More on Web3 & Crypto

Vitalik
4 years ago
An approximate introduction to how zk-SNARKs are possible (part 1)
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has 2 very powerful applications: Perhaps the most powerful cryptographic technology to come out of the last decade is general-purpose succinct zero knowledge proofs, usually called zk-SNARKs ("zero knowledge succinct arguments of knowledge"). A zk-SNARK allows you to generate a proof that some computation has some particular output, in such a way that the proof can be verified extremely quickly even if the underlying computation takes a very long time to run. The "ZK" part adds an additional feature: the proof can keep some of the inputs to the computation hidden.
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has two very powerful applications:
- Scalability: if a block takes a long time to verify, one person can verify it and generate a proof, and everyone else can just quickly verify the proof instead
- Privacy: you can prove that you have the right to transfer some asset (you received it, and you didn't already transfer it) without revealing the link to which asset you received. This ensures security without unduly leaking information about who is transacting with whom to the public.
But zk-SNARKs are quite complex; indeed, as recently as in 2014-17 they were still frequently called "moon math". The good news is that since then, the protocols have become simpler and our understanding of them has become much better. This post will try to explain how ZK-SNARKs work, in a way that should be understandable to someone with a medium level of understanding of mathematics.
Why ZK-SNARKs "should" be hard
Let us take the example that we started with: we have a number (we can encode "cow" followed by the secret input as an integer), we take the SHA256 hash of that number, then we do that again another 99,999,999 times, we get the output, and we check what its starting digits are. This is a huge computation.
A "succinct" proof is one where both the size of the proof and the time required to verify it grow much more slowly than the computation to be verified. If we want a "succinct" proof, we cannot require the verifier to do some work per round of hashing (because then the verification time would be proportional to the computation). Instead, the verifier must somehow check the whole computation without peeking into each individual piece of the computation.
One natural technique is random sampling: how about we just have the verifier peek into the computation in 500 different places, check that those parts are correct, and if all 500 checks pass then assume that the rest of the computation must with high probability be fine, too?
Such a procedure could even be turned into a non-interactive proof using the Fiat-Shamir heuristic: the prover computes a Merkle root of the computation, uses the Merkle root to pseudorandomly choose 500 indices, and provides the 500 corresponding Merkle branches of the data. The key idea is that the prover does not know which branches they will need to reveal until they have already "committed to" the data. If a malicious prover tries to fudge the data after learning which indices are going to be checked, that would change the Merkle root, which would result in a new set of random indices, which would require fudging the data again... trapping the malicious prover in an endless cycle.
But unfortunately there is a fatal flaw in naively applying random sampling to spot-check a computation in this way: computation is inherently fragile. If a malicious prover flips one bit somewhere in the middle of a computation, they can make it give a completely different result, and a random sampling verifier would almost never find out.
It only takes one deliberately inserted error, that a random check would almost never catch, to make a computation give a completely incorrect result.
If tasked with the problem of coming up with a zk-SNARK protocol, many people would make their way to this point and then get stuck and give up. How can a verifier possibly check every single piece of the computation, without looking at each piece of the computation individually? There is a clever solution.
see part 2

forkast
3 years ago
Three Arrows Capital collapse sends crypto tremors
Three Arrows Capital's Google search volume rose over 5,000%.
Three Arrows Capital, a Singapore-based cryptocurrency hedge fund, filed for Chapter 15 bankruptcy last Friday to protect its U.S. assets from creditors.
Three Arrows filed for bankruptcy on July 1 in New York.
Three Arrows was ordered liquidated by a British Virgin Islands court last week after defaulting on a $670 million loan from Voyager Digital. Three days later, the Singaporean government reprimanded Three Arrows for spreading misleading information and exceeding asset limits.
Three Arrows' troubles began with Terra's collapse in May, after it bought US$200 million worth of Terra's LUNA tokens in February, co-founder Kyle Davies told the Wall Street Journal. Three Arrows has failed to meet multiple margin calls since then, including from BlockFi and Genesis.
Three Arrows Capital, founded by Kyle Davies and Su Zhu in 2012, manages $10 billion in crypto assets.
Bitcoin's price fell from US$20,600 to below US$19,200 after Three Arrows' bankruptcy petition. According to CoinMarketCap, BTC is now above US$20,000.
What does it mean?
Every action causes an equal and opposite reaction, per Newton's third law. Newtonian physics won't comfort Three Arrows investors, but future investors will thank them for their overconfidence.
Regulators are taking notice of crypto's meteoric rise and subsequent fall. Historically, authorities labeled the industry "high risk" to warn traditional investors against entering it. That attitude is changing. Regulators are moving quickly to regulate crypto to protect investors and prevent broader asset market busts.
The EU has reached a landmark deal that will regulate crypto asset sales and crypto markets across the 27-member bloc. The U.S. is close behind with a similar ruling, and smaller markets are also looking to improve safeguards.
For many, regulation is the only way to ensure the crypto industry survives the current winter.

Miguel Saldana
3 years ago
Crypto Inheritance's Catch-22
Security, privacy, and a strategy!
How to manage digital assets in worst-case scenarios is a perennial crypto concern. Since blockchain and bitcoin technology is very new, this hasn't been a major issue. Many early developers are still around, and many groups created around this technology are young and feel they have a lot of life remaining. This is why inheritance and estate planning in crypto should be handled promptly. As cryptocurrency's intrinsic worth rises, many people in the ecosystem are holding on to assets that might represent generational riches. With that much value, it's crucial to have a plan. Creating a solid plan entails several challenges.
the initial hesitation in coming up with a plan
The technical obstacles to ensuring the assets' security and privacy
the passing of assets from a deceased or incompetent person
Legal experts' lack of comprehension and/or understanding of how to handle and treat cryptocurrency.
This article highlights several challenges, a possible web3-native solution, and how to learn more.
The Challenge of Inheritance:
One of the biggest hurdles to inheritance planning is starting the conversation. As humans, we don't like to think about dying. Early adopters will experience crazy gains as cryptocurrencies become more popular. Creating a plan is crucial if you wish to pass on your riches to loved ones. Without a plan, the technical and legal issues I barely mentioned above would erode value by requiring costly legal fees and/or taxes, and you could lose everything if wallets and assets are not distributed appropriately (associated with the private keys). Raising awareness of the consequences of not having a plan should motivate people to make one.
Controlling Change:
Having an inheritance plan for your digital assets is crucial, but managing the guts and bolts poses a new set of difficulties. Privacy and security provided by maintaining your own wallet provide different issues than traditional finances and assets. Traditional finance is centralized (say a stock brokerage firm). You can assign another person to handle the transfer of your assets. In crypto, asset transfer is reimagined. One may suppose future transaction management is doable, but the user must consent, creating an impossible loop.
I passed away and must send a transaction to the person I intended to deliver it to.
I have to confirm or authorize the transaction, but I'm dead.
In crypto, scheduling a future transaction wouldn't function. To transfer the wallet and its contents, we'd need the private keys and/or seed phrase. Minimizing private key exposure is crucial to protecting your crypto from hackers, social engineering, and phishing. People have lost private keys after utilizing Life Hack-type tactics to secure them. People that break and hide their keys, lose them, or make them unreadable won't help with managing and/or transferring. This will require a derived solution.
Legal Challenges and Implications
Unlike routine cryptocurrency transfers and transactions, local laws may require special considerations. Even in the traditional world, estate/inheritance taxes, how assets will be split, and who executes the will must be considered. Many lawyers aren't crypto-savvy, which complicates the matter. There will be many hoops to jump through to safeguard your crypto and traditional assets and give them to loved ones.
Knowing RUFADAA/UFADAA, depending on your state, is vital for Americans. UFADAA offers executors and trustees access to online accounts (which crypto wallets would fall into). RUFADAA was changed to limit access to the executor to protect assets. RUFADAA outlines how digital assets are administered following death and incapacity in the US.
A Succession Solution
Having a will and talking about who would get what is the first step to having a solution, but using a Dad Mans Switch is a perfect tool for such unforeseen circumstances. As long as the switch's controller has control, nothing happens. Losing control of the switch initiates a state transition.
Subway or railway operations are examples. Modern control systems need the conductor to hold a switch to keep the train going. If they can't, the train stops.
Enter Sarcophagus
Sarcophagus is a decentralized dead man's switch built on Ethereum and Arweave. Sarcophagus allows actors to maintain control of their possessions even while physically unable to do so. Using a programmable dead man's switch and dual encryption, anything can be kept and passed on. This covers assets, secrets, seed phrases, and other use cases to provide authority and control back to the user and release trustworthy services from this work. Sarcophagus is built on a decentralized, transparent open source codebase. Sarcophagus is there if you're unprepared.
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Nir Zicherman
3 years ago
The Great Organizational Conundrum
Only two of the following three options can be achieved: consistency, availability, and partition tolerance
Someone told me that growing from 30 to 60 is the biggest adjustment for a team or business.
I remember thinking, That's random. Each company is unique. I've seen teams of all types confront the same issues during development periods. With new enterprises starting every year, we should be better at navigating growing difficulties.
As a team grows, its processes and systems break down, requiring reorganization or declining results. Why always? Why isn't there a perfect scaling model? Why hasn't that been found?
The Three Things Productive Organizations Must Have
Any company should be efficient and productive. Three items are needed:
First, it must verify that no two team members have conflicting information about the roadmap, strategy, or any input that could affect execution. Teamwork is required.
Second, it must ensure that everyone can receive the information they need from everyone else quickly, especially as teams become more specialized (an inevitability in a developing organization). It requires everyone's accessibility.
Third, it must ensure that the organization can operate efficiently even if a piece is unavailable. It's partition-tolerant.
From my experience with the many teams I've been on, invested in, or advised, achieving all three is nearly impossible. Why a perfect organization model cannot exist is clear after analysis.
The CAP Theorem: What is it?
Eric Brewer of Berkeley discovered the CAP Theorem, which argues that a distributed data storage should have three benefits. One can only have two at once.
The three benefits are consistency, availability, and partition tolerance, which implies that even if part of the system is offline, the remainder continues to work.
This notion is usually applied to computer science, but I've realized it's also true for human organizations. In a post-COVID world, many organizations are hiring non-co-located staff as they grow. CAP Theorem is more important than ever. Growing teams sometimes think they can develop ways to bypass this law, dooming themselves to a less-than-optimal team dynamic. They should adopt CAP to maximize productivity.
Path 1: Consistency and availability equal no tolerance for partitions
Let's imagine you want your team to always be in sync (i.e., for someone to be the source of truth for the latest information) and to be able to share information with each other. Only division into domains will do.
Numerous developing organizations do this, especially after the early stage (say, 30 people) when everyone may wear many hats and be aware of all the moving elements. After a certain point, it's tougher to keep generalists aligned than to divide them into specialized tasks.
In a specialized, segmented team, leaders optimize consistency and availability (i.e. every function is up-to-speed on the latest strategy, no one is out of sync, and everyone is able to unblock and inform everyone else).
Partition tolerance suffers. If any component of the organization breaks down (someone goes on vacation, quits, underperforms, or Gmail or Slack goes down), productivity stops. There's no way to give the team stability, availability, and smooth operation during a hiccup.
Path 2: Partition Tolerance and Availability = No Consistency
Some businesses avoid relying too heavily on any one person or sub-team by maximizing availability and partition tolerance (the organization continues to function as a whole even if particular components fail). Only redundancy can do that. Instead of specializing each member, the team spreads expertise so people can work in parallel. I switched from Path 1 to Path 2 because I realized too much reliance on one person is risky.
What happens after redundancy? Unreliable. The more people may run independently and in parallel, the less anyone can be the truth. Lack of alignment or updated information can lead to people executing slightly different strategies. So, resources are squandered on the wrong work.
Path 3: Partition and Consistency "Tolerance" equates to "absence"
The third, least-used path stresses partition tolerance and consistency (meaning answers are always correct and up-to-date). In this organizational style, it's most critical to maintain the system operating and keep everyone aligned. No one is allowed to read anything without an assurance that it's up-to-date (i.e. there’s no availability).
Always short-lived. In my experience, a business that prioritizes quality and scalability over speedy information transmission can get bogged down in heavy processes that hinder production. Large-scale, this is unsustainable.
Accepting CAP
When two puzzle pieces fit, the third won't. I've watched developing teams try to tackle these difficulties, only to find, as their ancestors did, that they can never be entirely solved. Idealized solutions fail in reality, causing lost effort, confusion, and lower production.
As teams develop and change, they should embrace CAP, acknowledge there is a limit to productivity in a scaling business, and choose the best two-out-of-three path.

Jenn Leach
3 years ago
How Much I Got Paid by YouTube for a 68 Million Views Video
My nameless, faceless channel case study
The Numbers
I anonymize this YouTube channel.
It's in a trendy, crowded niche. Sharing it publicly will likely enhance competition.
I'll still share my dashboard numbers:
A year ago, the video was released.
What I earned
I'll stop stalling. Here's a screenshot of my YouTube statistics page displaying Adsense profits.
YouTube Adsense made me ZERO dollars.
OMG!
How is this possible?
YouTube Adsense can't monetize my niche. This is typical in faceless niches like TikTok's rain videos. If they were started a while ago, I'm sure certain rain accounts are monetized, but not today.
I actually started a soothing sounds faceless YouTube channel. This was another account of mine.
I looped Pexels films for hours. No background music, just wind, rain, etc.
People could watch these videos to relax or get ready for bed. They're ideal for background noise and relaxation.
They're long-lasting, too. It's easy to make a lot from YouTube Adsense if you insert ads.
Anyway, I tried to monetize it and couldn’t. This was about a year ago. That’s why I doubt new accounts in this genre would be able to get approved for ads.
Back to my faceless channel with 68 million views.
I received nothing from YouTube Adsense, but I made money elsewhere.
Getting paid by the gods of affiliate marketing
Place links in the video and other videos on the channel to get money. Visitors that buy through your affiliate link earn you a commission.
This video earned many clicks on my affiliate links.
I linked to a couple of Amazon products, a YouTube creator tool, my kofi link, and my subscribe link.
Sponsorships
Brands pay you to include ads in your videos.
This video led to many sponsorships.
I've done dozens of sponsorship campaigns that paid $40 to $50 for an end screen to $450 for a preroll ad.
Last word
Overall, I made less than $3,000.
If I had time, I'd be more proactive with sponsorships. You can pitch brand sponsorships. This actually works.
I'd do that if I could rewind time.
I still can, but I think the reaction rate would be higher closer to the viral video's premiere date.

Sammy Abdullah
3 years ago
Payouts to founders at IPO
How much do startup founders make after an IPO? We looked at 2018's major tech IPOs. Paydays aren't what founders took home at the IPO (shares are normally locked up for 6 months), but what they were worth at the IPO price on the day the firm went public. It's not cash, but it's nice. Here's the data.
Several points are noteworthy.
Huge payoffs. Median and average pay were $399m and $918m. Average and median homeownership were 9% and 12%.
Coinbase, Uber, UI Path. Uber, Zoom, Spotify, UI Path, and Coinbase founders raised billions. Zoom's founder owned 19% and Spotify's 28% and 13%. Brian Armstrong controlled 20% of Coinbase at IPO and was worth $15bn. Preserving as much equity as possible by staying cash-efficient or raising at high valuations also helps.
The smallest was Ping. Ping's compensation was the smallest. Andre Duand owned 2% but was worth $20m at IPO. That's less than some billion-dollar paydays, but still good.
IPOs can be lucrative, as you can see. Preserving equity could be the difference between a $20mm and $15bln payday (Coinbase).