More on NFTs & Art
Jake Prins
3 years ago
What are NFTs 2.0 and what issues are they meant to address?
New standards help NFTs reach their full potential.
NFTs lack interoperability and functionality. They have great potential but are mostly speculative. To maximize NFTs, we need flexible smart contracts.
Current requirements are too restrictive.
Most NFTs are based on ERC-721, which makes exchanging them easy. CryptoKitties, a popular online game, used the 2017 standard to demonstrate NFTs' potential.
This simple standard includes a base URI and incremental IDs for tokens. Add the tokenID to the base URI to get the token's metadata.
This let creators collect NFTs. Many NFT projects store metadata on IPFS, a distributed storage network, but others use Google Drive. NFT buyers often don't realize that if the creators delete or move the files, their NFT is just a pointer.
This isn't the standard's biggest issue. There's no way to validate NFT projects.
Creators are one of the most important aspects of art, but nothing is stored on-chain.
ERC-721 contracts only have a name and symbol.
Most of the data on OpenSea's collection pages isn't from the NFT's smart contract. It was added through a platform input field, so it's in the marketplace's database. Other websites may have different NFT information.
In five years, your NFT will be just a name, symbol, and ID.
Your NFT doesn't mention its creators. Although the smart contract has a public key, it doesn't reveal who created it.
The NFT's creators and their reputation are crucial to its value. Think digital fashion and big brands working with well-known designers when more professionals use NFTs. Don't you want them in your NFT?
Would paintings be as valuable if their artists were unknown? Would you believe it's real?
Buying directly from an on-chain artist would reduce scams. Current standards don't allow this data.
Most creator profiles live on centralized marketplaces and could disappear. Current platforms have outpaced underlying standards. The industry's standards are lagging.
For NFTs to grow beyond pointers to a monkey picture file, we may need to use new Web3-based standards.
Introducing NFTs 2.0
Fabian Vogelsteller, creator of ERC-20, developed new web3 standards. He proposed LSP7 Digital Asset and LSP8 Identifiable Digital Asset, also called NFT 2.0.
NFT and token metadata inputs are extendable. Changes to on-chain metadata inputs allow NFTs to evolve. Instead of public keys, the contract can have Universal Profile addresses attached. These profiles show creators' faces and reputations. NFTs can notify asset receivers, automating smart contracts.
LSP7 and LSP8 use ERC725Y. Using a generic data key-value store gives contracts much-needed features:
The asset can be customized and made to stand out more by allowing for unlimited data attachment.
Recognizing changes to the metadata
using a hash reference for metadata rather than a URL reference
This base will allow more metadata customization and upgradeability. These guidelines are:
Genuine and Verifiable Now, the creation of an NFT by a specific Universal Profile can be confirmed by smart contracts.
Dynamic NFTs can update Flexible & Updatable Metadata, allowing certain things to evolve over time.
Protected metadata Now, secure metadata that is readable by smart contracts can be added indefinitely.
Better NFTS prevent the locking of NFTs by only being sent to Universal Profiles or a smart contract that can interact with them.
Summary
NFTS standards lack standardization and powering features, limiting the industry.
ERC-721 is the most popular NFT standard, but it only represents incremental tokenIDs without metadata or asset representation. No standard sender-receiver interaction or security measures ensure safe asset transfers.
NFT 2.0 refers to the new LSP7-DigitalAsset and LSP8-IdentifiableDigitalAsset standards.
They have new standards for flexible metadata, secure transfers, asset representation, and interactive transfer.
With NFTs 2.0 and Universal Profiles, creators could build on-chain reputations.
NFTs 2.0 could bring the industry's needed innovation if it wants to move beyond trading profile pictures for speculation.
Adrien Book
3 years ago
What is Vitalik Buterin's newest concept, the Soulbound NFT?
Decentralizing Web3's soul
Our tech must reflect our non-transactional connections. Web3 arose from a lack of social links. It must strengthen these linkages to get widespread adoption. Soulbound NFTs help.
This NFT creates digital proofs of our social ties. It embodies G. Simmel's idea of identity, in which individuality emerges from social groups, just as social groups evolve from people.
It's multipurpose. First, gather online our distinctive social features. Second, highlight and categorize social relationships between entities and people to create a spiderweb of networks.
1. 🌐 Reducing online manipulation: Only socially rich or respectable crypto wallets can participate in projects, ensuring that no one can create several wallets to influence decentralized project governance.
2. 🤝 Improving social links: Some sectors of society lack social context. Racism, sexism, and homophobia do that. Public wallets can help identify and connect distinct social groupings.
3. 👩❤️💋👨 Increasing pluralism: Soulbound tokens can ensure that socially connected wallets have less voting power online to increase pluralism. We can also overweight a minority of numerous voices.
4. 💰Making more informed decisions: Taking out an insurance policy requires a life review. Why not loans? Character isn't limited by income, and many people need a chance.
5. 🎶 Finding a community: Soulbound tokens are accessible to everyone. This means we can find people who are like us but also different. This is probably rare among your friends and family.
NFTs are dangerous, and I don't like them. Social credit score, privacy, lost wallet. We must stay informed and keep talking to innovators.
E. Glen Weyl, Puja Ohlhaver and Vitalik Buterin get all the credit for these ideas, having written the very accessible white paper “Decentralized Society: Finding Web3’s Soul”.
CyberPunkMetalHead
2 years ago
Why Bitcoin NFTs Are Incomprehensible yet Likely Here to Stay
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.
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Bob Service
3 years ago
Did volcanic 'glasses' play a role in igniting early life?
Quenched lava may have aided in the formation of long RNA strands required by primitive life.
It took a long time for life to emerge. Microbes were present 3.7 billion years ago, just a few hundred million years after the 4.5-billion-year-old Earth had cooled enough to sustain biochemistry, according to fossils, and many scientists believe RNA was the genetic material for these first species. RNA, while not as complicated as DNA, would be difficult to forge into the lengthy strands required to transmit genetic information, raising the question of how it may have originated spontaneously.
Researchers may now have a solution. They demonstrate how basaltic glasses assist individual RNA letters, also known as nucleoside triphosphates, join into strands up to 200 letters long in lab studies. The glasses are formed when lava is quenched in air or water, or when melted rock generated by asteroid strikes cools rapidly, and they would have been plentiful in the early Earth's fire and brimstone.
The outcome has caused a schism among top origin-of-life scholars. "This appears to be a great story that finally explains how nucleoside triphosphates react with each other to create RNA strands," says Thomas Carell, a scientist at Munich's Ludwig Maximilians University. However, Harvard University's Jack Szostak, an RNA expert, says he won't believe the results until the study team thoroughly describes the RNA strands.
Researchers interested in the origins of life like the idea of a primordial "RNA universe" since the molecule can perform two different functions that are essential for life. It's made up of four chemical letters, just like DNA, and can carry genetic information. RNA, like proteins, can catalyze chemical reactions that are necessary for life.
However, RNA can cause headaches. No one has yet discovered a set of plausible primordial conditions that would cause hundreds of RNA letters—each of which is a complicated molecule—to join together into strands long enough to support the intricate chemistry required to kick-start evolution.
Basaltic glasses may have played a role, according to Stephen Mojzsis, a geologist at the University of Colorado, Boulder. They're high in metals like magnesium and iron, which help to trigger a variety of chemical reactions. "Basaltic glass was omnipresent on Earth at the time," he adds.
He provided the Foundation for Applied Molecular Evolution samples of five different basalt glasses. Each sample was ground into a fine powder, sanitized, and combined with a solution of nucleoside triphosphates by molecular biologist Elisa Biondi and her colleagues. The RNA letters were unable to link up without the presence of glass powder. However, when the molecules were mixed with the glass particles, they formed long strands of hundreds of letters, according to the researchers, who published their findings in Astrobiology this week. There was no need for heat or light. Biondi explains, "All we had to do was wait." After only a day, little RNA strands produced, yet the strands continued to grow for months. Jan Paek, a molecular biologist at Firebird Biomolecular Sciences, says, "The beauty of this approach is its simplicity." "Mix the components together, wait a few days, and look for RNA."
Nonetheless, the findings pose a slew of problems. One of the questions is how nucleoside triphosphates came to be in the first place. Recent study by Biondi's colleague Steven Benner suggests that the same basaltic glasses may have aided in the creation and stabilization of individual RNA letters.
The form of the lengthy RNA strands, according to Szostak, is a significant challenge. Enzymes in modern cells ensure that most RNAs form long linear chains. RNA letters, on the other hand, can bind in complicated branching sequences. Szostak wants the researchers to reveal what kind of RNA was produced by the basaltic glasses. "It irritates me that the authors made an intriguing initial finding but then chose to follow the hype rather than the research," Szostak says.
Biondi acknowledges that her team's experiment almost probably results in some RNA branching. She does acknowledge, however, that some branched RNAs are seen in species today, and that analogous structures may have existed before the origin of life. Other studies carried out by the study also confirmed the presence of lengthy strands with connections, indicating that they are most likely linear. "It's a healthy argument," says Dieter Braun, a Ludwig Maximilian University origin-of-life chemist. "It will set off the next series of tests."
Amelia Winger-Bearskin
3 years ago
Reasons Why AI-Generated Images Remind Me of Nightmares
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.
Greg Satell
2 years ago
Focus: The Deadly Strategic Idea You've Never Heard Of (But Definitely Need To Know!
Steve Jobs' initial mission at Apple in 1997 was to destroy. He killed the Newton PDA and Macintosh clones. Apple stopped trying to please everyone under Jobs.
Afterward, there were few highly targeted moves. First, the pink iMac. Modest success. The iPod, iPhone, and iPad made Apple the world's most valuable firm. Each maneuver changed the company's center of gravity and won.
That's the idea behind Schwerpunkt, a German military term meaning "focus." Jobs didn't need to win everywhere, just where it mattered, so he focused Apple's resources on a few key goods. Finding your Schwerpunkt is more important than charts and analysis for excellent strategy.
Comparison of Relative Strength and Relative Weakness
The iPod, Apple's first major hit after Jobs' return, didn't damage Microsoft and the PC, but instead focused Apple's emphasis on a fledgling, fragmented market that generated "sucky" products. Apple couldn't have taken on the computer titans at this stage, yet it beat them.
The move into music players used Apple's particular capabilities, especially its ability to build simple, easy-to-use interfaces. Jobs' charisma and stature, along his understanding of intellectual property rights from Pixar, helped him build up iTunes store, which was a quagmire at the time.
In Good Strategy | Bad Strategy, management researcher Richard Rumelt argues that good strategy uses relative strength to counter relative weakness. To discover your main point, determine your abilities and where to effectively use them.
Steve Jobs did that at Apple. Microsoft and Dell, who controlled the computer sector at the time, couldn't enter the music player business. Both sought to produce iPod competitors but failed. Apple's iPod was nobody else's focus.
Finding The Center of Attention
In a military engagement, leaders decide where to focus their efforts by assessing commanders intent, the situation on the ground, the topography, and the enemy's posture on that terrain. Officers spend their careers learning about schwerpunkt.
Business executives must assess internal strengths including personnel, technology, and information, market context, competitive environment, and external partner ecosystems. Steve Jobs was a master at analyzing forces when he returned to Apple.
He believed Apple could integrate technology and design for the iPod and that the digital music player industry sucked. By analyzing competitors' products, he was convinced he could produce a smash by putting 1000 tunes in my pocket.
The only difficulty was there wasn't the necessary technology. External ecosystems were needed. On a trip to Japan to meet with suppliers, a Toshiba engineer claimed the company had produced a tiny memory drive approximately the size of a silver dollar.
Jobs knew the memory drive was his focus. He wrote a $10 million cheque and acquired exclusive technical rights. For a time, none of his competitors would be able to recreate his iPod with the 1000 songs in my pocket.
How to Enter the OODA Loop
John Boyd invented the OODA loop as a pilot to better his own decision-making. First OBSERVE your surroundings, then ORIENT that information using previous knowledge and experiences. Then you DECIDE and ACT, which changes the circumstance you must observe, orient, decide, and act on.
Steve Jobs used the OODA loop to decide to give Toshiba $10 million for a technology it had no use for. He compared the new information with earlier observations about the digital music market.
Then something much more interesting happened. The iPod was an instant hit, changing competition. Other computer businesses that competed in laptops, desktops, and servers created digital music players. Microsoft's Zune came out in 2006, Dell's Digital Jukebox in 2004. Both flopped.
By then, Apple was poised to unveil the iPhone, which would cause its competitors to Observe, Orient, Decide, and Act. Boyd named this OODA Loop infiltration. They couldn't gain the initiative by constantly reacting to Apple.
Microsoft and Dell were titans back then, but it's hard to recall. Apple went from near bankruptcy to crushing its competition via Schwerpunkt.
Rather than a destination, it is a journey
Trying to win everywhere is a strategic blunder. Win significant fights, not trivial skirmishes. Identifying a focal point to direct resources and efforts is the essence of Schwerpunkt.
When Steve Jobs returned to Apple, PC firms were competing, but he focused on digital music players, and the iPod made Apple a player. He launched the iPhone when his competitors were still reacting. When Steve Jobs said, "One more thing," at the end of a product presentation, he had a new focus.
Schwerpunkt isn't static; it's dynamic. Jobs' ability to observe, refocus, and modify the competitive backdrop allowed Apple to innovate consistently. His strategy was tailored to Apple's capabilities, customers, and ecosystem. Microsoft or Dell, better suited for the enterprise sector, couldn't succeed with a comparable approach.
There is no optimal strategy, only ones suited to a given environment, when relative strength might be used against relative weakness. Discovering the center of gravity where you can break through is more of a journey than a destination; it will become evident after you reach.