More on NFTs & Art

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.

1eth1da
3 years ago
6 Rules to build a successful NFT Community in 2022

Too much NFT, Discord, and shitposting.
How do you choose?
How do you recruit more members to join your NFT project?
In 2021, a successful NFT project required:
Monkey/ape artwork
Twitter and Discord bot-filled
Roadmap overpromise
Goal was quick cash.
2022 and the years after will change that.
These are 6 Rules for a Strong NFT Community in 2022:
THINK LONG TERM
This relates to roadmap planning. Hype and dumb luck may drive NFT projects (ahem, goblins) but rarely will your project soar.
Instead, consider sustainability.
Plan your roadmap based on your team's abilities.
Do what you're already doing, but with NFTs, make it bigger and better.
You shouldn't copy a project's roadmap just because it was profitable.
This will lead to over-promising, team burnout, and an RUG NFT project.
OFFER VALUE
Building a great community starts with giving.
Why are musicians popular?
Because they offer entertainment for everyone, a random person becomes a fan, and more fans become a cult.
That's how you should approach your community.
TEAM UP
A great team helps.
An NFT project could have 3 or 2 people.
Credibility trumps team size.
Make sure your team can answer community questions, resolve issues, and constantly attend to them.
Don't overwork and burn out.
Your community will be able to recognize that you are trying too hard and give up on the project.
BUILD A GREAT PRODUCT
Bored Ape Yacht Club altered the NFT space.
Cryptopunks transformed NFTs.
Many others did, including Okay Bears.
What made them that way?
Because they answered a key question.
What is my NFT supposed to be?
Before planning art, this question must be answered.
NFTs can't be just jpegs.
What does it represent?
Is it a Metaverse-ready project?
What blockchain are you going to be using and why?
Set some ground rules for yourself. This helps your project's direction.
These questions will help you and your team set a direction for blockchain, NFT, and Web3 technology.
EDUCATE ON WEB3
The more the team learns about Web3 technology, the more they can offer their community.
Think tokens, metaverse, cross-chain interoperability and more.
BUILD A GREAT COMMUNITY
Several projects mistreat their communities.
They treat their community like "customers" and try to sell them NFT.
Providing Whitelists and giveaways aren't your only community-building options.
Think bigger.
Consider them family and friends, not wallets.
Consider them fans.
These are some tips to start your NFT project.
Matt Nutsch
3 years ago
Most people are unaware of how artificial intelligence (A.I.) is changing the world.
Recently, I saw an interesting social media post. In an entrepreneurship forum. A blogger asked for help because he/she couldn't find customers. I now suspect that the writer’s occupation is being disrupted by A.I.
Introduction
Artificial Intelligence (A.I.) has been a hot topic since the 1950s. With recent advances in machine learning, A.I. will touch almost every aspect of our lives. This article will discuss A.I. technology and its social and economic implications.
What's AI?
A computer program or machine with A.I. can think and learn. In general, it's a way to make a computer smart. Able to understand and execute complex tasks. Machine learning, NLP, and robotics are common types of A.I.
AI's global impact
AI will change the world, but probably faster than you think. A.I. already affects our daily lives. It improves our decision-making, efficiency, and productivity.
A.I. is transforming our lives and the global economy. It will create new business and job opportunities but eliminate others. Affected workers may face financial hardship.
AI examples:
OpenAI's GPT-3 text-generation
Developers can train, deploy, and manage models on GPT-3. It handles data preparation, model training, deployment, and inference for machine learning workloads. GPT-3 is easy to use for both experienced and new data scientists.
My team conducted an experiment. We needed to generate some blog posts for a website. We hired a blogger on Upwork. OpenAI created a blog post. The A.I.-generated blog post was of higher quality and lower cost.
MidjourneyAI's Art Contests
AI already affects artists. Artists use A.I. to create realistic 3D images and videos for digital art. A.I. is also used to generate new art ideas and methods.
MidjourneyAI and GigapixelAI won a contest last month. It's AI. created a beautiful piece of art that captured the contest's spirit. AI triumphs. It could open future doors.
After the art contest win, I registered to try out these new image generating A.I.s. In the MidjourneyAI chat forum, I noticed an artist's plea. The artist begged others to stop flooding RedBubble with AI-generated art.
Shutterstock and Getty Images have halted user uploads. AI-generated images flooded online marketplaces.
Imagining Videos with Meta
Meta released Make-a-Video this week. It's an A.I. app that creates videos from text. What you type creates a video.
This technology will impact TV, movies, and video games greatly. Imagine a movie or game that's personalized to your tastes. It's closer than you think.
Uses and Abuses of Deepfakes
Deepfake videos are computer-generated images of people. AI creates realistic images and videos of people.
Deepfakes are entertaining but have social implications. Porn introduced deepfakes in 2017. People put famous faces on porn actors and actresses without permission.
Soon, deepfakes were used to show dead actors/actresses or make them look younger. Carrie Fischer was included in films after her death using deepfake technology.
Deepfakes can be used to create fake news or manipulate public opinion, according to an AI.
Voices for Darth Vader and Iceman
James Earl Jones, who voiced Darth Vader, sold his voice rights this week. Aged actor won't be in those movies. Respeecher will use AI to mimic Jones's voice. This technology could change the entertainment industry. One actor can now voice many characters.
AI can generate realistic voice audio from text. Top Gun 2 actor Val Kilmer can't speak for medical reasons. Sonantic created Kilmer's voice from the movie script. This entertaining technology has social implications. It blurs authentic recordings and fake media.
Medical A.I. fights viruses
A team of Chinese scientists used machine learning to predict effective antiviral drugs last year. They started with a large dataset of virus-drug interactions. Researchers combined that with medication and virus information. Finally, they used machine learning to predict effective anti-virus medicines. This technology could solve medical problems.
AI ideas AI-generated Itself
OpenAI's GPT-3 predicted future A.I. uses. Here's what it told me:
AI will affect the economy. Businesses can operate more efficiently and reinvest resources with A.I.-enabled automation. AI can automate customer service tasks, reducing costs and improving satisfaction.
A.I. makes better pricing, inventory, and marketing decisions. AI automates tasks and makes decisions. A.I.-powered robots could help the elderly or disabled. Self-driving cars could reduce accidents.
A.I. predictive analytics can predict stock market or consumer behavior trends and patterns. A.I. also personalizes recommendations. sways. A.I. recommends products and movies. AI can generate new ideas based on data analysis.
Conclusion
A.I. will change business as it becomes more common. It will change how we live and work by creating growth and prosperity.
Exciting times, but also one which should give us all pause. Technology can be good or evil. We must use new technologies ethically, fairly, and honestly.
“The author generated some sentences in this text in part with GPT-3, OpenAI’s large-scale language-generation model. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication. The text of this post was further edited using HemingWayApp. Many of the images used were generated using A.I. as described in the captions.”
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Rick Blyth
3 years ago
Looking for a Reliable Micro SaaS Niche
Niches are rich, as the adage goes.
Micro SaaS requires a great micro-niche; otherwise, it's merely plain old SaaS with a large audience.
Instead of targeting broad markets with few identifying qualities, specialise down to a micro-niche. How would you target these users?
Better go tiny. You'll locate and engage new consumers more readily and serve them better with a customized solution.
Imagine you're a real estate lawyer looking for a case management solution. Because it's so specific to you, you'd be lured to this link:
instead of below:
Next, locate mini SaaS niches that could work for you. You're not yet looking at the problems/solutions in these areas, merely shortlisting them.
The market should be growing, not shrinking
We shouldn't design apps for a declining niche. We intend to target stable or growing niches for the next 5 to 10 years.
If it's a developing market, you may be able to claim a stake early. You must balance this strategy with safer, longer-established niches (accountancy, law, health, etc).
First Micro SaaS apps I designed were for Merch By Amazon creators, a burgeoning niche. I found this niche when searching for passive income.
Graphic designers and entrepreneurs post their art to Amazon to sell on clothes. When Amazon sells their design, they get a royalty. Since 2015, this platform and specialty have grown dramatically.
Amazon doesn't publicize the amount of creators on the platform, but it's possible to approximate by looking at Facebook groups, Reddit channels, etc.
I could see the community growing week by week, with new members joining. Merch was an up-and-coming niche, and designers made money when their designs sold. All I had to do was create tools that let designers focus on making bestselling designs.
Look at the Google Trends graph below to see how this niche has evolved and when I released my apps and resigned my job.
Are the users able to afford the tools?
Who's your average user? Consumer or business? Is your solution budgeted?
If they're students, you'll struggle to convince them to subscribe to your study-system app (ahead of video games and beer).
Let's imagine you designed a Shopify plugin that emails customers when a product is restocked. If your plugin just needs 5 product sales a month to justify its cost, everyone wins (just be mindful that one day Shopify could potentially re-create your plugins functionality within its core offering making your app redundant ).
Do specialized users buy tools? If so, that's comforting. If not, you'd better have a compelling value proposition for your end customer if you're the first.
This should include how much time or money your program can save or make the user.
Are you able to understand the Micro SaaS market?
Ideally, you're already familiar about the industry/niche. Maybe you're fixing a challenge from your day job or freelance work.
If not, evaluate how long it would take to learn the niche's users. Health & Fitness is easier to relate to and understand than hedge fund derivatives trading.
Competing in these complex (and profitable) fields might offer you an edge.
B2C, B2M, or B2B?
Consider your user base's demographics. Will you target businesses, consumers, or both? Let's examine the different consumer types:
B2B refers to business-to-business transactions where customers are other businesses. UpVoty, Plutio, Slingshot, Salesforce, Atlassian, and Hubspot are a few examples of SaaS, ranging from Micro SaaS to SaaS.
Business to Consumer (B2C), in which your clients are people who buy things. For instance, Duolingo, Canva, and Nomad List.
For instance, my tool KDP Wizard has a mixed user base of publishing enterprises and also entrepreneurial consumers selling low-content books on Amazon. This is a case of business to many (B2M), where your users are a mixture of businesses and consumers. There is a large SaaS called Dropbox that offers both personal and business plans.
Targeting a B2B vs. B2C niche is very different. The sales cycle differs.
A B2B sales staff must make cold calls to potential clients' companies. Long sales, legal, and contractual conversations are typically required for each business to get the go-ahead. The cost of obtaining a new customer is substantially more than it is for B2C, despite the fact that the recurring fees are significantly higher.
Since there is typically only one individual making the purchasing decision, B2C signups are virtually always self-service with reduced recurring fees. Since there is typically no outbound sales staff in B2C, acquisition costs are significantly lower than in B2B.
User Characteristics for B2B vs. B2C
Consider where your niche's users congregate if you don't already have a presence there.
B2B users frequent LinkedIn and Twitter. B2C users are on Facebook/Instagram/Reddit/Twitter, etc.
Churn is higher in B2C because consumers haven't gone through all the hoops of a B2B sale. Consumers are more unpredictable than businesses since they let their bank cards exceed limitations or don't update them when they expire.
With a B2B solution, there's a contractual arrangement and the firm will pay the subscription as long as they need it.
Depending on how you feel about the above (sales team vs. income vs. churn vs. targeting), you'll know which niches to pursue.
You ought to respect potential customers.
Would you hang out with customers?
You'll connect with users at conferences (in-person or virtual), webinars, seminars, screenshares, Facebook groups, emails, support calls, support tickets, etc.
If talking to a niche's user base makes you shudder, you're in for a tough road. Whether they're demanding or dull, avoid them if possible.
Merch users are mostly graphic designers, side hustlers, and entrepreneurs. These laid-back users embrace technologies that assist develop their Merch business.
I discovered there was only one annual conference for this specialty, held in Seattle, USA. I decided to organize a conference for UK/European Merch designers, despite never having done so before.
Hosting a conference for over 80 people was stressful, and it turned out to be much bigger than expected, with attendees from the US, Europe, and the UK.
I met many specialized users, built relationships, gained trust, and picked their brains in person. Many of the attendees were already Merch Wizard users, so hearing their feedback and ideas for future features was invaluable.
focused and specific
Instead of building for a generic, hard-to-reach market, target a specific group.
I liken it to fishing in a little, hidden pond. This small pond has only one species of fish, so you learn what bait it likes. Contrast that with trawling for hours to catch as many fish as possible, even if some aren't what you want.
In the case management scenario, it's difficult to target leads because several niches could use the app. Where do your potential customers hang out? Your generic solution: No.
It's easier to join a community of Real Estate Lawyers and see if your software can answer their pain points.
My Success with Micro SaaS
In my case, my Micro SaaS apps have been my chrome extensions. Since I launched them, they've earned me an average $10k MRR, allowing me to quit my lousy full-time job years ago.
I sold my apps after scaling them for a life-changing lump amount. Since then, I've helped unfulfilled software developers escape the 9-5 through Micro SaaS.
Whether it's a profitable side hustle or a liferaft to quit their job and become their own Micro SaaS boss.
Having built my apps to the point where I could quit my job, then scaled and sold them, I feel I can share my skills with software developers worldwide.
Read my free guide on self-funded SaaS to discover more about Micro SaaS, or download your own copy. 12 chapters cover everything from Idea to Exit.
Watch my YouTube video to learn how to construct a Micro SaaS app in 10 steps.
INTΞGRITY team
3 years ago
Privacy Policy
Effective date: August 31, 2022
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The California Consumer Privacy Act, or "CCPA" (Cal. Civ. Code 1798.100 et seq. ), grants California residents some rights regarding their personal data. If you are a California resident, you are subject to this clause.
We have collected the following categories of personal information over the past year: identifiers, commercial information, internet or other electronic network activity information, and conclusions. Please refer to the section titled "Collection of Information" for specifics regarding the data points we gather and the sorts of sources from which we acquire them. We collect personal information for the business and marketing purposes outlined in the section on Use of Information. In the past 12 months, we have shared the following types of personal information to the following groups of recipients for business purposes:
Category of Personal Information: Identifiers
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Categories of Recipients: Analytics Providers, Infrastructure Providers
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We retain the personal information associated with your account so long as your account is active. If you close your account, your account information will be deleted within 14 days. We retain other personal data for as long as is required to fulfill the objectives for which it was obtained and for other legitimate business purposes, such as to meet our legal, regulatory, or other compliance responsibilities.
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CONTACT US
Please contact us at hello@int3grity.com if you have any queries regarding this Privacy Statement.

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.
