This could cost you.

Content creators may have heard about Google's "Helpful content upgrade."

This change is another Google effort to remove low-quality, repetitive, and AI-generated content.

Why should content creators care?

Because too much content manipulates search results.

My experience includes the following.

Website admins seek high-quality guest posts from me. They send me AI-generated text after I say "yes." My readers are irrelevant. Backlinks are needed.

Companies copy high-ranking content to boost their Google rankings. Unfortunately, it's common.

What does this content offer?

Nothing.

Despite Google's updates and efforts to clean search results, webmasters create manipulative content.

As a marketer, I knew about AI-powered content generation tools. However, I've never tried them.

I use old-fashioned content creation methods to grow my website from 0 to 3,000 monthly views in one year.

Last year, I launched a niche website.

I do keyword research, analyze search intent and competitors' content, write an article, proofread it, and then optimize it.

This strategy is time-consuming.

But it yields results!

Here's proof from Google Analytics:

Proven strategies yield promising results.

To validate my assumptions and find new strategies, I run many experiments.

I tested an AI-powered content generator.

I used a tool to write this Google-optimized article about SEO for startups.

I wanted to analyze AI-generated content's Google performance.

Here are the outcomes of my test.

First, quality.

I dislike "meh" content. I expect articles to answer my questions. If not, I've wasted my time.

My essays usually include research, personal anecdotes, and what I accomplished and achieved.

AI-generated articles aren't as good because they lack individuality.

Read my AI-generated article about startup SEO to see what I mean.

It's dry and shallow, IMO.

It seems robotic.

I'd use quotes and personal experience to show how SEO for startups is different.

My article paraphrases top-ranked articles on a certain topic.

It's readable but useless. Similar articles abound online. Why read it?

AI-generated content is low-quality.

Let me show you how this content ranks on Google.

The Google Search Console report shows impressions, clicks, and average position.

Low numbers.

No one opens the 5th Google search result page to read the article. Too far!

You may say the new article will improve.

Marketing-wise, I doubt it.

This article is shorter and less comprehensive than top-ranking pages. It's unlikely to win because of this.

AI-generated content's terrible reality.

I'll compare how this content I wrote for readers and SEO performs.

Both the AI and my article are fresh, but trends are emerging.

My article's CTR and average position are higher.

I spent a week researching and producing that piece, unlike AI-generated content. My expert perspective and unique consequences make it interesting to read.

Human-made.

In summary

No content generator can duplicate a human's tone, writing style, or creativity. Artificial content is always inferior.

Not "bad," but inferior.

Demand for content production tools will rise despite Google's efforts to eradicate thin content.

Most won't spend hours producing link-building articles. Costly.

As guest and sponsored posts, artificial content will thrive.

Before accepting a new arrangement, content creators and website owners should consider this.

In this article, I'll describe a weekend project I started to make something. It was Product Hunt's #1 of the Day, #2 Weekly, and #4 Monthly product.

How did I make Landing Page Checklist so simple? Building and launching took 3 weeks. I worked 3 hours a day max. Weekends were busy.

It's sort of a long story, so scroll to the bottom of the page to see what tools I utilized to create Landing Page Checklist :x ‍

As a matter of fact, it all started with the startups-investments blog; Startup Bulletin, that I started writing in 2018. No, don’t worry, I won’t be going that far behind. The twitter account where I shared the blog posts of this newsletter was inactive for a looong time. I was holding this Twitter account since 2009, I couldn’t bear to destroy it. At the same time, I was thinking how to evaluate this account.

So I looked for a weekend assignment.

Weekend undertaking: Generate business names

Barash and I established a weekend effort to stay current. Building things helped us learn faster.

Simple. Startup Name Generator The utility generated random startup names. After market research for SEO purposes, we dubbed it Business Name Generator.

Backend developer Barash dislikes frontend work. He told me to write frontend code. Chakra UI and Tailwind CSS were recommended.

It was the first time I have heard about Tailwind CSS.

Before this project, I made mobile-web app designs in Sketch and shared them via Zeplin. I can read HTML-CSS or React code, but not write it. I didn't believe myself but followed Barash's advice.

My home page wasn't responsive when I started. Here it was:)

And then... Product Hunt had something I needed. Me-only! A website builder that gives you clean Tailwind CSS code and pre-made web components (like Elementor). Incredible.

I bought it right away because it was so easy to use. Best part: It's not just index.html. It includes all needed files. Like

• postcss.config.js

• README.md

• package.json

• among other things, tailwind.config.js

This is for non-techies.

Tailwind.build; which is Shuffle now, allows you to create and export projects for free (with limited features). You can try it by visiting their website.

After downloading the project, you can edit the text and graphics in Visual Studio (or another text editor). This HTML file can be hosted whenever.

Github is an easy way to host a landing page.

1. your project via Shuffle for export

2. your website's content, edit

3. Create a Gitlab, Github, or Bitbucket account.

4. to Github, upload your project folder.

5. Integrate Vercel with your Github account (or another platform below)

6. Allow them to guide you in steps.

Finally. If you push your code to Github using Github Desktop, you'll do it quickly and easily.

Speaking of; here are some hosting and serverless backend services for web applications and static websites for you host your landing pages for FREE!

I host landingpage.fyi on Vercel but all is fine. You can choose any platform below with peace in mind.

• Vercel

• Render

• Netlify

After connecting your project/repo to Vercel, you don’t have to do anything on Vercel. Vercel updates your live website when you update Github Desktop. Wow!

Tails came out while I was using tailwind.build. Although it's prettier, tailwind.build is more mobile-friendly. I couldn't resist their lovely parts. Tails :)

Tails have several well-designed parts. Some components looked awful on mobile, but this bug helped me understand Tailwind CSS.

Unlike Shuffle, Tails does not include files when you export such as config.js, main.js, README.md. It just gives you the HTML code. Suffle.dev is a bit ahead in this regard and with mobile-friendly blocks if you ask me. Of course, I took advantage of both.

creativebusinessnames.co is inactive, but I'll leave a deployment link :)

Adam Wathan's YouTube videos and Tailwind's official literature helped me, but I couldn't have done it without Tails and Shuffle. These tools helped me make landing pages. I shouldn't have started over.

So began my Tailwind CSS adventure. I didn't build landingpage. I didn't plan it to be this long; sorry.

I learnt a lot while I was playing around with Shuffle and Tails Builders.

Long story short I built landingpage.fyi with the help of these tools;

Learning, building, and distribution

• tailwindcss.com/docs

• Shuffle (Started with a Shuffle Template)

• Tails (Used components from here)

• Sketch (to handle icons, logos, and .svg’s)

• metatags.io (Auto Generator Meta Tags)

• Vercel (Hosting)

• Github Desktop (Pushing code to Github -super easy-)

• Visual Studio Code (Edit my code)

• Mailerlite (Capture Emails)

• Google Analytics

• Jarvis / Conversion.ai (%90 of the text on website written by AI 😇 )

• CookieHub (Consent Management)

That's all. A few things:

The Outcome

.fyi Domain: Why?

I'm often asked this.

I don't know, but I wanted to include the landing page term. Popular TLDs are gone. I saw my alternatives. brief and catchy.

CSS Tailwind Resources

I'll share project resources like Tails and Shuffle.

• Wicked Templates

• TailwindCSS Buttons

• Blocks | Wicked Templates

• nine4

• TUK — Tailwind UI KIT

• HyperUI

• Lofi UI

• Beginner Tailwind (I lately enrolled in this course but haven’t completed it yet.)

Thanks for reading my blog's first post. Please share if you like it.

Digital influences that mimic humans are rising.

Lil Miquela has 3M Instagram followers, 3.6M TikTok followers, and 30K Twitter followers. She's been on the covers of Prada, Dior, and Calvin Klein magazines. Miquela released Not Mine in 2017 and launched Hard Feelings at Lollapazoolas this year. This isn't surprising, given the rise of influencer marketing.

This may be unexpected. Miquela's fake. Brud, a Los Angeles startup, produced her in 2016.

Lil Miquela is one of many rising virtual influencers in the new era of social media marketing. She acts like a real person and performs the same tasks as sports stars and models.

The emergence of online influencers

Before 2018, computer-generated characters were rare. Since the virtual human industry boomed, they've appeared in marketing efforts worldwide.

In 2020, the WHO partnered up with Atlanta-based virtual influencer Knox Frost (@knoxfrost) to gather contributions for the COVID-19 Solidarity Response Fund.

Lu do Magalu (@magazineluiza) has been the virtual spokeswoman for Magalu since 2009, using social media to promote reviews, product recommendations, unboxing videos, and brand updates. Magalu's 10-year profit was $552M.

In 2020, PUMA partnered with Southeast Asia's first virtual model, Maya (@mayaaa.gram). She joined Singaporean actor Tosh Zhang in the PUMA campaign. Local virtual influencer Ava Lee-Graham (@avagram.ai) partnered with retail firm BHG to promote their in-house labels.

In Japan, Imma (@imma.gram) is the face of Nike, PUMA, Dior, Salvatore Ferragamo SpA, and Valentino. Imma's bubblegum pink bob and ultra-fine fashion landed her on the cover of Grazia magazine.

Lotte Home Shopping created Lucy (@here.me.lucy) in September 2020. She made her TV debut as a Christmas show host in 2021. Since then, she has 100K Instagram followers and 13K TikTok followers.

Liu Yiexi gained 3 million fans in five days on Douyin, China's TikTok, in 2021. Her two-minute video went viral overnight. She's posted 6 videos and has 830 million Douyin followers.

China's virtual human industry was worth $487 million in 2020, up 70% year over year, and is expected to reach $875.9 million in 2021.

Investors worldwide are interested. Immas creator Aww Inc. raised $1 million from Coral Capital in September 2020, according to Bloomberg. Superplastic Inc., the Vermont-based startup behind influencers Janky and Guggimon, raised $16 million by 2020. Craft Ventures, SV Angels, and Scooter Braun invested. Crunchbase shows the company has raised $47 million.

The industries they represent, including Augmented and Virtual reality, were worth $14.84 billion in 2020 and are projected to reach $454.73 billion by 2030, a CAGR of 40.7%, according to PR Newswire.

Advantages for brands

Forbes suggests brands embrace computer-generated influencers. Examples:

1. Unlimited creative opportunities: Because brands can personalize everything—from a person's look and activities to the style of their content—virtual influencers may be suited to a brand's needs and personalities.

2. 100% brand control: Brand managers now have more influence over virtual influencers, so they no longer have to give up and rely on content creators to include brands into their storytelling and style. Virtual influencers can constantly produce social media content to promote a brand's identity and ideals because they are completely scandal-free.

3. Long-term cost savings: Because virtual influencers are made of pixels, they may be reused endlessly and never lose their beauty. Additionally, they can move anywhere around the world and even into space to fit a brand notion. They are also always available. Additionally, the expense of creating their content will not rise in step with their expanding fan base.

4. Introduction to the metaverse: Statista reports that 75% of American consumers between the ages of 18 and 25 follow at least one virtual influencer. As a result, marketers that support virtual celebrities may now interact with younger audiences that are more tech-savvy and accustomed to the digital world. Virtual influencers can be included into any digital space, including the metaverse, as they are entirely computer-generated 3D personas. Virtual influencers can provide brands with a smooth transition into this new digital universe to increase brand trust and develop emotional ties, in addition to the young generations' rapid adoption of the metaverse.

5. Better engagement than in-person influencers: A Hype Auditor study found that online influencers have roughly three times the engagement of their conventional counterparts. Virtual influencers should be used to boost brand engagement even though the data might not accurately reflect the entire sector.

Concerns about influencers created by computers

Virtual influencers could encourage excessive beauty standards in South Korea, which has a $10.7 billion plastic surgery industry.

A classic Korean beauty has a small face, huge eyes, and pale, immaculate skin. Virtual influencers like Lucy have these traits. According to Lee Eun-hee, a professor at Inha University's Department of Consumer Science, this could make national beauty standards more unrealistic, increasing demand for plastic surgery or cosmetic items.

Other parts of the world raise issues regarding selling items to consumers who don't recognize the models aren't human and the potential of cultural appropriation when generating influencers of other ethnicities, called digital blackface by some.

Meta, Facebook and Instagram's parent corporation, acknowledges this risk.

“Like any disruptive technology, synthetic media has the potential for both good and harm. Issues of representation, cultural appropriation and expressive liberty are already a growing concern,” the company stated in a blog post. “To help brands navigate the ethical quandaries of this emerging medium and avoid potential hazards, (Meta) is working with partners to develop an ethical framework to guide the use of (virtual influencers).”

Despite theoretical controversies, the industry will likely survive. Companies think virtual influencers are the next frontier in the digital world, which includes the metaverse, virtual reality, and digital currency.

In conclusion

Virtual influencers may garner millions of followers online and help marketers reach youthful audiences. According to a YouGov survey, the real impact of computer-generated influencers is yet unknown because people prefer genuine connections. Virtual characters can supplement brand marketing methods. When brands are metaverse-ready, the author predicts virtual influencer endorsement will continue to expand.

Higher startup valuations are often favorable for all parties. High valuations show a business's potential. New customers and talent are attracted. They earn respect.

Everyone benefits if a company's valuation rises.

Founders and investors have always been incentivized to overestimate a company's value.

Post-money valuations were inflated by 2021 market expectations and the valuation model's mechanisms.

Founders must understand both levers to handle a normalizing market.

2021, the year of miracles

2021 must've seemed miraculous to entrepreneurs, employees, and VCs. Valuations rose, and funding resumed after the first Covid-19 epidemic caution.

In 2021, VC investments increased from $335B to $643B. 518 new worldwide unicorns vs. 134 in 2020; 951 US IPOs vs. 431.

Things can change quickly, as 2020-21 showed.

Rising interest rates, geopolitical developments, and normalizing technology conditions drive down share prices and tech company market caps in 2022. Zoom, the poster-child of early lockdown success, is down 37% since 1st Jan.

Once-inflated valuations can become a problem in a normalizing market, especially for founders, employees, and early investors.

the reason why startups are always overvalued

To see why inflated valuations are a problem, consider one of its causes.

Private company values only fluctuate following a new investment round, unlike publicly-traded corporations. The startup's new value is calculated simply:

(Latest round share price) x (total number of company shares)

This is the industry standard Post-Money Valuation model.

Let’s illustrate how it works with an example. If a VC invests $10M for 1M shares (at $10/share), and the company has 10M shares after the round, its Post-Money Valuation is $100M (10/share x 10M shares).

This approach might seem like the most natural way to assess a business, but the model often unintentionally overstates the underlying value of the company even if the share price paid by the investor is fair. All shares aren't equal.

New investors in a corporation will always try to minimize their downside risk, or the amount they lose if things go wrong. New investors will try to negotiate better terms and pay a premium.

How the value of a struggling SpaceX increased

SpaceX's 2008 Series D is an example. Despite the financial crisis and unsuccessful rocket launches, the company's Post-Money Valuation was 36% higher after the investment round. Why?

Series D SpaceX shares were protected. In case of liquidation, Series D investors were guaranteed a 2x return before other shareholders.

Due to downside protection, investors were willing to pay a higher price for this new share class.

The Post-Money Valuation model overpriced SpaceX because it viewed all the shares as equal (they weren't).

Why entrepreneurs, workers, and early investors stand to lose the most

Post-Money Valuation is an effective and sufficient method for assessing a startup's valuation, despite not taking share class disparities into consideration.

In a robust market, where the firm valuation will certainly expand with the next fundraising round or exit, the inflated value is of little significance.

Fairness endures. If a corporation leaves at a greater valuation, each stakeholder will receive a proportional distribution. (i.e., 5% of a $100M corporation yields $5M).

SpaceX's inherent overvaluation was never a problem. Had it been sold for less than its Post-Money Valuation, some shareholders, including founders, staff, and early investors, would have seen their ownership drop.

The unforgiving world of 2022

In 2022, founders, employees, and investors who benefited from inflated values will face below-valuation exits and down-rounds.

For them, 2021 will be a curse, not a blessing.

Some tech giants are worried. Klarna's valuation fell from $45B (Oct 21) to $30B (Jun 22), Canvas from $40B to $27B, and GoPuffs from $17B to $8.3B.

Shazam and Blue Apron have to exit or IPO at a cheaper price. Premium share classes are protected, while others receive less. The same goes for bankrupts.

Those who continue at lower valuations will lose reputation and talent. When their value declines by half, generous employee stock options become less enticing, and their ability to return anything is questioned.

What can we infer about the present situation?

Such techniques to enhance your company's value or stop a normalizing market are fiction.

The current situation is a painful reminder for entrepreneurs and a crucial lesson for future firms.

The devastating market fall of the previous six months has taught us one thing:

1. Keep in mind that any valuation is speculative. Money Post A startup's valuation is a highly simplified approximation of its true value, particularly in the early phases when it lacks significant income or a cutting-edge product. It is merely a projection of the future and a hypothetical meter. Until it is achieved by an exit, a valuation is nothing more than a number on paper.
   

2. Assume the value of your company is lower than it was in the past. Your previous valuation might not be accurate now due to substantial changes in the startup financing markets. There is little reason to think that your company's value will remain the same given the 50%+ decline in many newly listed IT companies. Recognize how the market situation is changing and use caution.
   

3. Recognize the importance of the stake you hold. Each share class has a unique value that varies. Know the sort of share class you own and how additional contractual provisions affect the market value of your security. Frameworks have been provided by Metrick and Yasuda (Yale & UC) and Gornall and Strebulaev (Stanford) for comprehending the terms that affect investors' cash-flow rights upon withdrawal. As a result, you will be able to more accurately evaluate your firm and determine the worth of each share class.
   

4. Be wary of approving excessively protective share terms.
   The trade-offs should be considered while negotiating subsequent rounds. Accepting punitive contractual terms could first seem like a smart option in order to uphold your inflated worth, but you should proceed with caution. Such provisions ALWAYS result in misaligned shareholders, with common shareholders (such as you and your staff) at the bottom of the list.

Non-technical talents can benefit data scientists in addition to statistics and programming.

As our article 5 Most In-Demand Skills for Data Scientists shows, being business-minded is useful. How can you get such a diverse skill set? We've compiled a list of helpful resources.

Data science, data analysis, programming, and business are covered. Even a few of these books will make you a better data scientist.

Ready? Let’s dive in.

Best books for data scientists

1. The Black Swan

Author: Nassim Taleb

First, a less obvious title. Nassim Nicholas Taleb's seminal series examines uncertainty, probability, risk, and decision-making.

Three characteristics define a black swan event:

• It is erratic.

• It has a significant impact.

• Many times, people try to come up with an explanation that makes it seem more predictable than it actually was.

People formerly believed all swans were white because they'd never seen otherwise. A black swan in Australia shattered their belief.

Taleb uses this incident to illustrate how human thinking mistakes affect decision-making. The book teaches readers to be aware of unpredictability in the ever-changing IT business.

Try multiple tactics and models because you may find the answer.

2. High Output Management

Author: Andrew Grove

Intel's former chairman and CEO provides his insights on developing a global firm in this business book. We think Grove would choose “management” to describe the talent needed to start and run a business.

That's a skill for CEOs, techies, and data scientists. Grove writes on developing productive teams, motivation, real-life business scenarios, and revolutionizing work.

Five lessons:

• Every action is a procedure.

• Meetings are a medium of work

• Manage short-term goals in accordance with long-term strategies.

• Mission-oriented teams accelerate while functional teams increase leverage.

• Utilize performance evaluations to enhance output.

So — if the above captures your imagination, it’s well worth getting stuck in.

3. The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers

Author: Ben Horowitz

Few realize how difficult it is to run a business, even though many see it as a tremendous opportunity.

Business schools don't teach managers how to handle the toughest difficulties; they're usually on their own. So Ben Horowitz wrote this book.

It gives tips on creating and maintaining a new firm and analyzes the hurdles CEOs face.

Find suggestions on:

• create software

• Run a business.

• Promote a product

• Obtain resources

• Smart investment

• oversee daily operations

This book will help you cope with tough times.

4. Obviously Awesome: How to Nail Product Positioning

Author: April Dunford

Your job as a data scientist is a product. You should be able to sell what you do to clients. Even if your product is great, you must convince them.

How to? April Dunford's advice: Her book explains how to connect with customers by making your offering seem like a secret sauce.

You'll learn:

• Select the ideal market for your products.

• Connect an audience to the value of your goods right away.

• Take use of three positioning philosophies.

• Utilize market trends to aid purchasers

5. The Mom test

Author: Rob Fitzpatrick

The Mom Test improves communication. Client conversations are rarely predictable. The book emphasizes one of the most important communication rules: enquire about specific prior behaviors.

Both ways work. If a client has suggestions or demands, listen carefully and ensure everyone understands. The book is packed with client-speaking tips.

6. Introduction to Machine Learning with Python: A Guide for Data Scientists

Authors: Andreas C. Müller, Sarah Guido

Now, technical documents.

This book is for Python-savvy data scientists who wish to learn machine learning. Authors explain how to use algorithms instead of math theory.

Their technique is ideal for developers who wish to study machine learning basics and use cases. Sci-kit-learn, NumPy, SciPy, pandas, and Jupyter Notebook are covered beyond Python.

If you know machine learning or artificial neural networks, skip this.

7. Python Data Science Handbook: Essential Tools for Working with Data

Author: Jake VanderPlas

Data work isn't easy. Data manipulation, transformation, cleansing, and visualization must be exact.

Python is a popular tool. The Python Data Science Handbook explains everything. The book describes how to utilize Pandas, Numpy, Matplotlib, Scikit-Learn, and Jupyter for beginners.

The only thing missing is a way to apply your learnings.

8. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

Author: Wes McKinney

The author leads you through manipulating, processing, cleaning, and analyzing Python datasets using NumPy, Pandas, and IPython.

The book's realistic case studies make it a great resource for Python or scientific computing beginners. Once accomplished, you'll uncover online analytics, finance, social science, and economics solutions.

9. Data Science from Scratch

Author: Joel Grus

Here's a title for data scientists with Python, stats, maths, and algebra skills (alongside a grasp of algorithms and machine learning). You'll learn data science's essential libraries, frameworks, modules, and toolkits.

The author works through all the key principles, providing you with the practical abilities to develop simple code. The book is appropriate for intermediate programmers interested in data science and machine learning.

Not that prior knowledge is required. The writing style matches all experience levels, but understanding will help you absorb more.

10. Machine Learning Yearning

Author: Andrew Ng

Andrew Ng is a machine learning expert. Co-founded and teaches at Stanford. This free book shows you how to structure an ML project, including recognizing mistakes and building in complex contexts.

The book delivers knowledge and teaches how to apply it, so you'll know how to:

• Determine the optimal course of action for your ML project.

• Create software that is more effective than people.

• Recognize when to use end-to-end, transfer, and multi-task learning, and how to do so.

• Identifying machine learning system flaws

Ng writes easy-to-read books. No rigorous math theory; just a terrific approach to understanding how to make technical machine learning decisions.

11. Deep Learning with PyTorch Step-by-Step

Author: Daniel Voigt Godoy

The last title is also the most recent. The book was revised on 23 January 2022 to discuss Deep Learning and PyTorch, a Python coding tool.

It comprises four parts:

1. Fundamentals (gradient descent, training linear and logistic regressions in PyTorch)

2. Machine Learning (deeper models and activation functions, convolutions, transfer learning, initialization schemes)

3. Sequences (RNN, GRU, LSTM, seq2seq models, attention, self-attention, transformers)

4. Automatic Language Recognition (tokenization, embeddings, contextual word embeddings, ELMo, BERT, GPT-2)

We admire the book's readability. The author avoids difficult mathematical concepts, making the material feel like a conversation.

Is every data scientist a humanist?

Even as a technological professional, you can't escape human interaction, especially with clients.

We hope these books will help you develop interpersonal skills.

On January 1, "Public Domain Day," thousands of creative works immediately join the public domain. The original creator or copyright holder loses exclusive rights to reproduce, adapt, or publish the work, and anybody can use it. It happens with movies, poems, music, artworks, books (where creative rights endure 70 years beyond the author's death), and sometimes source code.

Public domain creative works open the door to new uses. 400,000 sound recordings from before 1923, including Winnie-the-Pooh, were released this year.  With most of A.A. Milne's 1926 Winnie-the-Pooh characters now available, we're seeing innovative interpretations Milne likely never planned. The ancient hyphenated version of the honey-loving bear is being adapted for a horror movie: "Winnie-the-Pooh: Blood and Honey"... with Pooh and Piglet as the baddies.

Counterintuitively, experimenting and recombination can occasionally increase IP value. Open source movements allow the public to build on (or fork and duplicate) existing technologies. Permissionless innovation helps Android, Linux, and other open source software projects compete. Crypto's success at attracting public development is also due to its support of open source and "remix culture," notably in NFT forums.

Production memes

NFT projects use several IP strategies to establish brands, communities, and content. Some preserve regular IP protections; others offer NFT owners the opportunity to innovate on connected IP; yet others have removed copyright and other IP safeguards.

By using the "Creative Commons Zero" (cc0) license, artists can intentionally select for "no rights reserved." This option permits anyone to benefit from derivative works without legal repercussions. There's still a lot of confusion between copyrights and NFTs, so nothing here should be considered legal, financial, tax, or investment advice. Check out this post for an overview of copyright vulnerabilities with NFTs and how authors can protect owners' rights. This article focuses on cc0.

Nouns, a 2021 project, popularized cc0 for NFTs. Others followed, including: A Common Place, Anonymice, Blitmap, Chain Runners, Cryptoadz, CryptoTeddies, Goblintown, Gradis, Loot, mfers, Mirakai, Shields, and Terrarium Club are cc0 projects.

Popular crypto artist XCOPY licensed their 1-of-1 NFT artwork "Right-click and Save As Guy" under cc0 in January, exactly one month after selling it. cc0 has spawned many derivatives.

"Right-click Save As Guy" by XCOPY (1)/derivative works (2)

XCOPY said Monday he would apply cc0 to "all his existing art." "We haven't seen a cc0 summer yet, but I think it's approaching," said the artist. - predicting a "DeFi summer" in 2020, when decentralized finance gained popularity.

Why do so many NFT authors choose "no rights"?

Promoting expansions of the original project to create a more lively and active community is one rationale. This makes sense in crypto, where many value open sharing and establishing community.

Creativity depends on cultural significance. NFTs may allow verifiable ownership of any digital asset, regardless of license, but cc0 jumpstarts "meme-ability" by actively, not passively, inviting derivative works. As new derivatives are made and shared, attention might flow back to the original, boosting its reputation. This may inspire new interpretations, leading in a flywheel effect where each derivative adds to the original's worth - similar to platform network effects, where platforms become more valuable as more users join them.

cc0 licence allows creators "seize production memes."

"SEASON 1 MEME CARD 2"

Physical items are also using cc0 NFT assets, thus it's not just a digital phenomenon. The Nouns Vision initiative turned the square-framed spectacles shown on each new NounsDAO NFT ("one per day, forever") into luxury sunglasses. Blitmap's pixel-art has been used on shoes, apparel, and caps. In traditional IP regimes, a single owner controls creation, licensing, and production.

The physical "blitcap" (3rd level) is a descendant of the trait in the cc0 Chain Runners collection (2nd), which uses the "logo" from cc0 Blitmap (1st)! The Logo is Blitmap token #84 and has been used as a trait in various collections. The "Dom Rose" is another popular token. These homages reference Blitmap's influence as a cc0 leader, as one of the earliest NFT projects to proclaim public domain intents. A new collection, Citizens of Tajigen, emerged last week with a Blitcap characteristic.

These derivatives can be a win-win for everyone, not just the original inventors, especially when using NFT assets to establish unique brands. As people learn about the derivative, they may become interested in the original. If you see someone wearing Nouns glasses on the street (or in a Super Bowl ad), you may desire a pair, but you may also be interested in buying an original NounsDAO NFT or related derivative.

Blitmap Logo Hat (1), Chain Runners #780 ft. Hat (2), and Blitmap Original "Logo #87" (3)

Co-creating open source

NFTs' power comes from smart contract technology's intrinsic composability. Many smart contracts can be integrated or stacked to generate richer applications.

"Money Legos" describes how decentralized finance ("DeFi") smart contracts interconnect to generate new financial use cases. Yearn communicates with MakerDAO's stablecoin $DAI and exchange liquidity provider Curve by calling public smart contract methods. NFTs and their underlying smart contracts can operate as the base-layer framework for recombining and interconnecting culture and creativity.

cc0 gives an NFT's enthusiast community authority to develop new value layers whenever, wherever, and however they wish.

Multiple cc0 projects are playable characters in HyperLoot, a Loot Project knockoff.

Open source and Linux's rise are parallels. When the internet was young, Microsoft dominated the OS market with Windows. Linux (and its developer Linus Torvalds) championed a community-first mentality, freely available the source code without restrictions. This led to developers worldwide producing new software for Linux, from web servers to databases. As people (and organizations) created world-class open source software, Linux's value proposition grew, leading to explosive development and industry innovation. According to Truelist, Linux powers 96.3% of the top 1 million web servers and 85% of smartphones.

With cc0 licensing empowering NFT community builders, one might hope for long-term innovation. Combining cc0 with NFTs "turns an antagonistic game into a co-operative one," says NounsDAO cofounder punk4156. It's important on several levels. First, decentralized systems from open source to crypto are about trust and coordination, therefore facilitating cooperation is crucial. Second, the dynamics of this cooperation work well in the context of NFTs because giving people ownership over their digital assets allows them to internalize the results of co-creation through the value that accrues to their assets and contributions, which incentivizes them to participate in co-creation in the first place.

Licensed to create

If cc0 projects are open source "applications" or "platforms," then NFT artwork, metadata, and smart contracts provide the "user interface" and the underlying blockchain (e.g., Ethereum) is the "operating system." For these apps to attain Linux-like potential, more infrastructure services must be established and made available so people may take advantage of cc0's remixing capabilities.

These services are developing. Zora protocol and OpenSea's open source Seaport protocol enable open, permissionless NFT marketplaces. A pixel-art-rendering engine was just published on-chain to the Ethereum blockchain and integrated into OKPC and ICE64. Each application improves blockchain's "out-of-the-box" capabilities, leading to new apps created from the improved building blocks.

Web3 developer growth is at an all-time high, yet it's still a small fraction of active software developers globally. As additional developers enter the field, prospective NFT projects may find more creative and infrastructure Legos for cc0 and beyond.

Electric Capital Developer Report (2021), p. 122

Growth requires composability. Users can easily integrate digital assets developed on public standards and compatible infrastructure into other platforms. The Loot Project is one of the first to illustrate decentralized co-creation, worldbuilding, and more in NFTs. This example was low-fi or "incomplete" aesthetically, providing room for imagination and community co-creation.

Loot began with a series of Loot bag NFTs, each listing eight "adventure things" in white writing on a black backdrop (such as Loot Bag #5726's "Katana, Divine Robe, Great Helm, Wool Sash, Divine Slippers, Chain Gloves, Amulet, Gold Ring"). Dom Hofmann's free Loot bags served as a foundation for the community.

Several projects have begun metaphorical (lore) and practical (game development) world-building in a short time, with artists contributing many variations to the collective "Lootverse." They've produced games (Realms & The Crypt), characters (Genesis Project, Hyperloot, Loot Explorers), storytelling initiatives (Banners, OpenQuill), and even infrastructure (The Rift).

Why cc0 and composability? Because consumers own and control Loot bags, they may use them wherever they choose by connecting their crypto wallets. This allows users to participate in multiple derivative projects, such as  Genesis Adventurers, whose characters appear in many others — creating a decentralized franchise not owned by any one corporation.

Genesis Project's Genesis Adventurer (1) with HyperLoot (2) and Loot Explorer (3) versions

When to go cc0

There are several IP development strategies NFT projects can use. When it comes to cc0, it’s important to be realistic. The public domain won't make a project a runaway success just by implementing the license. cc0 works well for NFT initiatives that can develop a rich, enlarged ecosystem.

Many of the most successful cc0 projects have introduced flexible intellectual property. The Nouns brand is as obvious for a beer ad as for real glasses; Loot bags are simple primitives that make sense in all adventure settings; and the Goblintown visual style looks good on dwarfs, zombies, and cranky owls as it does on Val Kilmer.

The ideal cc0 NFT project gives builders the opportunity to add value:

• vertically, by stacking new content and features directly on top of the original cc0 assets (for instance, as with games built on the Loot ecosystem, among others), and

• horizontally, by introducing distinct but related intellectual property that helps propagate the original cc0 project’s brand (as with various Goblintown derivatives, among others).

These actions can assist cc0 NFT business models. Because cc0 NFT projects receive royalties from secondary sales, third-party extensions and derivatives can boost demand for the original assets.

Using cc0 license lowers friction that could hinder brand-reinforcing extensions or lead to them bypassing the original. Robbie Broome recently argued (in the context of his cc0 project A Common Place) that giving away his IP to cc0 avoids bad rehashes down the line. If UrbanOutfitters wanted to put my design on a tee, they could use the actual work instead of hiring a designer. CC0 can turn competition into cooperation.

Community agreement about core assets' value and contribution can help cc0 projects. Cohesion and engagement are key. Using the above examples: Developers can design adventure games around whatever themes and item concepts they desire, but many choose Loot bags because of the Lootverse's community togetherness. Flipmap shared half of its money with the original Blitmap artists in acknowledgment of that project's core role in the community. This can build a healthy culture within a cc0 project ecosystem. Commentator NiftyPins said it was smart to acknowledge the people that constructed their universe. Many OG Blitmap artists have popped into the Flipmap discord to share information.

cc0 isn't a one-size-fits-all answer; NFTs formed around well-established brands may prefer more restrictive licenses to preserve their intellectual property and reinforce exclusivity. cc0 has some superficial similarities to permitting NFT owners to market the IP connected with their NFTs (à la Bored Ape Yacht Club), but there is a significant difference: cc0 holders can't exclude others from utilizing the same IP. This can make it tougher for holders to develop commercial brands on cc0 assets or offer specific rights to partners. Holders can still introduce enlarged intellectual property (such as backstories or derivatives) that they control.

Blockchain technologies and the crypto ethos are decentralized and open-source. This makes it logical for crypto initiatives to build around cc0 content models, which build on the work of the Creative Commons foundation and numerous open source pioneers.

NFT creators that choose cc0 must select how involved they want to be in building the ecosystem. Some cc0 project leaders, like Chain Runners' developers, have kept building on top of the initial cc0 assets, creating an environment derivative projects can plug into. Dom Hofmann stood back from Loot, letting the community lead. (Dom is also working on additional cc0 NFT projects for the company he formed to build Blitmap.) Other authors have chosen out totally, like sartoshi, who announced his exit from the cc0 project he founded, mfers, and from the NFT area by publishing a final edition suitably named "end of sartoshi" and then deactivating his Twitter account. A multi-signature wallet of seven mfers controls the project's smart contract. 

cc0 licensing allows a robust community to co-create in ways that benefit all members, regardless of original creators' continuous commitment. We foresee more organized infrastructure and design patterns as NFT matures. Like open source software, value capture frameworks may see innovation. (We could imagine a variant of the "Sleepycat license," which requires commercial software to pay licensing fees when embedding open source components.) As creators progress the space, we expect them to build unique rights and licensing strategies. cc0 allows NFT producers to bootstrap ideas that may take off.