc. raised $30 million from venture capitalists within weeks of Tarbert's call, his representative says. Mansour, 26, believes this will be bigger than crypto.

Anyone who's read The Wisdom of Crowds knows prediction markets' potential. Well-designed markets can help draw out knowledge from disparate groups, and research shows that when money is at stake, people make better predictions. Lopes Lara calls it a "bullshit tax." That's why Google, Microsoft, and even the US Department of Defense use prediction markets internally to guide decisions, and why university-linked political betting sites like PredictIt sometimes outperform polls.

Regulators feared Wall Street-scale trading would encourage investors to manipulate reality. If the stakes are high enough, traders could pressure congressional staffers to stall a bill or bet on whether Kanye West's new album will drop this week. When Lopes Lara and Mansour pitched the CFTC, senior regulators raised these issues. Politically appointed commissioners overruled their concerns, and one later joined Kalshi's board.

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Kalshi's victory was due more to lobbying and legal wrangling than to Silicon Valley-style innovation. Lopes Lara and Mansour didn't invent anything; they changed a well-established concept's governance. The result could usher in a new era of market-based enlightenment or push Wall Street's destructive tendencies into the real world.

If Kalshi's founders lacked experience to bolster their CFTC application, they had comical youth success. Lopes Lara studied ballet at the Brazilian Bolshoi before coming to the US. Mansour won France's math Olympiad. They bonded over their work ethic in an MIT computer science class.

Lopes Lara had the idea for Kalshi while interning at a New York hedge fund. When the traders around her weren't working, she noticed they were betting on the news: Would Apple hit a trillion dollars? Kylie Jenner? "It was anything," she says.

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Mansour saw the business potential when Lopes Lara suggested it. He interned at Goldman Sachs Group Inc., helping investors prepare for the UK leaving the EU. Goldman sold clients complex stock-and-derivative combinations. As he discussed it with Lopes Lara, they agreed that investors should hedge their risk by betting on Brexit itself rather than an imperfect proxy.

Lopes Lara and Mansour hypothesized how a marketplace might work. They settled on a "event contract," a binary-outcome instrument like "Will inflation hit 5% by the end of the month?" The contract would settle at $1 (if the event happened) or zero (if it didn't), but its price would fluctuate based on market sentiment. After a good debate, a politician's election odds may rise from 50 to 55. Kalshi would charge a commission on every trade and sell data to traders, political campaigns, businesses, and others.

In October 2018, five months after graduation, the pair flew to California to compete in a hackathon for wannabe tech founders organized by the Silicon Valley incubator Y Combinator. They built a website in a day and a night and presented it to entrepreneurs the next day. Their prototype barely worked, but they won a three-month mentorship program and $150,000. Michael Seibel, managing director of Y Combinator, said of their idea, "I had to take a chance!"

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Seibel's skepticism was rooted in America's historical wariness of gambling. Roulette, poker, and other online casino games are largely illegal, and sports betting was only legal in a few states until May 2018. Kalshi as a risk-hedging platform rather than a bookmaker seemed like a good idea, but convincing the CFTC wouldn't be easy. In 2012, the CFTC said trading on politics had no "economic purpose" and was "contrary to the public interest."

Lopes Lara and Mansour cold-called 60 Googled lawyers during their time at Y Combinator. Everyone advised quitting. Mansour recalls the pain. Jeff Bandman, a former CFTC official, helped them navigate the agency and its characters.

When they weren’t busy trying to recruit lawyers, Lopes Lara and Mansour were meeting early-stage investors. Alfred Lin of Sequoia Capital Operations LLC backed Airbnb, DoorDash, and Uber Technologies. Lin told the founders their idea could capitalize on retail trading and challenge how the financial world manages risk. "Come back with regulatory approval," he said.

In the US, even small bets on most events were once illegal. Under the Commodity Exchange Act, the CFTC can stop exchanges from listing contracts relating to "terrorism, assassination, war" and "gaming" if they are "contrary to the public interest," which was often the case.

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In 1988, as academic interest in the field grew, the agency allowed the University of Iowa to set up a prediction market for research purposes, as long as it didn't make a profit or advertise and limited bets to $500. PredictIt, the biggest and best-known political betting platform in the US, also got an exemption thanks to an association with Victoria University of Wellington in New Zealand. Today, it's a sprawling marketplace with its own subculture and lingo. PredictIt users call it "Rules Cuck Panther" when they lose on a technicality. Major news outlets cite PredictIt's odds on Discord and the Star Spangled Gamblers podcast.

CFTC limits PredictIt bets to $850. To keep traders happy, PredictIt will often run multiple variations of the same question, listing separate contracts for two dozen Democratic primary candidates, for example. A trader could have more than $10,000 riding on a single outcome. Some of the site's traders are current or former campaign staffers who can answer questions like "How many tweets will Donald Trump post from Nov. 20 to 27?" and "When will Anthony Scaramucci's role as White House communications director end?"

According to PredictIt co-founder John Phillips, politicians help explain the site's accuracy. "Prediction markets work well and are accurate because they attract people with superior information," he said in a 2016 podcast. “In the financial stock market, it’s called inside information.”

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Trading on nonpublic information is illegal outside of academia, which presented a dilemma for Lopes Lara and Mansour. Kalshi's forecasts needed to be accurate. Kalshi must eliminate insider trading as a regulated entity. Lopes Lara and Mansour wanted to build a high-stakes PredictIt without the anarchy or blurred legal lines—a "New York Stock Exchange for Events." First, they had to convince regulators event trading was safe.

When Lopes Lara and Mansour approached the CFTC in the spring of 2019, some officials in the Division of Market Oversight were skeptical, according to interviews with people involved in the process. For all Kalshi's talk of revolutionizing finance, this was just a turbocharged version of something that had been rejected before.

The DMO couldn't see the big picture. The staff review was supposed to ensure Kalshi could complete a checklist, "23 Core Principles of a Designated Contract Market," which included keeping good records and having enough money. The five commissioners decide. With Trump as president, three of them were ideologically pro-market.

Lopes Lara, Mansour, and their lawyer Bandman, an ex-CFTC official, answered the DMO's questions while lobbying the commissioners on Zoom about the potential of event markets to mitigate risks and make better decisions. Before each meeting, they would write a script and memorize it word for word.

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Several prediction markets that hadn't sought regulatory approval bolstered Kalshi's case. Polymarket let customers bet hundreds of thousands of dollars anonymously using cryptocurrencies, making it hard to track. Augur, which facilitates private wagers between parties using blockchain, couldn't regulate bets and hadn't stopped users from betting on assassinations. Kalshi, by comparison, argued it was doing everything right. (The CFTC fined Polymarket $1.4 million for operating an unlicensed exchange in January 2022. Polymarket says it's now compliant and excited to pioneer smart contract-based financial solutions with regulators.

Kalshi was approved unanimously despite some DMO members' concerns about event contracts' riskiness. "Once they check all the boxes, they're in," says a CFTC insider.

Three months after CFTC approval, Kalshi announced funding from Sequoia, Charles Schwab, and Henry Kravis. Sequoia's Lin, who joined the board, said Tarek, Luana, and team created a new way to invest and engage with the world.

The CFTC hadn't asked what markets the exchange planned to run since. After approval, Lopes Lara and Mansour had the momentum. Kalshi's March list of 30 proposed contracts caused chaos at the DMO. The division handles exchanges that create two or three new markets a year. Kalshi’s business model called for new ones practically every day.

Uncontroversial proposals included weather and GDP questions. Others, on the initial list and later, were concerning. DMO officials feared Covid-19 contracts amounted to gambling on human suffering, which is why war and terrorism markets are banned. (Similar logic doomed ex-admiral John Poindexter's Policy Analysis Market, a Bush-era plan to uncover intelligence by having security analysts bet on Middle East events.) Regulators didn't see how predicting the Grammy winners was different from betting on the Patriots to win the Super Bowl. Who, other than John Legend, would need to hedge the best R&B album winner?

Event contracts raised new questions for the DMO's product review team. Regulators could block gaming contracts that weren't in the public interest under the Commodity Exchange Act, but no one had defined gaming. It was unclear whether the CFTC had a right or an obligation to consider whether a contract was in the public interest. How was it to determine public interest? Another person familiar with the CFTC review says, "It was a mess." The agency didn't comment.

CFTC staff feared some event contracts could be cheated. Kalshi wanted to run a bee-endangerment market. The DMO pushed back, saying it saw two problems symptomatic of the asset class: traders could press government officials for information, and officials could delay adding the insects to the list to cash in.

The idea that traders might manipulate prediction markets wasn't paranoid. In 2013, academics David Rothschild and Rajiv Sethi found that an unidentified party lost $7 million buying Mitt Romney contracts on Intrade, a now-defunct, unlicensed Irish platform, in the runup to the 2012 election. The authors speculated that the trader, whom they dubbed the “Romney Whale,” may have been looking to boost morale and keep donations coming in.

Kalshi said manipulation and insider trading are risks for any market. It built a surveillance system and said it would hire a team to monitor it. "People trade on events all the time—they just use options and other instruments. This brings everything into the open, Mansour says. Kalshi didn't include election contracts, a red line for CFTC Democrats.

Lopes Lara and Mansour were ready to launch kalshi.com that summer, but the DMO blocked them. Product reviewers were frustrated by spending half their time on an exchange that represented a tiny portion of the derivatives market. Lopes Lara and Mansour pressed politically appointed commissioners during the impasse.

Tarbert, the chairman, had moved on, but Kalshi found a new supporter in Republican Brian Quintenz, a crypto-loving former hedge fund manager. He was unmoved by the DMO's concerns, arguing that speculation on Kalshi's proposed events was desirable and the agency had no legal standing to prevent it. He supported a failed bid to allow NFL futures earlier this year. Others on the commission were cautious but supportive. Given the law's ambiguity, they worried they'd be on shaky ground if Kalshi sued if they blocked a contract. Without a permanent chairman, the agency lacked leadership.

To block a contract, DMO staff needed a majority of commissioners' support, which they didn't have in all but a few cases. "We didn't have the votes," a reviewer says, paraphrasing Hamilton. By the second half of 2021, new contract requests were arriving almost daily at the DMO, and the demoralized and overrun division eventually accepted defeat and stopped fighting back. By the end of the year, three senior DMO officials had left the agency, making it easier for Kalshi to list its contracts unimpeded.

Today, Kalshi is growing. 32 employees work in a SoHo office with big windows and exposed brick. Quintenz, who left the CFTC 10 months after Kalshi was approved, is on its board. He joined because he was interested in the market's hedging and risk management opportunities.

Mid-May, the company's website had 75 markets, such as "Will Q4 GDP be negative?" Will NASA land on the moon by 2025? The exchange recently reached 2 million weekly contracts, a jump from where it started but still a small number compared to other futures exchanges. Early adopters are PredictIt and Polymarket fans. Bets on the site are currently capped at $25,000, but Kalshi hopes to increase that to $100,000 and beyond.

With the regulatory drawbridge down, Lopes Lara and Mansour must move quickly. Chicago's CME Group Inc. plans to offer index-linked event contracts. Kalshi will release a smartphone app to attract customers. After that, it hopes to partner with a big brokerage. Sequoia is a major investor in Robinhood Markets Inc. Robinhood users could have access to Kalshi so that after buying GameStop Corp. shares, they'd be prompted to bet on the Oscars or the next Fed commissioner.

Some, like Illinois Democrat Sean Casten, accuse Robinhood and its competitors of gamifying trading to encourage addiction, but Kalshi doesn't seem worried. Mansour says Kalshi's customers can't bet more than they've deposited, making debt difficult. Eventually, he may introduce leveraged bets.

Tension over event contracts recalls another CFTC episode. Brooksley Born proposed regulating the financial derivatives market in 1994. Alan Greenspan and others in the government opposed her, saying it would stifle innovation and push capital overseas. Unrestrained, derivatives grew into a trillion-dollar industry until 2008, when they sparked the financial crisis.

Today, with a midterm election looming, it seems reasonable to ask whether Kalshi plans to get involved. Elections have historically been the biggest draw in prediction markets, with 125 million shares traded on PredictIt for 2020. “We can’t discuss specifics,” Mansour says. “All I can say is, you know, we’re always working on expanding the universe of things that people can trade on.”

Any election contracts would need CFTC approval, which may be difficult with three Democratic commissioners. A Republican president would change the equation.