If you think NFTs are awful, check out the art market.

The fervor around NFTs has subsided in recent months due to the crypto market crash and the media's short attention span. They were all anyone could talk about earlier this spring. Last semester, when passions were high and field luminaries were discussing "slurp juices," I asked my students and students from over 20 other universities what they thought of NFTs.

According to many, NFTs were either tasteless pyramid schemes or a new way for artists to make money. NFTs contributed to the climate crisis and harmed the environment, but so did air travel, fast fashion, and smartphones. Some students complained that NFTs were cheap, tasteless, algorithmically generated schlock, but others asked how this was different from other art.

I'm not sure what I expected, but the intensity of students' reactions surprised me. They had strong, emotional opinions about a technology I'd always considered administrative. NFTs address ownership and accounting, like most crypto/blockchain projects.

Art markets can be irrational, arbitrary, and subject to the same scams and schemes as any market. And maybe a few shenanigans that are unique to the art world.

The Fairness Question

Fairness, a deflating moral currency, was the general sentiment (the less of it in circulation, the more ardently we clamor for it.) These students, almost all of whom are artists, complained to the mismatch between the quality of the work in some notable NFT collections and the excessive amounts these items were fetching on the market. They can sketch a Bored Ape or Lazy Lion in their sleep. Why should they buy ramen with school loans while certain swindlers get rich?

I understand students. Art markets are unjust. They can be irrational, arbitrary, and governed by chance and circumstance, like any market. And art-world shenanigans.

Almost every mainstream critique leveled against NFTs applies just as easily to art markets

Over 50% of artworks in circulation are fake, say experts. Sincere art collectors and institutions are upset by the prevalence of fake goods on the market. Not everyone. Wealthy people and companies use art as investments. They can use cultural institutions like museums and galleries to increase the value of inherited art collections. People sometimes buy artworks and use family ties or connections to museums or other cultural taste-makers to hype the work in their collection, driving up the price and allowing them to sell for a profit. Money launderers can disguise capital flows by using market whims, hype, and fluctuating asset prices.

Almost every mainstream critique leveled against NFTs applies just as easily to art markets.

Art has always been this way. Edward Kienholz's 1989 print series satirized art markets. He stamped 395 identical pieces of paper from $1 to $395. Each piece was initially priced as indicated. Kienholz was joking about a strange feature of art markets: once the last print in a series sells for $395, all previous works are worth at least that much. The entire series is valued at its highest auction price. I don't know what a Kienholz print sells for today (inquire with the gallery), but it's more than $395.

I love Lee Lozano's 1969 "Real Money Piece." Lozano put cash in various denominations in a jar in her apartment and gave it to visitors. She wrote, "Offer guests coffee, diet pepsi, bourbon, half-and-half, ice water, grass, and money." "Offer real money as candy."

Lee Lozano kept track of who she gave money to, how much they took, if any, and how they reacted to the offer of free money without explanation. Diverse reactions. Some found it funny, others found it strange, and others didn't care. Lozano rarely says:

Apr 17 Keith Sonnier refused, later screws lid very tightly back on. Apr 27 Kaltenbach takes all the money out of the jar when I offer it, examines all the money & puts it all back in jar. Says he doesn’t need money now. Apr 28 David Parson refused, laughing. May 1 Warren C. Ingersoll refused. He got very upset about my “attitude towards money.” May 4 Keith Sonnier refused, but said he would take money if he needed it which he might in the near future. May 7 Dick Anderson barely glances at the money when I stick it under his nose and says “Oh no thanks, I intend to earn it on my own.” May 8 Billy Bryant Copley didn’t take any but then it was sort of spoiled because I had told him about this piece on the phone & he had time to think about it he said.

Smart Contracts (smart as in fair, not smart as in Blockchain)

Cornell University's Cheryl Finley has done a lot of research on secondary art markets. I first learned about her research when I met her at the University of Florida's Harn Museum, where she spoke about smart contracts (smart as in fair, not smart as in Blockchain) and new protocols that could help artists who are often left out of the economic benefits of their own work, including women and women of color.

Her talk included findings from her ArtNet op-ed with Lauren van Haaften-Schick, Christian Reeder, and Amy Whitaker.

NFTs allow us to think about and hack on formal contractual relationships outside a system of laws that is currently not set up to service our community.

The ArtNet article The Recent Sale of Amy Sherald's ‘Welfare Queen' Symbolizes the Urgent Need for Resale Royalties and Economic Equity for Artists discussed Sherald's 2012 portrait of a regal woman in a purple dress wearing a sparkling crown and elegant set of pearls against a vibrant red background.

Amy Sherald sold "Welfare Queen" to Princeton professor Imani Perry. Sherald agreed to a payment plan to accommodate Perry's budget.

Amy Sherald rose to fame for her 2016 portrait of Michelle Obama and her full-length portrait of Breonna Taylor, one of the most famous works of the past decade.

As is common, Sherald's rising star drove up the price of her earlier works. Perry's "Welfare Queen" sold for $3.9 million in 2021.

Imani Perry's early investment paid off big-time. Amy Sherald, whose work directly increased the painting's value and who was on an artist's shoestring budget when she agreed to sell "Welfare Queen" in 2012, did not see any of the 2021 auction money. Perry and the auction house got that money.

Sherald sold her Breonna Taylor portrait to the Smithsonian and Louisville's Speed Art Museum to fund a $1 million scholarship. This is a great example of what an artist can do for the community if they can amass wealth through their work.

NFTs haven't solved all of the art market's problems — fakes, money laundering, market manipulation — but they didn't create them. Blockchain and NFTs are credited with making these issues more transparent. More ideas emerge daily about what a smart contract should do for artists.

NFTs are a copyright solution. They allow us to hack formal contractual relationships outside a law system that doesn't serve our community.

Amy Sherald shows the good smart contracts can do (as in, well-considered, self-determined contracts, not necessarily blockchain contracts.) Giving back to our community, deciding where and how our work can be sold or displayed, and ensuring artists share in the equity of our work and the economy our labor creates.

I'm trying to understand why Bitcoin NFTs aren't ready.

Ordinals, a new Bitcoin protocol, has been controversial. NFTs can be added to Bitcoin transactions using the protocol. They are not tokens or fungible. Bitcoin NFTs are transaction metadata. Yes. They're not owned.

In January, the Ordinals protocol allowed data like photos to be directly encoded onto sats, the smallest units of Bitcoin worth 0.00000001 BTC, on the Bitcoin blockchain. Ordinals does not need a sidechain or token like other techniques. The Ordinals protocol has encoded JPEG photos, digital art, new profile picture (PFP) projects, and even 1993 DOOM onto the Bitcoin network.

Ordinals inscriptions are permanent digital artifacts preserved on the Bitcoin blockchain. It differs from Ethereum, Solana, and Stacks NFT technologies that allow smart contract creators to change information. Ordinals store the whole image or content on the blockchain, not just a link to an external server, unlike centralized databases, which can change the linked image, description, category, or contract identifier.

So far, more than 50,000 ordinals have been produced on the Bitcoin blockchain, and some of them have already been sold for astronomical amounts. The Ethereum-based CryptoPunks NFT collection spawned Ordinal Punk. Inscription 620 sold for 9.5 BTC, or $218,000, the most.

Segwit and Taproot, two important Bitcoin blockchain updates, enabled this. These protocols store transaction metadata, unlike Ethereum, where the NFT is the token. Bitcoin's NFT is a sat's transaction details.

What effects do ordinary values and NFTs have on the Bitcoin blockchain?

Ordinals will likely have long-term effects on the Bitcoin Ecosystem since they store, transact, and compute more data.

Charges Ordinals introduce scalability challenges. The Bitcoin network has limited transaction throughput and increased fees during peak demand. NFTs could make network transactions harder and more expensive. Ordinals currently occupy over 50% of block space, according to Glassnode.

One of the protocols that supported Ordinals Taproot has also seen a huge uptick:

Taproot use increases block size and transaction costs.

This could cause network congestion but also support more L2s with Ordinals-specific use cases. Dune info here.

Storage Needs The Bitcoin blockchain would need to store more data to store NFT data directly. Since ordinals were introduced, blocksize has tripled from 0.7mb to over 2.2mb, which could increase storage costs and make it harder for nodes to join the network.

Use Case Diversity On the other hand, NFTs on the Bitcoin blockchain could broaden Bitcoin's use cases beyond storage and payment. This could expand Bitcoin's user base. This is two-sided. Bitcoin was designed to be trustless, decentralized, peer-to-peer money.

Chain to permanently store NFTs as ordinals will change everything.

Popularity rise This new use case will boost Bitcoin appeal, according to some. This argument fails since Bitcoin is the most popular cryptocurrency. Popularity doesn't require a new use case. Cryptocurrency adoption boosts Bitcoin. It need not compete with Ethereum or provide extra benefits to crypto investors. If there was a need for another chain that supports NFTs (there isn't), why would anyone choose the slowest and most expensive network? It appears contradictory and unproductive.

Nonetheless, holding an NFT on the Bitcoin blockchain is more secure than any other blockchain, but this has little utility.

Bitcoin NFTs are undoubtedly controversial. NFTs are strange and perhaps harmful to Bitcoin's mission. If Bitcoin NFTs are here to stay, I hope a sidechain or rollup solution will take over and leave the base chain alone.

AI images are like funhouse mirrors.

Google's AI Blog introduced the puppy-slug in the summer of 2015.

Puppy-slug isn't a single image or character. "Puppy-slug" refers to Google's DeepDream's unsettling psychedelia. This tool uses convolutional neural networks to train models to recognize dataset entities. If researchers feed the model millions of dog pictures, the network will learn to recognize a dog.

DeepDream used neural networks to analyze and classify image data as well as generate its own images. DeepDream's early examples were created by training a convolutional network on dog images and asking it to add "dog-ness" to other images. The models analyzed images to find dog-like pixels and modified surrounding pixels to highlight them.

Puppy-slugs and other DeepDream images are ugly. Even when they don't trigger my trypophobia, they give me vertigo when my mind tries to reconcile familiar features and forms in unnatural, physically impossible arrangements. I feel like I've been poisoned by a forbidden mushroom or a noxious toad. I'm a Lovecraft character going mad from extradimensional exposure. They're gross!

Is this really how AIs see the world? This is possibly an even more unsettling topic that DeepDream raises than the blatant abjection of the images.

When these photographs originally circulated online, many friends were startled and scandalized. People imagined a computer's imagination would be literal, accurate, and boring. We didn't expect vivid hallucinations and organic-looking formations.

DeepDream's images didn't really show the machines' imaginations, at least not in the way that scared some people. DeepDream displays data visualizations. DeepDream reveals the "black box" of convolutional network training.

Some of these images look scary because the models don't "know" anything, at least not in the way we do.

These images are the result of advanced algorithms and calculators that compare pixel values. They can spot and reproduce trends from training data, but can't interpret it. If so, they'd know dogs have two eyes and one face per head. If machines can think creatively, they're keeping it quiet.

You could be forgiven for thinking otherwise, given OpenAI's Dall-impressive E's results. From a technological perspective, it's incredible.

Arthur C. Clarke once said, "Any sufficiently advanced technology is indistinguishable from magic." Dall-magic E's requires a lot of math, computer science, processing power, and research. OpenAI did a great job, and we should applaud them.

Dall-E and similar tools match words and phrases to image data to train generative models. Matching text to images requires sorting and defining the images. Untold millions of low-wage data entry workers, content creators optimizing images for SEO, and anyone who has used a Captcha to access a website make these decisions. These people could live and die without receiving credit for their work, even though the project wouldn't exist without them.

This technique produces images that are less like paintings and more like mirrors that reflect our own beliefs and ideals back at us, albeit via a very complex prism. Due to the limitations and biases that these models portray, we must exercise caution when viewing these images.

The issue was succinctly articulated by artist Mimi Onuoha in her piece "On Algorithmic Violence":

As we continue to see the rise of algorithms being used for civic, social, and cultural decision-making, it becomes that much more important that we name the reality that we are seeing. Not because it is exceptional, but because it is ubiquitous. Not because it creates new inequities, but because it has the power to cloak and amplify existing ones. Not because it is on the horizon, but because it is already here.

Disclaimer : This is not financial advice for any investment.

TL;DR

• You might not have realized it, but as we move toward net zero carbon emissions, the globe is already at war.

• According to the Paris Agreement of COP26, 64% of nations have already declared net zero, and the issue of carbon reduction has already become so important for businesses that it affects their ability to survive. Furthermore, the time when carbon emission standards will be defined and controlled on an individual basis is becoming closer.

• Since 2017, the market for carbon credits has experienced extraordinary expansion as a result of widespread talks about carbon credits. The carbon credit market is predicted to expand much more once net zero is implemented and carbon emission rules inevitably tighten.

Hello! Ben here from Nonce Classic. Nonce Classic has recently confirmed the tremendous growth potential of the carbon credit market in the midst of a major trend towards the global goal of net zero (carbon emissions caused by humans — carbon reduction by humans = 0 ). Moreover, we too believed that the questions and issues the carbon credit market suffered from the last 30–40yrs could be perfectly answered through crypto technology and that is why we have added a carbon credit crypto project to the Nonce Classic portfolio. There have been many teams out there that have tried to solve environmental problems through crypto but very few that have measurable experience working in the carbon credit scene. Thus we have put in our efforts to find projects that are not crypto projects created for the sake of issuing tokens but projects that pragmatically use crypto technology to combat climate change by solving problems of the current carbon credit market. In that process, we came to hear of Climate Coin, a veritable carbon credit crypto project, and us Nonce Classic as an accelerator, have begun contributing to its growth and invested in its tokens. Starting with this article, we plan to publish a series of articles explaining why the carbon credit market is bullish, why we invested in Climate Coin, and what kind of project Climate Coin is specifically. In this first article let us understand the carbon credit market and look into its growth potential! Let’s begin :)

The Unavoidable Entry of the Net Zero Era

Net zero means... Human carbon emissions are balanced by carbon reduction efforts. A non-environmentalist may find it hard to accept that net zero is attainable by 2050. Global cooperation to save the earth is happening faster than we imagine.

In the Paris Agreement of COP26, concluded in Glasgow, UK on Oct. 31, 2021, nations pledged to reduce worldwide yearly greenhouse gas emissions by more than 50% by 2030 and attain net zero by 2050. Governments throughout the world have pledged net zero at the national level and are holding each other accountable by submitting Nationally Determined Contributions (NDC) every five years to assess implementation. 127 of 198 nations have declared net zero.

Each country's 1.5-degree reduction plans have led to carbon reduction obligations for companies. In places with the strictest environmental regulations, like the EU, companies often face bankruptcy because the cost of buying carbon credits to meet their carbon allowances exceeds their operating profits. In this day and age, minimizing carbon emissions and securing carbon credits are crucial.

Recent SEC actions on climate change may increase companies' concerns about reducing emissions. The SEC required all U.S. stock market companies to disclose their annual greenhouse gas emissions and climate change impact on March 21, 2022. The SEC prepared the proposed regulation through in-depth analysis and stakeholder input since last year. Three out of four SEC members agreed that it should pass without major changes. If the regulation passes, it will affect not only US companies, but also countless companies around the world, directly or indirectly.

Even companies not listed on the U.S. stock market will be affected and, in most cases, required to disclose emissions. Companies listed on the U.S. stock market with significant greenhouse gas emissions or specific targets are subject to stricter emission standards (Scope 3) and disclosure obligations, which will magnify investigations into all related companies. Greenhouse gas emissions can be calculated three ways. Scope 1 measures carbon emissions from a company's facilities and transportation. Scope 2 measures carbon emissions from energy purchases. Scope 3 covers all indirect emissions from a company's value chains.

The SEC's proposed carbon emission disclosure mandate and regulations are one example of how carbon credit policies can cross borders and affect all parties. As such incidents will continue throughout the implementation of net zero, even companies that are not immediately obligated to disclose their carbon emissions must be prepared to respond to changes in carbon emission laws and policies.

Carbon reduction obligations will soon become individual. Individual consumption has increased dramatically with improved quality of life and convenience, despite national and corporate efforts to reduce carbon emissions. Since consumption is directly related to carbon emissions, increasing consumption increases carbon emissions. Countries around the world have agreed that to achieve net zero, carbon emissions must be reduced on an individual level. Solutions to individual carbon reduction are being actively discussed and studied under the term Personal Carbon Trading (PCT).

PCT is a system that allows individuals to trade carbon emission quotas in the form of carbon credits. Individuals who emit more carbon than their allotment can buy carbon credits from those who emit less. European cities with well-established carbon credit markets are preparing for net zero by conducting early carbon reduction prototype projects. The era of checking product labels for carbon footprints, choosing low-emissions transportation, and worrying about hot shower emissions is closer than we think.

The Market for Carbon Credits Is Expanding Fearfully

Compliance and voluntary carbon markets make up the carbon credit market.

A Compliance Market enforces carbon emission allowances for actors. Companies in industries that previously emitted a lot of carbon are included in the mandatory carbon market, and each government receives carbon credits each year. If a company's emissions are less than the assigned cap and it has extra carbon credits, it can sell them to other companies that have larger emissions and require them (Cap and Trade). The annual number of free emission permits provided to companies is designed to decline, therefore companies' desire for carbon credits will increase. The compliance market's yearly trading volume will exceed $261B in 2020, five times its 2017 level.

In the Voluntary Market, carbon reduction is voluntary and carbon credits are sold for personal reasons or to build market participants' eco-friendly reputations. Even if not in the compliance market, it is typical for a corporation to be obliged to offset its carbon emissions by acquiring voluntary carbon credits. When a company seeks government or company investment, it may be denied because it is not net zero. If a significant shareholder declares net zero, the companies below it must execute it. As the world moves toward ESG management, becoming an eco-friendly company is no longer a strategic choice to gain a competitive edge, but an important precaution to not fall behind. Due to this eco-friendly trend, the annual market volume of voluntary emission credits will approach $1B by November 2021. The voluntary credit market is anticipated to reach $5B to $50B by 2030. (TSCVM 2021 Report)

In conclusion

This article analyzed how net zero, a target promised by countries around the world to combat climate change, has brought governmental, corporate, and human changes. We discussed how these shifts will become more obvious as we approach net zero, and how the carbon credit market would increase exponentially in response. In the following piece, let's analyze the hurdles impeding the carbon credit market's growth, how the project we invested in tries to tackle these issues, and why we chose Climate Coin. Wait! Jim Skea, co-chair of the IPCC working group, said,

“It’s now or never, if we want to limit global warming to 1.5°C” — Jim Skea

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Believe what you see, what people say

It’s sad that we never get trained to leave assumptions behind. - Sebastian Thrun

Many problems in software development are not because of code but because developers create the wrong software. This isn't rare because software is emergent and most individuals only realize what they want after it's built.

Inquisitive developers who pass the yellow cat test can improve the process.

Carpenters measure twice and cut the wood once. Developers are rarely so careful.

The Yellow Cat Test

Game of Thrones made dragons cool again, so I am reading The Game of Thrones book.

The yellow cat exam is from Syrio Forel, Arya Stark's fencing instructor.

Syrio tells Arya he'll strike left when fencing. He hits her after she dodges left. Arya says “you lied”. Syrio says his words lied, but his eyes and arm told the truth.

Arya learns how Syrio became Bravos' first sword.

“On the day I am speaking of, the first sword was newly dead, and the Sealord sent for me. Many bravos had come to him, and as many had been sent away, none could say why. When I came into his presence, he was seated, and in his lap was a fat yellow cat. He told me that one of his captains had brought the beast to him, from an island beyond the sunrise. ‘Have you ever seen her like?’ he asked of me.

“And to him I said, ‘Each night in the alleys of Braavos I see a thousand like him,’ and the Sealord laughed, and that day I was named the first sword.”

Arya screwed up her face. “I don’t understand.”

Syrio clicked his teeth together. “The cat was an ordinary cat, no more. The others expected a fabulous beast, so that is what they saw. How large it was, they said. It was no larger than any other cat, only fat from indolence, for the Sealord fed it from his own table. What curious small ears, they said. Its ears had been chewed away in kitten fights. And it was plainly a tomcat, yet the Sealord said ‘her,’ and that is what the others saw. Are you hearing?” Reddit discussion.

Development teams should not believe what they are told.

We created an appointment booking system. We thought it was an appointment-booking system. Later, we realized the software's purpose was to book the right people for appointments and discourage the unneeded ones.

The first 3 months of the project had half-correct requirements and software understanding.

Open your eyes

“Open your eyes is all that is needed. The heart lies and the head plays tricks with us, but the eyes see true. Look with your eyes, hear with your ears. Taste with your mouth. Smell with your nose. Feel with your skin. Then comes the thinking afterwards, and in that way, knowing the truth” Syrio Ferel

We must see what exists, not what individuals tell the development team or how developers think the software should work. Initial criteria cover 50/70% and change.

Developers build assumptions problems by assuming how software should work. Developers must quickly explain assumptions.

When a development team's assumptions are inaccurate, they must alter the code, DevOps, documentation, and tests.

It’s always faster and easier to fix requirements before code is written.

First-draft requirements can be based on old software. Development teams must grasp corporate goals and consider needs from many angles.

Testers help rethink requirements. They look at how software requirements shouldn't operate.

Technical features and benefits might misdirect software projects.

The initiatives that focused on technological possibilities developed hard-to-use software that needed extensive rewriting following user testing.

Software development

High-level criteria are different from detailed ones.

• The interpretation of words determines their meaning.

• Presentations are lofty, upbeat, and prejudiced.

• People's perceptions may be unclear, incorrect, or just based on one perspective (half the story)

• Developers can be misled by requirements, circumstances, people, plans, diagrams, designs, documentation, and many other things.

Developers receive misinformation, misunderstandings, and wrong assumptions. The development team must avoid building software with erroneous specifications.

Once code and software are written, the development team changes and fixes them.

Developers create software with incomplete information, they need to fill in the blanks to create the complete picture.

Conclusion

Yellow cats are often inaccurate when communicating requirements.

Before writing code, clarify requirements, assumptions, etc.

Everyone will pressure the development team to generate code rapidly, but this will slow down development.

Code changes are harder than requirements.