More on Current Events
Will Lockett
3 years ago
Russia's nukes may be useless
Russia's nuclear threat may be nullified by physics.
Putin seems nostalgic and wants to relive the Cold War. He's started a deadly war to reclaim the old Soviet state of Ukraine and is threatening the West with nuclear war. NATO can't risk starting a global nuclear war that could wipe out humanity to support Ukraine's independence as much as they want to. Fortunately, nuclear physics may have rendered Putin's nuclear weapons useless. However? How will Ukraine and NATO react?
To understand why Russia's nuclear weapons may be ineffective, we must first know what kind they are.
Russia has the world's largest nuclear arsenal, with 4,447 strategic and 1,912 tactical weapons (all of which are ready to be rolled out quickly). The difference between these two weapons is small, but it affects their use and logistics. Strategic nuclear weapons are ICBMs designed to destroy a city across the globe. Russia's ICBMs have many designs and a yield of 300–800 kilotonnes. 300 kilotonnes can destroy Washington. Tactical nuclear weapons are smaller and can be fired from artillery guns or small truck-mounted missile launchers, giving them a 1,500 km range. Instead of destroying a distant city, they are designed to eliminate specific positions, bases, or military infrastructure. They produce 1–50 kilotonnes.
These two nuclear weapons use different nuclear reactions. Pure fission bombs are compact enough to fit in a shell or small missile. All early nuclear weapons used this design for their fission bombs. This technology is inefficient for bombs over 50 kilotonnes. Larger bombs are thermonuclear. Thermonuclear weapons use a small fission bomb to compress and heat a hydrogen capsule, which undergoes fusion and releases far more energy than ignition fission reactions, allowing for effective giant bombs.
Here's Russia's issue.
A thermonuclear bomb needs deuterium (hydrogen with one neutron) and tritium (hydrogen with two neutrons). Because these two isotopes fuse at lower energies than others, the bomb works. One problem. Tritium is highly radioactive, with a half-life of only 12.5 years, and must be artificially made.
Tritium is made by irradiating lithium in nuclear reactors and extracting the gas. Tritium is one of the most expensive materials ever made, at $30,000 per gram.
Why does this affect Putin's nukes?
Thermonuclear weapons need tritium. Tritium decays quickly, so they must be regularly refilled at great cost, which Russia may struggle to do.
Russia has a smaller economy than New York, yet they are running an invasion, fending off international sanctions, and refining tritium for 4,447 thermonuclear weapons.
The Russian military is underfunded. Because the state can't afford it, Russian troops must buy their own body armor. Arguably, Putin cares more about the Ukraine conflict than maintaining his nuclear deterrent. Putin will likely lose power if he loses the Ukraine war.
It's possible that Putin halted tritium production and refueling to save money for Ukraine. His threats of nuclear attacks and escalating nuclear war may be a bluff.
This doesn't help Ukraine, sadly. Russia's tactical nuclear weapons don't need expensive refueling and will help with the invasion. So Ukraine still risks a nuclear attack. The bomb that destroyed Hiroshima was 15 kilotonnes, and Russia's tactical Iskander-K nuclear missile has a 50-kiloton yield. Even "little" bombs are deadly.
We can't guarantee it's happening in Russia. Putin may prioritize tritium. He knows the power of nuclear deterrence. Russia may have enough tritium for this conflict. Stockpiling a material with a short shelf life is unlikely, though.
This means that Russia's most powerful weapons may be nearly useless, but they may still be deadly. If true, this could allow NATO to offer full support to Ukraine and push the Russian tyrant back where he belongs. If Putin withholds funds from his crumbling military to maintain his nuclear deterrent, he may be willing to sink the ship with him. Let's hope the former.
Steve QJ
3 years ago
Putin's War On Reality
The dictator's playbook.
Stalin's successor, Nikita Khrushchev, delivered a speech titled "On The Cult Of Personality And Its Consequences" in 1956, three years after Stalin’s death.
It was Stalin's grave abuse of power that caused untold harm to our party.
Stalin acted not by persuasion, explanation, or patient cooperation, but by imposing his ideas and demanding absolute obedience. […]
See where Stalin's mania for greatness led? He had lost all sense of reality.
The speech, which was never made public, shook the Soviet Union and the Soviet Bloc. After Stalin's "cult of personality" was exposed as a lie, only reality remained.
As I've watched the nightmare unfold in Ukraine, I'm reminded of that question. Primarily by Putin's repeated denials.
His odd claim that Ukraine is run by drug addicts and Nazis (especially strange given that Volodymyr Zelenskyy, the Ukrainian president, is Jewish). Others attempt to portray Russia as liberators rather than occupiers. For example, he portrays Luhansk and Donetsk as plucky, newly independent states when they have been totalitarian statelets for 8 years.
Putin seemed to have lost all sense of reality.
Maybe that's why his remarks to an oligarchs' gathering stood out:
Everything is a desperate measure. They gave us no choice. We couldn't do anything about their security risks. […] They could have put the country in jeopardy.
This is almost certainly true from Putin's perspective. Even for Putin, a military invasion seems unlikely. So, what exactly is putting Russia's security in jeopardy? How could Ukraine's independence endanger Russia's existence?
The truth is the only thing that truly terrifies leaders like these.
Trump, the president of “alternative facts,” "and “fake news” praised Putin's fabricated justifications for the Ukraine invasion. Russia tightened news censorship as news of their losses came in. It's no accident that modern dictatorships like Russia (and China and North Korea) restrict citizens' access to information.
Controlling what people see, hear, and think is the simplest method. And Ukraine's recent efforts to join the European Union showed a country whose thoughts Putin couldn't control. With the Russian and Ukrainian peoples so close, he could not control their reality.
He appears to think this is a threat worth fighting NATO over.
It's easy to disown history's great dictators. By the magnitude of their harm. But the strategy they used is still in use today, albeit not to the same devastating effect.
The Kim dynasty in North Korea has ruled for 74 years, Putin has ruled Russia for 19 years (using loopholes and even rewriting the constitution).
“Politicians and diapers must be changed frequently,” said Mark Twain. "And for the same reason.”
When their egos are threatened, they sabre-rattle, as in Kim Jong-un and Donald Trump's famous spat about the size of their...ahem, “nuclear buttons”." Or Putin's threats of mutual destruction this weekend.
Most importantly, they have cult-like control over their followers.
When a leader whose power is built on lies feels he is losing control of the narrative, things like Trump's Jan. 6 meltdown and Putin's current actions in Ukraine are unavoidable.
Leaders who try to control their people's reality will have to die to keep the illusion alive.
Long version of this post available here
Gill Pratt
3 years ago
War's Human Cost
War's Human Cost
I didn't start crying until I was outside a McDonald's in an Olempin, Poland rest area on highway S17.
Children pick toys at a refugee center, Olempin, Poland, March 4, 2022.
Refugee children, mostly alone with their mothers, but occasionally with a gray-haired grandfather or non-Ukrainian father, were coaxed into picking a toy from boxes provided by a kind-hearted company and volunteers.
I went to Warsaw to continue my research on my family's history during the Holocaust. In light of the ongoing Ukrainian conflict, I asked former colleagues in the US Department of Defense and Intelligence Community if it was safe to travel there. They said yes, as Poland was a NATO member.
I stayed in a hotel in the Warsaw Ghetto, where 90% of my mother's family was murdered in the Holocaust. Across the street was the first Warsaw Judenrat. It was two blocks away from the apartment building my mother's family had owned and lived in, now dilapidated and empty.
Building of my great-grandfather, December 2021.
A mass grave of thousands of rocks for those killed in the Warsaw Ghetto, I didn't cry when I touched its cold walls.
Warsaw Jewish Cemetery, 200,000–300,000 graves.
Mass grave, Warsaw Jewish Cemetery.
My mother's family had two homes, one in Warszawa and the rural one was a forest and sawmill complex in Western Ukraine. For the past half-year, a local Ukrainian historian had been helping me discover faint traces of her family’s life there — in fact, he had found some people still alive who remembered the sawmill and that it belonged to my mother’s grandfather. The historian was good at his job, and we had become close.
My historian friend, December 2021, talking to a Ukrainian.
With war raging, my second trip to Warsaw took on a different mission. To see his daughter and one-year-old grandson, I drove east instead of to Ukraine. They had crossed the border shortly after the war began, leaving men behind, and were now staying with a friend on Poland's eastern border.
I entered after walking up to the house and settling with the dog. The grandson greeted me with a huge smile and the Ukrainian word for “daddy,” “Tato!” But it was clear he was awaiting his real father's arrival, and any man he met would be so tentatively named.
After a few moments, the boy realized I was only a stranger. He had musical talent, like his mother and grandfather, both piano teachers, as he danced to YouTube videos of American children's songs dubbed in Ukrainian, picking the ones he liked and crying when he didn't.
Songs chosen by my historian friend's grandson, March 4, 2022
He had enough music and began crying regardless of the song. His mother picked him up and started nursing him, saying she was worried about him. She had no idea where she would live or how she would survive outside Ukraine. She showed me her father's family history of losses in the Holocaust, which matched my own research.
After an hour of drinking tea and trying to speak of hope, I left for the 3.5-hour drive west to Warsaw.
It was unlike my drive east. It was reminiscent of the household goods-filled carts pulled by horses and people fleeing war 80 years ago.
Jewish refugees relocating, USHMM Holocaust Encyclopaedia, 1939.
The carefully chosen trinkets by children to distract them from awareness of what is really happening and the anxiety of what lies ahead, made me cry despite all my research on the Holocaust. There is no way for them to communicate with their mothers, who are worried, absent, and without their fathers.
It's easy to see war as a contest of nations' armies, weapons, and land. The most costly aspect of war is its psychological toll. My father screamed in his sleep from nightmares of his own adolescent trauma in Warsaw 80 years ago.
Survivor father studying engineering, 1961.
In the airport, I waited to return home while Ukrainian public address systems announced refugee assistance. Like at McDonald's, many mothers were alone with their children, waiting for a flight to distant relatives.
That's when I had my worst trip experience.
A woman near me, clearly a refugee, answered her phone, cried out, and began wailing.
The human cost of war descended like a hammer, and I realized that while I was going home, she never would
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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
Pen Magnet
3 years ago
Why Google Staff Doesn't Work
Sundar Pichai unveiled Simplicity Sprint at Google's latest all-hands conference.
To boost employee efficiency.
Not surprising. Few envisioned Google declaring a productivity drive.
Sunder Pichai's speech:
“There are real concerns that our productivity as a whole is not where it needs to be for the head count we have. Help me create a culture that is more mission-focused, more focused on our products, more customer focused. We should think about how we can minimize distractions and really raise the bar on both product excellence and productivity.”
The primary driver driving Google's efficiency push is:
Google's efficiency push follows 13% quarterly revenue increase. Last year in the same quarter, it was 62%.
Market newcomers may argue that the previous year's figure was fuelled by post-Covid reopening and growing consumer spending. Investors aren't convinced. A promising company like Google can't afford to drop so quickly.
Google’s quarterly revenue growth stood at 13%, against 62% in last year same quarter.
Google isn't alone. In my recent essay regarding 2025 programmers, I warned about the economic downturn's effects on FAAMG's workforce. Facebook had suspended hiring, and Microsoft had promised hefty bonuses for loyal staff.
In the same article, I predicted Google's troubles. Online advertising, especially the way Google and Facebook sell it using user data, is over.
FAAMG and 2nd rung IT companies could be the first to fall without Post-COVID revival and uncertain global geopolitics.
Google has hardly ever discussed effectiveness:
Apparently openly.
Amazon treats its employees like robots, even in software positions. It has significant turnover and a terrible reputation as a result. Because of this, it rarely loses money due to staff productivity.
Amazon trumps Google. In reality, it treats its employees poorly.
Google was the founding father of the modern-day open culture.
Larry and Sergey Google founded the IT industry's Open Culture. Silicon Valley called Google's internal democracy and transparency near anarchy. Management rarely slammed decisions on employees. Surveys and internal polls ensured everyone knew the company's direction and had a vote.
20% project allotment (weekly free time to build own project) was Google's open-secret innovation component.
After Larry and Sergey's exit in 2019, this is Google's first profitability hurdle. Only Google insiders can answer these questions.
Would Google's investors compel the company's management to adopt an Amazon-style culture where the developers are treated like circus performers?
If so, would Google follow suit?
If so, how does Google go about doing it?
Before discussing Google's likely plan, let's examine programming productivity.
What determines a programmer's productivity is simple:
How would we answer Google's questions?
As a programmer, I'm more concerned about Simplicity Sprint's aftermath than its economic catalysts.
Large organizations don't care much about quarterly and annual productivity metrics. They have 10-year product-launch plans. If something seems horrible today, it's likely due to someone's lousy judgment 5 years ago who is no longer in the blame game.
Deconstruct our main question.
How exactly do you change the culture of the firm so that productivity increases?
How can you accomplish that without affecting your capacity to profit? There are countless ways to increase output without decreasing profit.
How can you accomplish this with little to no effect on employee motivation? (While not all employers care about it, in this case we are discussing the father of the open company culture.)
How do you do it for a 10-developer IT firm that is losing money versus a 1,70,000-developer organization with a trillion-dollar valuation?
When implementing a large-scale organizational change, success must be carefully measured.
The fastest way to do something is to do it right, no matter how long it takes.
You require clearly-defined group/team/role segregation and solid pass/fail matrices to:
You can give performers rewards.
Ones that are average can be inspired to improve
Underachievers may receive assistance or, in the worst-case scenario, rehabilitation
As a 20-year programmer, I associate productivity with greatness.
Doing something well, no matter how long it takes, is the fastest way to do it.
Let's discuss a programmer's productivity.
Why productivity is a strange term in programming:
Productivity is work per unit of time.
Money=time This is an economic proverb. More hours worked, more pay. Longer projects cost more.
As a buyer, you desire a quick supply. As a business owner, you want employees who perform at full capacity, creating more products to transport and boosting your profits.
All economic matrices encourage production because of our obsession with it. Productivity is the only organic way a nation may increase its GDP.
Time is money — is not just a proverb, but an economical fact.
Applying the same productivity theory to programming gets problematic. An automating computer. Its capacity depends on the software its master writes.
Today, a sophisticated program can process a billion records in a few hours. Creating one takes a competent coder and the necessary infrastructure. Learning, designing, coding, testing, and iterations take time.
Programming productivity isn't linear, unlike manufacturing and maintenance.
Average programmers produce code every day yet miss deadlines. Expert programmers go days without coding. End of sprint, they often surprise themselves by delivering fully working solutions.
Reversing the programming duties has no effect. Experts aren't needed for productivity.
These patterns remind me of an XKCD comic.
Programming productivity depends on two factors:
The capacity of the programmer and his or her command of the principles of computer science
His or her productive bursts, how often they occur, and how long they last as they engineer the answer
At some point, productivity measurement becomes Schrödinger’s cat.
Product companies measure productivity using use cases, classes, functions, or LOCs (lines of code). In days of data-rich source control systems, programmers' merge requests and/or commits are the most preferred yardstick. Companies assess productivity by tickets closed.
Every organization eventually has trouble measuring productivity. Finer measurements create more chaos. Every measure compares apples to oranges (or worse, apples with aircraft.) On top of the measuring overhead, the endeavor causes tremendous and unnecessary stress on teams, lowering their productivity and defeating its purpose.
Macro productivity measurements make sense. Amazon's factory-era management has done it, but at great cost.
Google can pull it off if it wants to.
What Google meant in reality when it said that employee productivity has decreased:
When Google considers its employees unproductive, it doesn't mean they don't complete enough work in the allotted period.
They can't multiply their work's influence over time.
Programmers who produce excellent modules or products are unsure on how to use them.
The best data scientists are unable to add the proper parameters in their models.
Despite having a great product backlog, managers struggle to recruit resources with the necessary skills.
Product designers who frequently develop and A/B test newer designs are unaware of why measures are inaccurate or whether they have already reached the saturation point.
Most ignorant: All of the aforementioned positions are aware of what to do with their deliverables, but neither their supervisors nor Google itself have given them sufficient authority.
So, Google employees aren't productive.
How to fix it?
Business analysis: White suits introducing novel items can interact with customers from all regions. Track analytics events proactively, especially the infrequent ones.
SOLID, DRY, TEST, and AUTOMATION: Do less + reuse. Use boilerplate code creation. If something already exists, don't implement it yourself.
Build features-building capabilities: N features are created by average programmers in N hours. An endless number of features can be built by average programmers thanks to the fact that expert programmers can produce 1 capability in N hours.
Work on projects that will have a positive impact: Use the same algorithm to search for images on YouTube rather than the Mars surface.
Avoid tasks that can only be measured in terms of time linearity at all costs (if a task can be completed in N minutes, then M copies of the same task would cost M*N minutes).
In conclusion:
Software development isn't linear. Why should the makers be measured?
Notation for The Big O
I'm discussing a new way to quantify programmer productivity. (It applies to other professions, but that's another subject)
The Big O notation expresses the paradigm (the algorithmic performance concept programmers rot to ace their Google interview)
Google (or any large corporation) can do this.
Sort organizational roles into categories and specify their impact vs. time objectives. A CXO role's time vs. effect function, for instance, has a complexity of O(log N), meaning that if a CEO raises his or her work time by 8x, the result only increases by 3x.
Plot the influence of each employee over time using the X and Y axes, respectively.
Add a multiplier for Y-axis values to the productivity equation to make business objectives matter. (Example values: Support = 5, Utility = 7, and Innovation = 10).
Compare employee scores in comparable categories (developers vs. devs, CXOs vs. CXOs, etc.) and reward or help employees based on whether they are ahead of or behind the pack.
After measuring every employee's inventiveness, it's straightforward to help underachievers and praise achievers.
Example of a Big(O) Category:
If I ran Google (God forbid, its worst days are far off), here's how I'd classify it. You can categorize Google employees whichever you choose.
The Google interview truth:
O(1) < O(log n) < O(n) < O(n log n) < O(n^x) where all logarithmic bases are < n.
O(1): Customer service workers' hours have no impact on firm profitability or customer pleasure.
CXOs Most of their time is spent on travel, strategic meetings, parties, and/or meetings with minimal floor-level influence. They're good at launching new products but bad at pivoting without disaster. Their directions are being followed.
Devops, UX designers, testers Agile projects revolve around deployment. DevOps controls the levers. Their automation secures results in subsequent cycles.
UX/UI Designers must still prototype UI elements despite improved design tools.
All test cases are proportional to use cases/functional units, hence testers' work is O(N).
Architects Their effort improves code quality. Their right/wrong interference affects product quality and rollout decisions even after the design is set.
Core Developers Only core developers can write code and own requirements. When people understand and own their labor, the output improves dramatically. A single character error can spread undetected throughout the SDLC and cost millions.
Core devs introduce/eliminate 1000x bugs, refactoring attempts, and regression. Following our earlier hypothesis.
The fastest way to do something is to do it right, no matter how long it takes.
Conclusion:
Google is at the liberal extreme of the employee-handling spectrum
Microsoft faced an existential crisis after 2000. It didn't choose Amazon's data-driven people management to revitalize itself.
Instead, it entrusted developers. It welcomed emerging technologies and opened up to open source, something it previously opposed.
Google is too lax in its employee-handling practices. With that foundation, it can only follow Amazon, no matter how carefully.
Any attempt to redefine people's measurements will affect the organization emotionally.
The more Google compares apples to apples, the higher its chances for future rebirth.
Protos
3 years ago
Plagiarism on OpenSea: humans and computers
OpenSea, a non-fungible token (NFT) marketplace, is fighting plagiarism. A new “two-pronged” approach will aim to root out and remove copies of authentic NFTs and changes to its blue tick verified badge system will seek to enhance customer confidence.
According to a blog post, the anti-plagiarism system will use algorithmic detection of “copymints” with human reviewers to keep it in check.
Last year, NFT collectors were duped into buying flipped images of the popular BAYC collection, according to The Verge. The largest NFT marketplace had to remove its delay pay minting service due to an influx of copymints.
80% of NFTs removed by the platform were minted using its lazy minting service, which kept the digital asset off-chain until the first purchase.
NFTs copied from popular collections are opportunistic money-grabs. Right-click, save, and mint the jacked JPEGs that are then flogged as an authentic NFT.
The anti-plagiarism system will scour OpenSea's collections for flipped and rotated images, as well as other undescribed permutations. The lack of detail here may be a deterrent to scammers, or it may reflect the new system's current rudimentary nature.
Thus, human detectors will be needed to verify images flagged by the detection system and help train it to work independently.
“Our long-term goal with this system is two-fold: first, to eliminate all existing copymints on OpenSea, and second, to help prevent new copymints from appearing,” it said.
“We've already started delisting identified copymint collections, and we'll continue to do so over the coming weeks.”
It works for Twitter, why not OpenSea
OpenSea is also changing account verification. Early adopters will be invited to apply for verification if their NFT stack is worth $100 or more. OpenSea plans to give the blue checkmark to people who are active on Twitter and Discord.
This is just the beginning. We are committed to a future where authentic creators can be verified, keeping scammers out.
Also, collections with a lot of hype and sales will get a blue checkmark. For example, a new NFT collection sold by the verified BAYC account will have a blue badge to verify its legitimacy.
New requests will be responded to within seven days, according to OpenSea.
These programs and products help protect creators and collectors while ensuring our community can confidently navigate the world of NFTs.
By elevating authentic content and removing plagiarism, these changes improve trust in the NFT ecosystem, according to OpenSea.
OpenSea is indeed catching up with the digital art economy. Last August, DevianArt upgraded its AI image recognition system to find stolen tokenized art on marketplaces like OpenSea.
It scans all uploaded art and compares it to “public blockchain events” like Ethereum NFTs to detect stolen art.