How a $300K Bored Ape Yacht Club NFT was accidentally sold for $3K
The Bored Ape Yacht Club is one of the most prestigious NFT collections in the world. A collection of 10,000 NFTs, each depicting an ape with different traits and visual attributes, Jimmy Fallon, Steph Curry and Post Malone are among their star-studded owners. Right now the price of entry is 52 ether, or $210,000.
Which is why it's so painful to see that someone accidentally sold their Bored Ape NFT for $3,066.
Unusual trades are often a sign of funny business, as in the case of the person who spent $530 million to buy an NFT from themselves. In Saturday's case, the cause was a simple, devastating "fat-finger error." That's when people make a trade online for the wrong thing, or for the wrong amount. Here the owner, real name Max or username maxnaut, meant to list his Bored Ape for 75 ether, or around $300,000. Instead he accidentally listed it for 0.75. One hundredth the intended price.
It was bought instantaneously. The buyer paid an extra $34,000 to speed up the transaction, ensuring no one could snap it up before them. The Bored Ape was then promptly listed for $248,000. The transaction appears to have been done by a bot, which can be coded to immediately buy NFTs listed below a certain price on behalf of their owners in order to take advantage of these exact situations.
"How'd it happen? A lapse of concentration I guess," Max told me. "I list a lot of items every day and just wasn't paying attention properly. I instantly saw the error as my finger clicked the mouse but a bot sent a transaction with over 8 eth [$34,000] of gas fees so it was instantly sniped before I could click cancel, and just like that, $250k was gone."
"And here within the beauty of the Blockchain you can see that it is both honest and unforgiving," he added.
Fat finger trades happen sporadically in traditional finance -- like the Japanese trader who almost bought 57% of Toyota's stock in 2014 -- but most financial institutions will stop those transactions if alerted quickly enough. Since cryptocurrency and NFTs are designed to be decentralized, you essentially have to rely on the goodwill of the buyer to reverse the transaction.
Fat finger errors in cryptocurrency trades have made many a headline over the past few years. Back in 2019, the company behind Tether, a cryptocurrency pegged to the US dollar, nearly doubled its own coin supply when it accidentally created $5 billion-worth of new coins. In March, BlockFi meant to send 700 Gemini Dollars to a set of customers, worth roughly $1 each, but mistakenly sent out millions of dollars worth of bitcoin instead. Last month a company erroneously paid a $24 million fee on a $100,000 transaction.
Similar incidents are increasingly being seen in NFTs, now that many collections have accumulated in market value over the past year. Last month someone tried selling a CryptoPunk NFT for $19 million, but accidentally listed it for $19,000 instead. Back in August, someone fat finger listed their Bored Ape for $26,000, an error that someone else immediately capitalized on. The original owner offered $50,000 to the buyer to return the Bored Ape -- but instead the opportunistic buyer sold it for the then-market price of $150,000.
"The industry is so new, bad things are going to happen whether it's your fault or the tech," Max said. "Once you no longer have control of the outcome, forget and move on."
The Bored Ape Yacht Club launched back in April 2021, with 10,000 NFTs being sold for 0.08 ether each -- about $190 at the time. While NFTs are often associated with individual digital art pieces, collections like the Bored Ape Yacht Club, which allow owners to flaunt their NFTs by using them as profile pictures on social media, are becoming increasingly prevalent. The Bored Ape Yacht Club has since become the second biggest NFT collection in the world, second only to CryptoPunks, which launched in 2017 and is considered the "original" NFT collection.
More on Web3 & Crypto
Scott Hickmann
3 years ago
YouTube
This is a YouTube video:
Vitalik
3 years ago
An approximate introduction to how zk-SNARKs are possible (part 2)
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? But it turns out that there is a clever solution.
Polynomials
Polynomials are a special class of algebraic expressions of the form:
- x+5
- x^4
- x^3+3x^2+3x+1
- 628x^{271}+318x^{270}+530x^{269}+…+69x+381
i.e. they are a sum of any (finite!) number of terms of the form cx^k
There are many things that are fascinating about polynomials. But here we are going to zoom in on a particular one: polynomials are a single mathematical object that can contain an unbounded amount of information (think of them as a list of integers and this is obvious). The fourth example above contained 816 digits of tau, and one can easily imagine a polynomial that contains far more.
Furthermore, a single equation between polynomials can represent an unbounded number of equations between numbers. For example, consider the equation A(x)+ B(x) = C(x). If this equation is true, then it's also true that:
- A(0)+B(0)=C(0)
- A(1)+B(1)=C(1)
- A(2)+B(2)=C(2)
- A(3)+B(3)=C(3)
And so on for every possible coordinate. You can even construct polynomials to deliberately represent sets of numbers so you can check many equations all at once. For example, suppose that you wanted to check:
- 12+1=13
- 10+8=18
- 15+8=23
- 15+13=28
You can use a procedure called Lagrange interpolation to construct polynomials A(x) that give (12,10,15,15) as outputs at some specific set of coordinates (eg. (0,1,2,3)), B(x) the outputs (1,8,8,13) on thos same coordinates, and so forth. In fact, here are the polynomials:
- A(x)=-2x^3+\frac{19}{2}x^2-\frac{19}{2}x+12
- B(x)=2x^3-\frac{19}{2}x^2+\frac{29}{2}x+1
- C(x)=5x+13
Checking the equation A(x)+B(x)=C(x) with these polynomials checks all four above equations at the same time.
Comparing a polynomial to itself
You can even check relationships between a large number of adjacent evaluations of the same polynomial using a simple polynomial equation. This is slightly more advanced. Suppose that you want to check that, for a given polynomial F, F(x+2)=F(x)+F(x+1) with the integer range {0,1…89} (so if you also check F(0)=F(1)=1, then F(100) would be the 100th Fibonacci number)
As polynomials, F(x+2)-F(x+1)-F(x) would not be exactly zero, as it could give arbitrary answers outside the range x={0,1…98}. But we can do something clever. In general, there is a rule that if a polynomial P is zero across some set S=\{x_1,x_2…x_n\} then it can be expressed as P(x)=Z(x)*H(x), where Z(x)=(x-x_1)*(x-x_2)*…*(x-x_n) and H(x) is also a polynomial. In other words, any polynomial that equals zero across some set is a (polynomial) multiple of the simplest (lowest-degree) polynomial that equals zero across that same set.
Why is this the case? It is a nice corollary of polynomial long division: the factor theorem. We know that, when dividing P(x) by Z(x), we will get a quotient Q(x) and a remainder R(x) is strictly less than that of Z(x). Since we know that P is zero on all of S, it means that R has to be zero on all of S as well. So we can simply compute R(x) via polynomial interpolation, since it's a polynomial of degree at most n-1 and we know n values (the zeros at S). Interpolating a polynomial with all zeroes gives the zero polynomial, thus R(x)=0 and H(x)=Q(x).
Going back to our example, if we have a polynomial F that encodes Fibonacci numbers (so F(x+2)=F(x)+F(x+1) across x=\{0,1…98\}), then I can convince you that F actually satisfies this condition by proving that the polynomial P(x)=F(x+2)-F(x+1)-F(x) is zero over that range, by giving you the quotient:
H(x)=\frac{F(x+2)-F(x+1)-F(x)}{Z(x)}
Where Z(x) = (x-0)*(x-1)*…*(x-98).
You can calculate Z(x) yourself (ideally you would have it precomputed), check the equation, and if the check passes then F(x) satisfies the condition!
Now, step back and notice what we did here. We converted a 100-step-long computation into a single equation with polynomials. Of course, proving the N'th Fibonacci number is not an especially useful task, especially since Fibonacci numbers have a closed form. But you can use exactly the same basic technique, just with some extra polynomials and some more complicated equations, to encode arbitrary computations with an arbitrarily large number of steps.
see part 3
Percy Bolmér
2 years ago
Ethereum No Longer Consumes A Medium-Sized Country's Electricity To Run
The Merge cut Ethereum's energy use by 99.5%.
The Crypto community celebrated on September 15, 2022. This day, Ethereum Merged. The entire blockchain successfully merged with the Beacon chain, and it was so smooth you barely noticed.
Many have waited, dreaded, and longed for this day.
Some investors feared the network would break down, while others envisioned a seamless merging.
Speculators predict a successful Merge will lead investors to Ethereum. This could boost Ethereum's popularity.
What Has Changed Since The Merge
The merging transitions Ethereum mainnet from PoW to PoS.
PoW sends a mathematical riddle to computers worldwide (miners). First miner to solve puzzle updates blockchain and is rewarded.
The puzzles sent are power-intensive to solve, so mining requires a lot of electricity. It's sent to every miner competing to solve it, requiring duplicate computation.
PoS allows investors to stake their coins to validate a new transaction. Instead of validating a whole block, you validate a transaction and get the fees.
You can validate instead of mine. A validator stakes 32 Ethereum. After staking, the validator can validate future blocks.
Once a validator validates a block, it's sent to a randomly selected group of other validators. This group verifies that a validator is not malicious and doesn't validate fake blocks.
This way, only one computer needs to solve or validate the transaction, instead of all miners. The validated block must be approved by a small group of validators, causing duplicate computation.
PoS is more secure because validating fake blocks results in slashing. You lose your bet tokens. If a validator signs a bad block or double-signs conflicting blocks, their ETH is burned.
Theoretically, Ethereum has one block every 12 seconds, so a validator forging a block risks burning 1 Ethereum for 12 seconds of transactions. This makes mistakes expensive and risky.
What Impact Does This Have On Energy Use?
Cryptocurrency is a natural calamity, sucking electricity and eating away at the earth one transaction at a time.
Many don't know the environmental impact of cryptocurrencies, yet it's tremendous.
A single Ethereum transaction used to use 200 kWh and leave a large carbon imprint. This update reduces global energy use by 0.2%.
Ethereum will submit a challenge to one validator, and that validator will forward it to randomly selected other validators who accept it.
This reduces the needed computing power.
They expect a 99.5% reduction, therefore a single transaction should cost 1 kWh.
Carbon footprint is 0.58 kgCO2, or 1,235 VISA transactions.
This is a big Ethereum blockchain update.
I love cryptocurrency and Mother Earth.
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Mangu Solutions
2 years ago
Growing a New App to $15K/mo in 6 Months [SaaS Case Study]
Discover How We Used Facebook Ads to Grow a New Mobile App from $0 to $15K MRR in Just 6 Months and Our Strategy to Hit $100K a Month.
Our client introduced a mobile app for Poshmark resellers in December and wanted as many to experience it and subscribe to the monthly plan.
An Error We Committed
We initiated a Facebook ad campaign with a "awareness" goal, not "installs." This sent them to a landing page that linked to the iPhone App Store and Android Play Store. Smart, right?
We got some installs, but we couldn't tell how many came from the ad versus organic/other channels because the objective we chose only reported landing page clicks, not app installs.
We didn't know which interest groups/audiences had the best cost per install (CPI) to optimize and scale our budget.
After spending $700 without adequate data (installs and trials report), we stopped the campaign and worked with our client's app developer to set up app events tracking.
This allowed us to create an installs campaign and track installs, trials, and purchases (in some cases).
Finding a Successful Audience
Once we knew what ad sets brought in what installs at what cost, we began optimizing and testing other interest groups and audiences, growing the profitable low CPI ones and eliminating the high CPI ones.
We did all our audience testing using an ABO campaign (Ad Set Budget Optimization), spending $10 to $30 on each ad set for three days and optimizing afterward. All ad sets under $30 were moved to a CBO campaign (Campaign Budget Optimization).
We let Facebook's AI decide how much to spend on each ad set, usually the one most likely to convert at the lowest cost.
If the CBO campaign maintains a nice CPI, we keep increasing the budget by $50 every few days or duplicating it sometimes in order to double the budget. This is how we've scaled to $400/day profitably.
Finding Successful Creatives
Per campaign, we tested 2-6 images/videos. Same ad copy and CTA. There was no clear winner because some images did better with some interest groups.
The image above with mail packages, for example, got us a cheap CPI of $9.71 from our Goodwill Stores interest group but, a high $48 CPI from our lookalike audience. Once we had statistically significant data, we turned off the high-cost ad.
New marketers who are just discovering A/B testing may assume it's black and white — winner and loser. However, Facebook ads' machine learning and reporting has gotten so sophisticated that it's hard to call a creative a flat-out loser, but rather a 'bad fit' for some audiences, and perfect for others.
You can see how each creative performs across age groups and optimize.
How Many Installs Did It Take Us to Earn $15K Per Month?
Six months after paying $25K, we got 1,940 app installs, 681 free trials, and 522 $30 monthly subscriptions. 522 * $30 gives us $15,660 in monthly recurring revenue (MRR).
Next, what? $100K per month
The conversation above is with the app's owner. We got on a 30-minute call where I shared how I plan to get the app to be making $100K a month like I’ve done for other businesses.
Reverse Engineering $100K
Formula:
For $100K/month, we need 3,334 people to pay $30/month. 522 people pay that. We need 2,812 more paid users.
522 paid users from 1,940 installs is a 27% conversion rate. To hit $100K/month, we need 10,415 more installs. Assuming...
With a $400 daily ad spend, we average 40 installs per day. This means that if everything stays the same, it would take us 260 days (around 9 months) to get to $100K a month (MRR).
Conclusion
You must market your goods to reach your income objective (without waiting forever). Paid ads is the way to go if you hate knocking on doors or irritating friends and family (who aren’t scalable anyways).
You must also test and optimize different angles, audiences, interest groups, and creatives.
Simon Ash
2 years ago
The Three Most Effective Questions for Ongoing Development
The Traffic Light Approach to Reviewing Personal, Team and Project Development
What needs improvement? If you want to improve, you need to practice your sport, musical instrument, habit, or work project. You need to assess your progress.
Continuous improvement is the foundation of focused practice and a growth mentality. Not just individually. High-performing teams pursue improvement. Right? Why is it hard?
As a leadership coach, senior manager, and high-level athlete, I've found three key questions that may unlock high performance in individuals and teams.
Problems with Reviews
Reviewing and improving performance is crucial, however I hate seeing review sessions in my diary. I rarely respond to questionnaire pop-ups or emails. Why?
Time constrains. Requests to fill out questionnaires often state they will take 10–15 minutes, but I can think of a million other things to do with that time. Next, review overload. Businesses can easily request comments online. No matter what you buy, someone will ask for your opinion. This bombardment might make feedback seem bad, which is bad.
The problem is that we might feel that way about important things like personal growth and work performance. Managers and team leaders face a greater challenge.
When to Conduct a Review
We must be wise about reviewing things that matter to us. Timing and duration matter. Reviewing the experience as quickly as possible preserves information and sentiments. Time must be brief. The review's importance and size will determine its length. We might only take a few seconds to review our morning coffee, but we might require more time for that six-month work project.
These post-event reviews should be supplemented by periodic reflection. Journaling can help with daily reflections, but I also like to undertake personal reviews every six months on vacation or at a retreat.
As an employee or line manager, you don't want to wait a year for a performance assessment. Little and frequently is best, with a more formal and in-depth assessment (typically with a written report) in 6 and 12 months.
The Easiest Method to Conduct a Review Session
I follow Einstein's review process:
“Make things as simple as possible but no simpler.”
Thus, it should be brief but deliver the necessary feedback. Quality critique is hard to receive if the process is overly complicated or long.
I have led or participated in many review processes, from strategic overhauls of big organizations to personal goal coaching. Three key questions guide the process at either end:
What ought to stop being done?
What should we do going forward?
What should we do first?
Following the Rule of 3, I compare it to traffic lights. Red, amber, and green lights:
Red What ought should we stop?
Amber What ought to we keep up?
Green Where should we begin?
This approach is easy to understand and self-explanatory, however below are some examples under each area.
Red What ought should we stop?
As a team or individually, we must stop doing things to improve.
Sometimes they're bad. If we want to lose weight, we should avoid sweets. If a team culture is bad, we may need to stop unpleasant behavior like gossiping instead of having difficult conversations.
Not all things we should stop are wrong. Time matters. Since it is finite, we sometimes have to stop nice things to focus on the most important. Good to Great author Jim Collins famously said:
“Don’t let the good be the enemy of the great.”
Prioritizing requires this idea. Thus, decide what to stop to prioritize.
Amber What ought to we keep up?
Should we continue with the amber light? It helps us decide what to keep doing during review. Many items fall into this category, so focus on those that make the most progress.
Which activities have the most impact? Which behaviors create the best culture? Success-building habits?
Use these questions to find positive momentum. These are the fly-wheel motions, according to Jim Collins. The Compound Effect author Darren Hardy says:
“Consistency is the key to achieving and maintaining momentum.”
What can you do consistently to reach your goal?
Green Where should we begin?
Finally, green lights indicate new beginnings. Red/amber difficulties may be involved. Stopping a red issue may give you more time to do something helpful (in the amber).
This green space inspires creativity. Kolbs learning cycle requires active exploration to progress. Thus, it's crucial to think of new approaches, try them out, and fail if required.
This notion underpins lean start-build, up's measure, learn approach and agile's trying, testing, and reviewing. Try new things until you find what works. Thomas Edison, the lighting legend, exclaimed:
“There is a way to do it better — find it!”
Failure is acceptable, but if you want to fail forward, look back on what you've done.
John Maxwell concurred with Edison:
“Fail early, fail often, but always fail forward”
A good review procedure lets us accomplish that. To avoid failure, we must act, experiment, and reflect.
Use the traffic light system to prioritize queries. Ask:
Red What needs to stop?
Amber What should continue to occur?
Green What might be initiated?
Take a moment to reflect on your day. Check your priorities with these three questions. Even if merely to confirm your direction, it's a terrific exercise!
Will Lockett
2 years ago
The world will be changed by this molten salt battery.
Four times the energy density and a fraction of lithium-cost ion's
As the globe abandons fossil fuels, batteries become more important. EVs, solar, wind, tidal, wave, and even local energy grids will use them. We need a battery revolution since our present batteries are big, expensive, and detrimental to the environment. A recent publication describes a battery that solves these problems. But will it be enough?
Sodium-sulfur molten salt battery. It has existed for a long time and uses molten salt as an electrolyte (read more about molten salt batteries here). These batteries are cheaper, safer, and more environmentally friendly because they use less eco-damaging materials, are non-toxic, and are non-flammable.
Previous molten salt batteries used aluminium-sulphur chemistries, which had a low energy density and required high temperatures to keep the salt liquid. This one uses a revolutionary sodium-sulphur chemistry and a room-temperature-melting salt, making it more useful, affordable, and eco-friendly. To investigate this, researchers constructed a button-cell prototype and tested it.
First, the battery was 1,017 mAh/g. This battery is four times as energy dense as high-density lithium-ion batteries (250 mAh/g).
No one knows how much this battery would cost. A more expensive molten-salt battery costs $15 per kWh. Current lithium-ion batteries cost $132/kWh. If this new molten salt battery costs the same as present cells, it will be 90% cheaper.
This room-temperature molten salt battery could be utilized in an EV. Cold-weather heaters just need a modest backup battery.
The ultimate EV battery? If used in a Tesla Model S, you could install four times the capacity with no weight gain, offering a 1,620-mile range. This huge battery pack would cost less than Tesla's. This battery would nearly perfect EVs.
Or would it?
The battery's capacity declined by 50% after 1,000 charge cycles. This means that our hypothetical Model S would suffer this decline after 1.6 million miles, but for more cheap vehicles that use smaller packs, this would be too short. This test cell wasn't supposed to last long, so this is shocking. Future versions of this cell could be modified to live longer.
This affordable and eco-friendly cell is best employed as a grid-storage battery for renewable energy. Its safety and affordable price outweigh its short lifespan. Because this battery is made of easily accessible materials, it may be utilized to boost grid-storage capacity without causing supply chain concerns or EV battery prices to skyrocket.
Researchers are designing a bigger pouch cell (like those in phones and laptops) for this purpose. The battery revolution we need could be near. Let’s just hope it isn’t too late.