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
(Edited)
More on Web3 & Crypto

Ren & Heinrich
3 years ago
200 DeFi Projects were examined. Here is what I learned.
I analyze the top 200 DeFi crypto projects in this article.
This isn't a study. The findings benefit crypto investors.
Let’s go!
A set of data
I analyzed data from defillama.com. In my analysis, I used the top 200 DeFis by TVL in October 2022.
Total Locked Value
The chart below shows platform-specific locked value.
14 platforms had $1B+ TVL. 65 platforms have $100M-$1B TVL. The remaining 121 platforms had TVLs below $100 million, with the lowest being $23 million.
TVLs are distributed Pareto. Top 40% of DeFis account for 80% of TVLs.
Compliant Blockchains
Ethereum's blockchain leads DeFi. 96 of the examined projects offer services on Ethereum. Behind BSC, Polygon, and Avalanche.
Five platforms used 10+ blockchains. 36 between 2-10 159 used 1 blockchain.
Use Cases for DeFi
The chart below shows platform use cases. Each platform has decentralized exchanges, liquid staking, yield farming, and lending.
These use cases are DefiLlama's main platform features.
Which use case costs the most? Chart explains. Collateralized debt, liquid staking, dexes, and lending have high TVLs.
The DeFi Industry
I compared three high-TVL platforms (Maker DAO, Balancer, AAVE). The columns show monthly TVL and token price changes. The graph shows monthly Bitcoin price changes.
Each platform's market moves similarly.
Probably because most DeFi deposits are cryptocurrencies. Since individual currencies are highly correlated with Bitcoin, it's not surprising that they move in unison.
Takeaways
This analysis shows that the most common DeFi services (decentralized exchanges, liquid staking, yield farming, and lending) also have the highest average locked value.
Some projects run on one or two blockchains, while others use 15 or 20. Our analysis shows that a project's blockchain count has no correlation with its success.
It's hard to tell if certain use cases are rising. Bitcoin's price heavily affects the entire DeFi market.
TVL seems to be a good indicator of a DeFi platform's success and quality. Higher TVL platforms are cheaper. They're a better long-term investment because they gain or lose less value than DeFis with lower TVLs.
Isobel Asher Hamilton
3 years ago
$181 million in bitcoin buried in a dump. $11 million to get them back
James Howells lost 8,000 bitcoins. He has $11 million to get them back.
His life altered when he threw out an iPhone-sized hard drive.
Howells, from the city of Newport in southern Wales, had two identical laptop hard drives squirreled away in a drawer in 2013. One was blank; the other had 8,000 bitcoins, currently worth around $181 million.
He wanted to toss out the blank one, but the drive containing the Bitcoin went to the dump.
He's determined to reclaim his 2009 stash.
Howells, 36, wants to arrange a high-tech treasure hunt for bitcoins. He can't enter the landfill.
Newport's city council has rebuffed Howells' requests to dig for his hard drive for almost a decade, stating it would be expensive and environmentally destructive.
I got an early look at his $11 million idea to search 110,000 tons of trash. He expects submitting it to the council would convince it to let him recover the hard disk.
110,000 tons of trash, 1 hard drive
Finding a hard disk among heaps of trash may seem Herculean.
Former IT worker Howells claims it's possible with human sorters, robot dogs, and an AI-powered computer taught to find hard drives on a conveyor belt.
His idea has two versions, depending on how much of the landfill he can search.
His most elaborate solution would take three years and cost $11 million to sort 100,000 metric tons of waste. Scaled-down version costs $6 million and takes 18 months.
He's created a team of eight professionals in AI-powered sorting, landfill excavation, garbage management, and data extraction, including one who recovered Columbia's black box data.
The specialists and their companies would be paid a bonus if they successfully recovered the bitcoin stash.
Howells: "We're trying to commercialize this project."
Howells claimed rubbish would be dug up by machines and sorted near the landfill.
Human pickers and a Max-AI machine would sort it. The machine resembles a scanner on a conveyor belt.
Remi Le Grand of Max-AI told us it will train AI to recognize Howells-like hard drives. A robot arm would select candidates.
Howells has added security charges to his scheme because he fears people would steal the hard drive.
He's budgeted for 24-hour CCTV cameras and two robotic "Spot" canines from Boston Dynamics that would patrol at night and look for his hard drive by day.
Howells said his crew met in May at the Celtic Manor Resort outside Newport for a pitch rehearsal.
Richard Hammond's narrative swings from banal to epic.
Richard Hammond filmed the meeting and created a YouTube documentary on Howells.
Hammond said of Howells' squad, "They're committed and believe in him and the idea."
Hammond: "It goes from banal to gigantic." "If I were in his position, I wouldn't have the strength to answer the door."
Howells said trash would be cleaned and repurposed after excavation. Reburying the rest.
"We won't pollute," he declared. "We aim to make everything better."
After the project is finished, he hopes to develop a solar or wind farm on the dump site. The council is unlikely to accept his vision soon.
A council representative told us, "Mr. Howells can't convince us of anything." "His suggestions constitute a significant ecological danger, which we can't tolerate and are forbidden by our permit."
Will the recovered hard drive work?
The "platter" is a glass or metal disc that holds the hard drive's data. Howells estimates 80% to 90% of the data will be recoverable if the platter isn't damaged.
Phil Bridge, a data-recovery expert who consulted Howells, confirmed these numbers.
If the platter is broken, Bridge adds, data recovery is unlikely.
Bridge says he was intrigued by the proposal. "It's an intriguing case," he added. Helping him get it back and proving everyone incorrect would be a great success story.
Who'd pay?
Swiss and German venture investors Hanspeter Jaberg and Karl Wendeborn told us they would fund the project if Howells received council permission.
Jaberg: "It's a needle in a haystack and a high-risk investment."
Howells said he had no contract with potential backers but had discussed the proposal in Zoom meetings. "Until Newport City Council gives me something in writing, I can't commit," he added.
Suppose he finds the bitcoins.
Howells said he would keep 30% of the data, worth $54 million, if he could retrieve it.
A third would go to the recovery team, 30% to investors, and the remainder to local purposes, including gifting £50 ($61) in bitcoin to each of Newport's 150,000 citizens.
Howells said he opted to spend extra money on "professional firms" to help convince the council.
What if the council doesn't approve?
If Howells can't win the council's support, he'll sue, claiming its actions constitute a "illegal embargo" on the hard drive. "I've avoided that path because I didn't want to cause complications," he stated. I wanted to cooperate with Newport's council.
Howells never met with the council face-to-face. He mentioned he had a 20-minute Zoom meeting in May 2021 but thought his new business strategy would help.
He met with Jessica Morden on June 24. Morden's office confirmed meeting.
After telling the council about his proposal, he can only wait. "I've never been happier," he said. This is our most professional operation, with the best employees.
The "crypto proponent" buys bitcoin every month and sells it for cash.
Howells tries not to think about what he'd do with his part of the money if the hard disk is found functional. "Otherwise, you'll go mad," he added.
This post is a summary. Read the full article here.

Sam Bourgi
3 years ago
DAOs are legal entities in Marshall Islands.
The Pacific island state recognizes decentralized autonomous organizations.
The Republic of the Marshall Islands has recognized decentralized autonomous organizations (DAOs) as legal entities, giving collectively owned and managed blockchain projects global recognition.
The Marshall Islands' amended the Non-Profit Entities Act 2021 that now recognizes DAOs, which are blockchain-based entities governed by self-organizing communities. Incorporating Admiralty LLC, the island country's first DAO, was made possible thanks to the amendement. MIDAO Directory Services Inc., a domestic organization established to assist DAOs in the Marshall Islands, assisted in the incorporation.
The new law currently allows any DAO to register and operate in the Marshall Islands.
“This is a unique moment to lead,” said Bobby Muller, former Marshall Islands chief secretary and co-founder of MIDAO. He believes DAOs will help create “more efficient and less hierarchical” organizations.
A global hub for DAOs, the Marshall Islands hopes to become a global hub for DAO registration, domicile, use cases, and mass adoption. He added:
"This includes low-cost incorporation, a supportive government with internationally recognized courts, and a technologically open environment."
According to the World Bank, the Marshall Islands is an independent island state in the Pacific Ocean near the Equator. To create a blockchain-based cryptocurrency that would be legal tender alongside the US dollar, the island state has been actively exploring use cases for digital assets since at least 2018.
In February 2018, the Marshall Islands approved the creation of a new cryptocurrency, Sovereign (SOV). As expected, the IMF has criticized the plan, citing concerns that a digital sovereign currency would jeopardize the state's financial stability. They have also criticized El Salvador, the first country to recognize Bitcoin (BTC) as legal tender.
Marshall Islands senator David Paul said the DAO legislation does not pose the same issues as a government-backed cryptocurrency. “A sovereign digital currency is financial and raises concerns about money laundering,” . This is more about giving DAOs legal recognition to make their case to regulators, investors, and consumers.
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Al Anany
2 years ago
Because of this covert investment that Bezos made, Amazon became what it is today.
He kept it under wraps for years until he legally couldn’t.
His shirt is incomplete. I can’t stop thinking about this…
Actually, ignore the article. Look at it. JUST LOOK at it… It’s quite disturbing, isn’t it?
Ughh…
Me: “Hey, what up?” Friend: “All good, watching lord of the rings on amazon prime video.” Me: “Oh, do you know how Amazon grew and became famous?” Friend: “Geek alert…Can I just watch in peace?” Me: “But… Bezos?” Friend: “Let it go, just let it go…”
I can question you, the reader, and start answering instantly without his consent. This far.
Reader, how did Amazon succeed? You'll say, Of course, it was an internet bookstore, then it sold everything.
Mistaken. They moved from zero to one because of this. How did they get from one to thousand? AWS-some. Understand? It's geeky and lame. If not, I'll explain my geekiness.
Over an extended period of time, Amazon was not profitable.
Business basics. You want customers if you own a bakery, right?
Well, 100 clients per day order $5 cheesecakes (because cheesecakes are awesome.)
$5 x 100 consumers x 30 days Equals $15,000 monthly revenue. You proudly work here.
Now you have to pay the barista (unless ChatGPT is doing it haha? Nope..)
The barista is requesting $5000 a month.
Each cheesecake costs the cheesecake maker $2.5 ($2.5 × 100 x 30 = $7500).
The monthly cost of running your bakery, including power, is about $5000.
Assume no extra charges. Your operating costs are $17,500.
Just $15,000? You have income but no profit. You might make money selling coffee with your cheesecake next month.
Is losing money bad? You're broke. Losing money. It's bad for financial statements.
It's almost a business ultimatum. Most startups fail. Amazon took nine years.
I'm reading Amazon Unbound: Jeff Bezos and the Creation of a Global Empire to comprehend how a company has a $1 trillion market cap.
Many things made Amazon big. The book claims that Bezos and Amazon kept a specific product secret for a long period.
Clouds above the bald head.
In 2006, Bezos started a cloud computing initiative. They believed many firms like Snapchat would pay for reliable servers.
In 2006, cloud computing was not what it is today. I'll simplify. 2006 had no iPhone.
Bezos invested in Amazon Web Services (AWS) without disclosing its revenue. That's permitted till a certain degree.
Google and Microsoft would realize Amazon is heavily investing in this market and worry.
Bezos anticipated high demand for this product. Microsoft built its cloud in 2010, and Google in 2008.
If you managed Google or Microsoft, you wouldn't know how much Amazon makes from their cloud computing service. It's enough. Yet, Amazon is an internet store, so they'll focus on that.
All but Bezos were wrong.
Time to come clean now.
They revealed AWS revenue in 2015. Two things were apparent:
Bezos made the proper decision to bet on the cloud and keep it a secret.
In this race, Amazon is in the lead.
They continued. Let me list some AWS users today.
Netflix
Airbnb
Twitch
More. Amazon was unprofitable for nine years, remember? This article's main graph.
AWS accounted for 74% of Amazon's profit in 2021. This 74% might not exist if they hadn't invested in AWS.
Bring this with you home.
Amazon predated AWS. Yet, it helped the giant reach $1 trillion. Bezos' secrecy? Perhaps, until a time machine is invented (they might host the time machine software on AWS, though.)
Without AWS, Amazon would have been profitable but unimpressive. They may have invested in anything else that would have returned more (like crypto? No? Ok.)
Bezos has business flaws. His success. His failures include:
introducing the Fire Phone and suffering a $170 million loss.
Amazon's failure in China In 2011, Amazon had a about 15% market share in China. 2019 saw a decrease of about 1%.
not offering a higher price to persuade the creator of Netflix to sell the company to him. He offered a rather reasonable $15 million in his proposal. But what if he had offered $30 million instead (Amazon had over $100 million in revenue at the time)? He might have owned Netflix, which has a $156 billion market valuation (and saved billions rather than invest in Amazon Prime Video).
Some he could control. Some were uncontrollable. Nonetheless, every action he made in the foregoing circumstances led him to invest in AWS.

Farhad Malik
3 years ago
How This Python Script Makes Me Money Every Day
Starting a passive income stream with data science and programming
My website is fresh. But how do I monetize it?
Creating a passive-income website is difficult. Advertise first. But what useful are ads without traffic?
Let’s Generate Traffic And Put Our Programming Skills To Use
SEO boosts traffic (Search Engine Optimisation). Traffic generation is complex. Keywords matter more than text, URL, photos, etc.
My Python skills helped here. I wanted to find relevant, Google-trending keywords (tags) for my topic.
First The Code
I wrote the script below here.
import re
from string import punctuation
import nltk
from nltk import TreebankWordTokenizer, sent_tokenize
from nltk.corpus import stopwords
class KeywordsGenerator:
def __init__(self, pytrends):
self._pytrends = pytrends
def generate_tags(self, file_path, top_words=30):
file_text = self._get_file_contents(file_path)
clean_text = self._remove_noise(file_text)
top_words = self._get_top_words(clean_text, top_words)
suggestions = []
for top_word in top_words:
suggestions.extend(self.get_suggestions(top_word))
suggestions.extend(top_words)
tags = self._clean_tokens(suggestions)
return ",".join(list(set(tags)))
def _remove_noise(self, text):
#1. Convert Text To Lowercase and remove numbers
lower_case_text = str.lower(text)
just_text = re.sub(r'\d+', '', lower_case_text)
#2. Tokenise Paragraphs To words
list = sent_tokenize(just_text)
tokenizer = TreebankWordTokenizer()
tokens = tokenizer.tokenize(just_text)
#3. Clean text
clean = self._clean_tokens(tokens)
return clean
def _clean_tokens(self, tokens):
clean_words = [w for w in tokens if w not in punctuation]
stopwords_to_remove = stopwords.words('english')
clean = [w for w in clean_words if w not in stopwords_to_remove and not w.isnumeric()]
return clean
def get_suggestions(self, keyword):
print(f'Searching pytrends for {keyword}')
result = []
self._pytrends.build_payload([keyword], cat=0, timeframe='today 12-m')
data = self._pytrends.related_queries()[keyword]['top']
if data is None or data.values is None:
return result
result.extend([x[0] for x in data.values.tolist()][:2])
return result
def _get_file_contents(self, file_path):
return open(file_path, "r", encoding='utf-8',errors='ignore').read()
def _get_top_words(self, words, top):
counts = dict()
for word in words:
if word in counts:
counts[word] += 1
else:
counts[word] = 1
return list({k: v for k, v in sorted(counts.items(), key=lambda item: item[1])}.keys())[:top]
if __name__ == "1__main__":
from pytrends.request import TrendReq
nltk.download('punkt')
nltk.download('stopwords')
pytrends = TrendReq(hl='en-GB', tz=360)
tags = KeywordsGenerator(pytrends)\
.generate_tags('text_file.txt')
print(tags)Then The Dependencies
This script requires:
nltk==3.7
pytrends==4.8.0Analysis of the Script
I copy and paste my article into text file.txt, and the code returns the keywords as a comma-separated string.
To achieve this:
A class I made is called KeywordsGenerator.
This class has a function:
generate_tagsThe function
generate_tagsperforms the following tasks:
retrieves text file contents
uses NLP to clean the text by tokenizing sentences into words, removing punctuation, and other elements.
identifies the most frequent words that are relevant.
The
pytrendsAPI is then used to retrieve related phrases that are trending for each word from Google.finally adds a comma to the end of the word list.
4. I then use the keywords and paste them into the SEO area of my website.
These terms are trending on Google and relevant to my topic. My site's rankings and traffic have improved since I added new keywords. This little script puts our knowledge to work. I shared the script in case anyone faces similar issues.
I hope it helps readers sell their work.

Duane Michael
2 years ago
Don't Fall Behind: 7 Subjects You Must Understand to Keep Up with Technology
As technology develops, you should stay up to date
You don't want to fall behind, do you? This post covers 7 tech-related things you should know.
You'll learn how to operate your computer (and other electronic devices) like an expert and how to leverage the Internet and social media to create your brand and business. Read on to stay relevant in today's tech-driven environment.
You must learn how to code.
Future-language is coding. It's how we and computers talk. Learn coding to keep ahead.
Try Codecademy or Code School. There are also numerous free courses like Coursera or Udacity, but they take a long time and aren't necessarily self-paced, so it can be challenging to find the time.
Artificial intelligence (AI) will transform all jobs.
Our skillsets must adapt with technology. AI is a must-know topic. AI will revolutionize every employment due to advances in machine learning.
Here are seven AI subjects you must know.
What is artificial intelligence?
How does artificial intelligence work?
What are some examples of AI applications?
How can I use artificial intelligence in my day-to-day life?
What jobs have a high chance of being replaced by artificial intelligence and how can I prepare for this?
Can machines replace humans? What would happen if they did?
How can we manage the social impact of artificial intelligence and automation on human society and individual people?
Blockchain Is Changing the Future
Few of us know how Bitcoin and blockchain technology function or what impact they will have on our lives. Blockchain offers safe, transparent, tamper-proof transactions.
It may alter everything from business to voting. Seven must-know blockchain topics:
Describe blockchain.
How does the blockchain function?
What advantages does blockchain offer?
What possible uses for blockchain are there?
What are the dangers of blockchain technology?
What are my options for using blockchain technology?
What does blockchain technology's future hold?
Cryptocurrencies are here to stay
Cryptocurrencies employ cryptography to safeguard transactions and manage unit creation. Decentralized cryptocurrencies aren't controlled by governments or financial institutions.
Bitcoin, the first cryptocurrency, was launched in 2009. Cryptocurrencies can be bought and sold on decentralized exchanges.
Bitcoin is here to stay.
Bitcoin isn't a fad, despite what some say. Since 2009, Bitcoin's popularity has grown. Bitcoin is worth learning about now. Since 2009, Bitcoin has developed steadily.
With other cryptocurrencies emerging, many people are wondering if Bitcoin still has a bright future. Curiosity is natural. Millions of individuals hope their Bitcoin investments will pay off since they're popular now.
Thankfully, they will. Bitcoin is still running strong a decade after its birth. Here's why.
The Internet of Things (IoT) is no longer just a trendy term.
IoT consists of internet-connected physical items. These items can share data. IoT is young but developing fast.
20 billion IoT-connected devices are expected by 2023. So much data! All IT teams must keep up with quickly expanding technologies. Four must-know IoT topics:
Recognize the fundamentals: Priorities first! Before diving into more technical lingo, you should have a fundamental understanding of what an IoT system is. Before exploring how something works, it's crucial to understand what you're working with.
Recognize Security: Security does not stand still, even as technology advances at a dizzying pace. As IT professionals, it is our duty to be aware of the ways in which our systems are susceptible to intrusion and to ensure that the necessary precautions are taken to protect them.
Be able to discuss cloud computing: The cloud has seen various modifications over the past several years once again. The use of cloud computing is also continually changing. Knowing what kind of cloud computing your firm or clients utilize will enable you to make the appropriate recommendations.
Bring Your Own Device (BYOD)/Mobile Device Management (MDM) is a topic worth discussing (MDM). The ability of BYOD and MDM rules to lower expenses while boosting productivity among employees who use these services responsibly is a major factor in their continued growth in popularity.
IoT Security is key
As more gadgets connect, they must be secure. IoT security includes securing devices and encrypting data. Seven IoT security must-knows:
fundamental security ideas
Authorization and identification
Cryptography
electronic certificates
electronic signatures
Private key encryption
Public key encryption
Final Thoughts
With so much going on in the globe, it can be hard to stay up with technology. We've produced a list of seven tech must-knows.
