Token taxonomy: Utility vs Security vs NFT
Let's examine the differences between the three main token types and their functions.
As Ethereum grew, the term "token" became a catch-all term for all assets built on the Ethereum blockchain. However, different tokens were grouped based on their applications and features, causing some confusion. Let's examine the modification of three main token types: security, utility, and non-fungible.
Utility tokens
They provide a specific utility benefit (or a number of such). A utility token is similar to a casino chip, a table game ticket, or a voucher. Depending on the terms of issuing, they can be earned and used in various ways. A utility token is a type of token that represents a tool or mechanism required to use the application in question. Like a service, a utility token's price is determined by supply and demand. Tokens can also be used as a bonus or reward mechanism in decentralized systems: for example, if you like someone's work, give them an upvote and they get a certain number of tokens. This is a way for authors or creators to earn money indirectly.
The most common way to use a utility token is to pay with them instead of cash for discounted goods or services.
Utility tokens are the most widely used by blockchain companies. Most cryptocurrency exchanges accept fees in native utility tokens.
Utility tokens can also be used as a reward. Companies tokenize their loyalty programs so that points can be bought and sold on blockchain exchanges. These tokens are widely used in decentralized companies as a bonus system. You can use utility tokens to reward creators for their contributions to a platform, for example. It also allows members to exchange tokens for specific bonuses and rewards on your site.
Unlike security tokens, which are subject to legal restrictions, utility tokens can be freely traded.
Security tokens
Security tokens are essentially traditional securities like shares, bonds, and investment fund units in a crypto token form.
The key distinction is that security tokens are typically issued by private firms (rather than public companies) that are not listed on stock exchanges and in which you can not invest right now. Banks and large venture funds used to be the only sources of funding. A person could only invest in private firms if they had millions of dollars in their bank account. Privately issued security tokens outperform traditional public stocks in terms of yield. Private markets grew 50% faster than public markets over the last decade, according to McKinsey Private Equity Research.
A security token is a crypto token whose value is derived from an external asset or company. So it is governed as security (read about the Howey test further in this article). That is, an ownership token derives its value from the company's valuation, assets on the balance sheet, or dividends paid to token holders.
Why are Security Tokens Important?
Cryptocurrency is a lucrative investment. Choosing from thousands of crypto assets can mean the difference between millionaire and bankrupt. Without security tokens, crypto investing becomes riskier and generating long-term profits becomes difficult. These tokens have lower risk than other cryptocurrencies because they are backed by real assets or business cash flows. So having them helps to diversify a portfolio and preserve the return on investment in riskier assets.
Security tokens open up new funding avenues for businesses. As a result, investors can invest in high-profit businesses that are not listed on the stock exchange.
The distinction between utility and security tokens isn't as clear as it seems. However, this increases the risk for token issuers, especially in the USA. The Howey test is the main pillar regulating judicial precedent in this area.
What is a Howey Test?
An "investment contract" is determined by the Howey Test, a lawsuit settled by the US Supreme Court. If it does, it's a security and must be disclosed and registered under the Securities Act of 1933 and the Securities Exchange Act of 1934.
If the SEC decides that a cryptocurrency token is a security, a slew of issues arise. In practice, this ensures that the SEC will decide when a token can be offered to US investors and if the project is required to file a registration statement with the SEC.
Due to the Howey test's extensive wording, most utility tokens will be classified as securities, even if not intended to be. Because of these restrictions, most ICOs are not available to US investors. When asked about ICOs in 2018, then-SEC Chairman Jay Clayton said they were securities. The given statement adds to the risk. If a company issues utility tokens without registering them as securities, the regulator may impose huge fines or even criminal charges.
What other documents regulate tokens?
Securities Act (1993) or Securities Exchange Act (1934) in the USA; MiFID directive and Prospectus Regulation in the EU. These laws require registering the placement of security tokens, limiting their transfer, but protecting investors.
Utility tokens have much less regulation. The Howey test determines whether a given utility token is a security. Tokens recognized as securities are now regulated as such. Having a legal opinion that your token isn't makes the implementation process much easier. Most countries don't have strict regulations regarding utility tokens except KYC (Know Your Client) and AML (Anti Money-Laundering).
As cryptocurrency and blockchain technologies evolve, more countries create UT regulations. If your company is based in the US, be aware of the Howey test and the Bank Secrecy Act. It classifies UTs and their issuance as money transmission services in most states, necessitating a license and strict regulations. Due to high regulatory demands, UT issuers try to avoid the United States as a whole. A new law separating utility tokens from bank secrecy act will be introduced in the near future, giving hope to American issuers.
The rest of the world has much simpler rules requiring issuers to create basic investor disclosures. For example, the latest European legislation (MiCA) allows businesses to issue utility tokens without regulator approval. They must also prepare a paper with all the necessary information for the investors.
A payment token is a utility token that is used to make a payment. They may be subject to electronic money laws.
Because non-fungible tokens are a new instrument, there is no regulating paper yet. However, if the NFT is fractionalized, the smaller tokens acquired may be seen as securities.
NFT Tokens
Collectible tokens are also known as non-fungible tokens. Their distinctive feature is that they denote unique items such as artwork, merch, or ranks. Unlike utility tokens, which are fungible, meaning that two of the same tokens are identical, NFTs represent a unit of possession that is strictly one of a kind. In a way, NFTs are like baseball cards, each one unique and valuable.
As for today, the most recognizable NFT function is to preserve the fact of possession. Owning an NFT with a particular gif, meme, or sketch does not transfer the intellectual right to the possessor, but is analogous to owning an original painting signed by the author.
Collectible tokens can also be used as digital souvenirs, so to say. Businesses can improve their brand image by issuing their own branded NFTs, which represent ranks or achievements within the corporate ecosystem. Gamifying business ecosystems would allow people to connect with a brand and feel part of a community.
Which type of tokens is right for you as a business to raise capital?
For most businesses, it's best to raise capital with security tokens by selling existing shares to global investors. Utility tokens aren't meant to increase in value over time, so leave them for gamification and community engagement. In a blockchain-based business, however, a utility token is often the lifeblood of the operation, and its appreciation potential is directly linked to the company's growth. You can issue multiple tokens at once, rather than just one type. It exposes you to various investors and maximizes the use of digital assets.
Which tokens should I buy?
There are no universally best tokens. Their volatility, industry, and risk-reward profile vary. This means evaluating tokens in relation to your overall portfolio and personal preferences: what industries do you understand best, what excites you, how do you approach taxes, and what is your planning horizon? To build a balanced portfolio, you need to know these factors.
Conclusion
The three most common types of tokens today are security, utility, and NFT. Security tokens represent stocks, mutual funds, and bonds. Utility tokens can be perceived as an inside-product "currency" or "ignition key" that grants you access to goods and services or empowers with other perks. NFTs are unique collectible units that identify you as the owner of something.
More on Web3 & Crypto
Crypto Zen Monk
2 years ago
How to DYOR in the world of cryptocurrency
RESEARCH
We must create separate ideas and handle our own risks to be better investors. DYOR is crucial.
The only thing unsustainable is your cluelessness.
DYOR: Why
On social media, there is a lot of false information and divergent viewpoints. All of these facts might be accurate, but they might not be appropriate for your portfolio and investment preferences.
You become a more knowledgeable investor thanks to DYOR.
DYOR improves your portfolio's risk management.
My DYOR resources are below.
Messari: Major Blockchains' Activities
New York-based Messari provides cryptocurrency open data libraries.
Major blockchains offer 24-hour on-chain volume. https://messari.io/screener/most-active-chains-DB01F96B
What to do
Invest in stable cryptocurrencies. Sort Messari by Real Volume (24H) or Reported Market Cap.
Coingecko: Research on Ecosystems
Top 10 Ecosystems by Coingecko are good.
What to do
Invest in quality.
Leading ten Ecosystems by Market Cap
There are a lot of coins in the ecosystem (second last column of above chart)
CoinGecko's Market Cap Crypto Categories Market capitalization-based cryptocurrency categories. Ethereum Ecosystem www.coingecko.com
Fear & Greed Index for Bitcoin (FGI)
The Bitcoin market sentiment index ranges from 0 (extreme dread) to 100. (extreme greed).
How to Apply
See market sentiment:
Extreme fright = opportunity to buy
Extreme greed creates sales opportunity (market due for correction).
Glassnode
Glassnode gives facts, information, and confidence to make better Bitcoin, Ethereum, and cryptocurrency investments and trades.
Explore free and paid metrics.
Stock to Flow Ratio: Application
The popular Stock to Flow Ratio concept believes scarcity drives value. Stock to flow is the ratio of circulating Bitcoin supply to fresh production (i.e. newly mined bitcoins). The S/F Ratio has historically predicted Bitcoin prices. PlanB invented this metric.
Utilization: Ethereum Hash Rate
Ethereum miners produce an estimated number of hashes per second.
ycharts: Hash rate of the Bitcoin network
TradingView
TradingView is your go-to tool for investment analysis, watch lists, technical analysis, and recommendations from other traders/investors.
Research for a cryptocurrency project
Two key questions every successful project must ask: Q1: What is this project trying to solve? Is it a big problem or minor? Q2: How does this project make money?
Each cryptocurrency:
Check out the white paper.
check out the project's internet presence on github, twitter, and medium.
the transparency of it
Verify the team structure and founders. Verify their LinkedIn profile, academic history, and other qualifications. Search for their names with scam.
Where to purchase and use cryptocurrencies Is it traded on trustworthy exchanges?
From CoinGecko and CoinMarketCap, we may learn about market cap, circulations, and other important data.
The project must solve a problem. Solving a problem is the goal of the founders.
Avoid projects that resemble multi-level marketing or ponzi schemes.
Your use of social media
Use social media carefully or ignore it: Twitter, TradingView, and YouTube
Someone said this before and there are some truth to it. Social media bullish => short.
Your Behavior
Investigate. Spend time. You decide. Worth it!
Only you have the best interest in your financial future.
Amelie Carver
3 years ago
Web3 Needs More Writers to Educate Us About It
WRITE FOR THE WEB3
Why web3’s messaging is lost and how crypto winter is growing growth seeds
People interested in crypto, blockchain, and web3 typically read Bitcoin and Ethereum's white papers. It's a good idea. Documents produced for developers and academia aren't always the ideal resource for beginners.
Given the surge of extremely technical material and the number of fly-by-nights, rug pulls, and other scams, it's little wonder mainstream audiences regard the blockchain sector as an expensive sideshow act.
What's the solution?
Web3 needs more than just builders.
After joining TikTok, I followed Amy Suto of SutoScience. Amy switched from TV scriptwriting to IT copywriting years ago. She concentrates on web3 now. Decentralized autonomous organizations (DAOs) are seeking skilled copywriters for web3.
Amy has found that web3's basics are easy to grasp; you don't need technical knowledge. There's a paradigm shift in knowing the basics; be persistent and patient.
Apple is positioning itself as a data privacy advocate, leveraging web3's zero-trust ethos on data ownership.
Finn Lobsien, who writes about web3 copywriting for the Mirror and Twitter, agrees: acronyms and abstractions won't do.
Web3 preached to the choir. Curious newcomers have only found whitepapers and scams when trying to learn why the community loves it. No wonder people resist education and buy-in.
Due to the gender gap in crypto (Crypto Bro is not just a stereotype), it attracts people singing to the choir or trying to cash in on the next big thing.
Last year, the industry was booming, so writing wasn't necessary. Now that the bear market has returned (for everyone, but especially web3), holding readers' attention is a valuable skill.
White papers and the Web3
Why does web3 rely so much on non-growth content?
Businesses must polish and improve their messaging moving into the 2022 recession. The 2021 tech boom provided such a sense of affluence and (unsustainable) growth that no one needed great marketing material. The market found them.
This was especially true for web3 and the first-time crypto believers. Obviously. If they knew which was good.
White papers help. White papers are highly technical texts that walk a reader through a product's details. How Does a White Paper Help Your Business and That White Paper Guy discuss them.
They're meant for knowledgeable readers. Investors and the technical (academic/developer) community read web3 white papers. White papers are used when a product is extremely technical or difficult to assist an informed reader to a conclusion. Web3 uses them most often for ICOs (initial coin offerings).
White papers for web3 education help newcomers learn about the web3 industry's components. It's like sending a first-grader to the Annotated Oxford English Dictionary to learn to read. It's a reference, not a learning tool, for words.
Newcomers can use platforms that teach the basics. These included Coinbase's Crypto Basics tutorials or Cryptochicks Academy, founded by the mother of Ethereum's inventor to get more women utilizing and working in crypto.
Discord and Web3 communities
Discord communities are web3's opposite. Discord communities involve personal communications and group involvement.
Online audience growth begins with community building. User personas prefer 1000 dedicated admirers over 1 million lukewarm followers, and the language is much more easygoing. Discord groups are renowned for phishing scams, compromised wallets, and incorrect information, especially since the crypto crisis.
White papers and Discord increase industry insularity. White papers are complicated, and Discord has a high risk threshold.
Web3 and writing ads
Copywriting is emotional, but white papers are logical. It uses the brain's quick-decision centers. It's meant to make the reader invest immediately.
Not bad. People think sales are sleazy, but they can spot the poor things.
Ethical copywriting helps you reach the correct audience. People who gain a following on Medium are likely to have copywriting training and a readership (or three) in mind when they publish. Tim Denning and Sinem Günel know how to identify a target audience and make them want to learn more.
In a fast-moving market, copywriting is less about long-form content like sales pages or blogs, but many organizations do. Instead, the copy is concise, individualized, and high-value. Tweets, email marketing, and IM apps (Discord, Telegram, Slack to a lesser extent) keep engagement high.
What does web3's messaging lack? As DAOs add stricter copyrighting, narrative and connecting tales seem to be missing.
Web3 is passionate about constructing the next internet. Now, they can connect their passion to a specific audience so newcomers understand why.
Trent Lapinski
3 years ago
What The Hell Is A Crypto Punk?
We are Crypto Punks, and we are changing your world.
A “Crypto Punk” is a new generation of entrepreneurs who value individual liberty and collective value creation and co-creation through decentralization. While many Crypto Punks were born and raised in a digital world, some of the early pioneers in the crypto space are from the Oregon Trail generation. They were born to an analog world, but grew up simultaneously alongside the birth of home computing, the Internet, and mobile computing.
A Crypto Punk’s world view is not the same as previous generations. By the time most Crypto Punks were born everything from fiat currency, the stock market, pharmaceuticals, the Internet, to advanced operating systems and microprocessing were already present or emerging. Crypto Punks were born into pre-existing conditions and systems of control, not governed by logic or reason but by greed, corporatism, subversion, bureaucracy, censorship, and inefficiency.
All Systems Are Human Made
Crypto Punks understand that all systems were created by people and that previous generations did not have access to information technologies that we have today. This is why Crypto Punks have different values than their parents, and value liberty, decentralization, equality, social justice, and freedom over wealth, money, and power. They understand that the only path forward is to work together to build new and better systems that make the old world order obsolete.
Unlike the original cypher punks and cyber punks, Crypto Punks are a new iteration or evolution of these previous cultures influenced by cryptography, blockchain technology, crypto economics, libertarianism, holographics, democratic socialism, and artificial intelligence. They are tasked with not only undoing the mistakes of previous generations, but also innovating and creating new ways of solving complex problems with advanced technology and solutions.
Where Crypto Punks truly differ is in their understanding that computer systems can exist for more than just engagement and entertainment, but actually improve the human condition by automating bureaucracy and inefficiency by creating more efficient economic incentives and systems.
Crypto Punks Value Transparency and Do Not Trust Flawed, Unequal, and Corrupt Systems
Crypto Punks have a strong distrust for inherently flawed and corrupt systems. This why Crypto Punks value transparency, free speech, privacy, and decentralization. As well as arguably computer systems over human powered systems.
Crypto Punks are the children of the Great Recession, and will never forget the economic corruption that still enslaves younger generations.
Crypto Punks were born to think different, and raised by computers to view reality through an LED looking glass. They will not surrender to the flawed systems of economic wage slavery, inequality, censorship, and subjection. They will literally engineer their own unstoppable financial systems and trade in cryptography over fiat currency merely to prove that belief systems are more powerful than corruption.
Crypto Punks are here to help achieve freedom from world governments, corporations and bankers who monetizine our data to control our lives.
Crypto Punks Decentralize
Despite all the evils of the world today, Crypto Punks know they have the power to create change. This is why Crypto Punks are optimistic about the future despite all the indicators that humanity is destined for failure.
Crypto Punks believe in systems that prioritize people and the planet above profit. Even so, Crypto Punks still believe in capitalistic systems, but only capitalistic systems that incentivize good behaviors that do not violate the common good for the sake of profit.
Cyber Punks Are Co-Creators
We are Crypto Punks, and we will build a better world for all of us. For the true price of creation is not in US dollars, but through working together as equals to replace the unequal and corrupt greedy systems of previous generations.
Where they have failed, Crypto Punks will succeed. Not because we want to, but because we have to. The world we were born into is so corrupt and its systems so flawed and unequal we were never given a choice.
We have to be the change we seek.
We are Crypto Punks.
Either help us, or get out of our way.
Are you a Crypto Punk?
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Dmitrii Eliuseev
2 years ago
Creating Images on Your Local PC Using Stable Diffusion AI
Deep learning-based generative art is being researched. As usual, self-learning is better. Some models, like OpenAI's DALL-E 2, require registration and can only be used online, but others can be used locally, which is usually more enjoyable for curious users. I'll demonstrate the Stable Diffusion model's operation on a standard PC.
Let’s get started.
What It Does
Stable Diffusion uses numerous components:
A generative model trained to produce images is called a diffusion model. The model is incrementally improving the starting data, which is only random noise. The model has an image, and while it is being trained, the reversed process is being used to add noise to the image. Being able to reverse this procedure and create images from noise is where the true magic is (more details and samples can be found in the paper).
An internal compressed representation of a latent diffusion model, which may be altered to produce the desired images, is used (more details can be found in the paper). The capacity to fine-tune the generation process is essential because producing pictures at random is not very attractive (as we can see, for instance, in Generative Adversarial Networks).
A neural network model called CLIP (Contrastive Language-Image Pre-training) is used to translate natural language prompts into vector representations. This model, which was trained on 400,000,000 image-text pairs, enables the transformation of a text prompt into a latent space for the diffusion model in the scenario of stable diffusion (more details in that paper).
This figure shows all data flow:
The weights file size for Stable Diffusion model v1 is 4 GB and v2 is 5 GB, making the model quite huge. The v1 model was trained on 256x256 and 512x512 LAION-5B pictures on a 4,000 GPU cluster using over 150.000 NVIDIA A100 GPU hours. The open-source pre-trained model is helpful for us. And we will.
Install
Before utilizing the Python sources for Stable Diffusion v1 on GitHub, we must install Miniconda (assuming Git and Python are already installed):
wget https://repo.anaconda.com/miniconda/Miniconda3-py39_4.12.0-Linux-x86_64.sh
chmod +x Miniconda3-py39_4.12.0-Linux-x86_64.sh
./Miniconda3-py39_4.12.0-Linux-x86_64.sh
conda update -n base -c defaults condaInstall the source and prepare the environment:
git clone https://github.com/CompVis/stable-diffusion
cd stable-diffusion
conda env create -f environment.yaml
conda activate ldm
pip3 install transformers --upgradeDownload the pre-trained model weights next. HiggingFace has the newest checkpoint sd-v14.ckpt (a download is free but registration is required). Put the file in the project folder and have fun:
python3 scripts/txt2img.py --prompt "hello world" --plms --ckpt sd-v1-4.ckpt --skip_grid --n_samples 1Almost. The installation is complete for happy users of current GPUs with 12 GB or more VRAM. RuntimeError: CUDA out of memory will occur otherwise. Two solutions exist.
Running the optimized version
Try optimizing first. After cloning the repository and enabling the environment (as previously), we can run the command:
python3 optimizedSD/optimized_txt2img.py --prompt "hello world" --ckpt sd-v1-4.ckpt --skip_grid --n_samples 1Stable Diffusion worked on my visual card with 8 GB RAM (alas, I did not behave well enough to get NVIDIA A100 for Christmas, so 8 GB GPU is the maximum I have;).
Running Stable Diffusion without GPU
If the GPU does not have enough RAM or is not CUDA-compatible, running the code on a CPU will be 20x slower but better than nothing. This unauthorized CPU-only branch from GitHub is easiest to obtain. We may easily edit the source code to use the latest version. It's strange that a pull request for that was made six months ago and still hasn't been approved, as the changes are simple. Readers can finish in 5 minutes:
Replace if attr.device!= torch.device(cuda) with if attr.device!= torch.device(cuda) and torch.cuda.is available at line 20 of ldm/models/diffusion/ddim.py ().
Replace if attr.device!= torch.device(cuda) with if attr.device!= torch.device(cuda) and torch.cuda.is available in line 20 of ldm/models/diffusion/plms.py ().
Replace device=cuda in lines 38, 55, 83, and 142 of ldm/modules/encoders/modules.py with device=cuda if torch.cuda.is available(), otherwise cpu.
Replace model.cuda() in scripts/txt2img.py line 28 and scripts/img2img.py line 43 with if torch.cuda.is available(): model.cuda ().
Run the script again.
Testing
Test the model. Text-to-image is the first choice. Test the command line example again:
python3 scripts/txt2img.py --prompt "hello world" --plms --ckpt sd-v1-4.ckpt --skip_grid --n_samples 1The slow generation takes 10 seconds on a GPU and 10 minutes on a CPU. Final image:
Hello world is dull and abstract. Try a brush-wielding hamster. Why? Because we can, and it's not as insane as Napoleon's cat. Another image:
Generating an image from a text prompt and another image is interesting. I made this picture in two minutes using the image editor (sorry, drawing wasn't my strong suit):
I can create an image from this drawing:
python3 scripts/img2img.py --prompt "A bird is sitting on a tree branch" --ckpt sd-v1-4.ckpt --init-img bird.png --strength 0.8It was far better than my initial drawing:
I hope readers understand and experiment.
Stable Diffusion UI
Developers love the command line, but regular users may struggle. Stable Diffusion UI projects simplify image generation and installation. Simple usage:
Unpack the ZIP after downloading it from https://github.com/cmdr2/stable-diffusion-ui/releases. Linux and Windows are compatible with Stable Diffusion UI (sorry for Mac users, but those machines are not well-suitable for heavy machine learning tasks anyway;).
Start the script.
Done. The web browser UI makes configuring various Stable Diffusion features (upscaling, filtering, etc.) easy:
V2.1 of Stable Diffusion
I noticed the notification about releasing version 2.1 while writing this essay, and it was intriguing to test it. First, compare version 2 to version 1:
alternative text encoding. The Contrastive LanguageImage Pre-training (CLIP) deep learning model, which was trained on a significant number of text-image pairs, is used in Stable Diffusion 1. The open-source CLIP implementation used in Stable Diffusion 2 is called OpenCLIP. It is difficult to determine whether there have been any technical advancements or if legal concerns were the main focus. However, because the training datasets for the two text encoders were different, the output results from V1 and V2 will differ for the identical text prompts.
a new depth model that may be used to the output of image-to-image generation.
a revolutionary upscaling technique that can quadruple the resolution of an image.
Generally higher resolution Stable Diffusion 2 has the ability to produce both 512x512 and 768x768 pictures.
The Hugging Face website offers a free online demo of Stable Diffusion 2.1 for code testing. The process is the same as for version 1.4. Download a fresh version and activate the environment:
conda deactivate
conda env remove -n ldm # Use this if version 1 was previously installed
git clone https://github.com/Stability-AI/stablediffusion
cd stablediffusion
conda env create -f environment.yaml
conda activate ldmHugging Face offers a new weights ckpt file.
The Out of memory error prevented me from running this version on my 8 GB GPU. Version 2.1 fails on CPUs with the slow conv2d cpu not implemented for Half error (according to this GitHub issue, the CPU support for this algorithm and data type will not be added). The model can be modified from half to full precision (float16 instead of float32), however it doesn't make sense since v1 runs up to 10 minutes on the CPU and v2.1 should be much slower. The online demo results are visible. The same hamster painting with a brush prompt yielded this result:
It looks different from v1, but it functions and has a higher resolution.
The superresolution.py script can run the 4x Stable Diffusion upscaler locally (the x4-upscaler-ema.ckpt weights file should be in the same folder):
python3 scripts/gradio/superresolution.py configs/stable-diffusion/x4-upscaling.yaml x4-upscaler-ema.ckptThis code allows the web browser UI to select the image to upscale:
The copy-paste strategy may explain why the upscaler needs a text prompt (and the Hugging Face code snippet does not have any text input as well). I got a GPU out of memory error again, although CUDA can be disabled like v1. However, processing an image for more than two hours is unlikely:
Stable Diffusion Limitations
When we use the model, it's fun to see what it can and can't do. Generative models produce abstract visuals but not photorealistic ones. This fundamentally limits The generative neural network was trained on text and image pairs, but humans have a lot of background knowledge about the world. The neural network model knows nothing. If someone asks me to draw a Chinese text, I can draw something that looks like Chinese but is actually gibberish because I never learnt it. Generative AI does too! Humans can learn new languages, but the Stable Diffusion AI model includes only language and image decoder brain components. For instance, the Stable Diffusion model will pull NO WAR banner-bearers like this:
V1:
V2.1:
The shot shows text, although the model never learned to read or write. The model's string tokenizer automatically converts letters to lowercase before generating the image, so typing NO WAR banner or no war banner is the same.
I can also ask the model to draw a gorgeous woman:
V1:
V2.1:
The first image is gorgeous but physically incorrect. A second one is better, although it has an Uncanny valley feel. BTW, v2 has a lifehack to add a negative prompt and define what we don't want on the image. Readers might try adding horrible anatomy to the gorgeous woman request.
If we ask for a cartoon attractive woman, the results are nice, but accuracy doesn't matter:
V1:
V2.1:
Another example: I ordered a model to sketch a mouse, which looks beautiful but has too many legs, ears, and fingers:
V1:
V2.1: improved but not perfect.
V1 produces a fun cartoon flying mouse if I want something more abstract:
I tried multiple times with V2.1 but only received this:
The image is OK, but the first version is closer to the request.
Stable Diffusion struggles to draw letters, fingers, etc. However, abstract images yield interesting outcomes. A rural landscape with a modern metropolis in the background turned out well:
V1:
V2.1:
Generative models help make paintings too (at least, abstract ones). I searched Google Image Search for modern art painting to see works by real artists, and this was the first image:
I typed "abstract oil painting of people dancing" and got this:
V1:
V2.1:
It's a different style, but I don't think the AI-generated graphics are worse than the human-drawn ones.
The AI model cannot think like humans. It thinks nothing. A stable diffusion model is a billion-parameter matrix trained on millions of text-image pairs. I input "robot is creating a picture with a pen" to create an image for this post. Humans understand requests immediately. I tried Stable Diffusion multiple times and got this:
This great artwork has a pen, robot, and sketch, however it was not asked. Maybe it was because the tokenizer deleted is and a words from a statement, but I tried other requests such robot painting picture with pen without success. It's harder to prompt a model than a person.
I hope Stable Diffusion's general effects are evident. Despite its limitations, it can produce beautiful photographs in some settings. Readers who want to use Stable Diffusion results should be warned. Source code examination demonstrates that Stable Diffusion images feature a concealed watermark (text StableDiffusionV1 and SDV2) encoded using the invisible-watermark Python package. It's not a secret, because the official Stable Diffusion repository's test watermark.py file contains a decoding snippet. The put watermark line in the txt2img.py source code can be removed if desired. I didn't discover this watermark on photographs made by the online Hugging Face demo. Maybe I did something incorrectly (but maybe they are just not using the txt2img script on their backend at all).
Conclusion
The Stable Diffusion model was fascinating. As I mentioned before, trying something yourself is always better than taking someone else's word, so I encourage readers to do the same (including this article as well;).
Is Generative AI a game-changer? My humble experience tells me:
I think that place has a lot of potential. For designers and artists, generative AI can be a truly useful and innovative tool. Unfortunately, it can also pose a threat to some of them since if users can enter a text field to obtain a picture or a website logo in a matter of clicks, why would they pay more to a different party? Is it possible right now? unquestionably not yet. Images still have a very poor quality and are erroneous in minute details. And after viewing the image of the stunning woman above, models and fashion photographers may also unwind because it is highly unlikely that AI will replace them in the upcoming years.
Today, generative AI is still in its infancy. Even 768x768 images are considered to be of a high resolution when using neural networks, which are computationally highly expensive. There isn't an AI model that can generate high-resolution photographs natively without upscaling or other methods, at least not as of the time this article was written, but it will happen eventually.
It is still a challenge to accurately represent knowledge in neural networks (information like how many legs a cat has or the year Napoleon was born). Consequently, AI models struggle to create photorealistic photos, at least where little details are important (on the other side, when I searched Google for modern art paintings, the results are often even worse;).
When compared to the carefully chosen images from official web pages or YouTube reviews, the average output quality of a Stable Diffusion generation process is actually less attractive because to its high degree of randomness. When using the same technique on their own, consumers will theoretically only view those images as 1% of the results.
Anyway, it's exciting to witness this area's advancement, especially because the project is open source. Google's Imagen and DALL-E 2 can also produce remarkable findings. It will be interesting to see how they progress.
Dani Herrera
2 years ago
What prevents companies from disclosing salary information?
Yes, salary details ought to be mentioned in job postings. Recruiters and candidates both agree, so why doesn't it happen?
The short answer is “Unfortunately, it’s not the Recruiter’s decision”. The longer answer is well… A LOT.
Starting in November 2022, NYC employers must include salary ranges in job postings. It should have started in May, but companies balked.
I'm thrilled about salary transparency. This decision will promote fair, inclusive, and equitable hiring practices, and I'm sure other states will follow suit. Good news!
Candidates, recruiters, and ED&I practitioners have advocated for pay transparency for years. Why the opposition?
Let's quickly review why companies have trouble sharing salary bands.
💰 Pay Parity
Many companies and leaders still oppose pay parity. Yes, even in 2022.
💰 Pay Equity
Many companies believe in pay parity and have reviewed their internal processes and systems to ensure equality.
However, Pay Equity affects who gets roles/promotions/salary raises/bonuses and when. Enter the pay gap!
💰Pay Transparency and its impact on Talent Retention
Sharing salary bands with external candidates (and the world) means current employees will have access to that information, which is one of the main reasons companies don't share salary data.
If a company has Pay Parity and Pay Equity issues, they probably have a Pay Transparency policy as well.
Sharing salary information with external candidates without ensuring current employees understand their own salary bands and how promotions/raises are decided could impact talent retention strategies.
This information should help clarify recent conversations.
Victoria Kurichenko
3 years ago
Here's what happened after I launched my second product on Gumroad.
One-hour ebook sales, affiliate relationships, and more.
If you follow me, you may know I started a new ebook in August 2022.
Despite publishing on this platform, my website, and Quora, I'm not a writer.
My writing speed is slow, 2,000 words a day, and I struggle to communicate cohesively.
In April 2022, I wrote a successful guide on How to Write Google-Friendly Blog Posts.
I had no email list or social media presence. I've made $1,600+ selling ebooks.
Evidence:
My first digital offering isn't a book.
It's an actionable guide with my tried-and-true process for writing Google-friendly content.
I'm not bragging.
Established authors like Tim Denning make more from my ebook sales with one newsletter.
This experience taught me writing isn't a privilege.
Writing a book and making money online doesn't require expertise.
Many don't consult experts. They want someone approachable.
Two years passed before I realized my own limits.
I have a brain, two hands, and Internet to spread my message.
I wrote and published a second ebook after the first's success.
On Gumroad, I released my second digital product.
Here's my complete Gumroad evaluation.
Gumroad is a marketplace for content providers to develop and sell sales pages.
Gumroad handles payments and client requests. It's helpful when someone sends a bogus payment receipt requesting an ebook (actual story!).
You'll forget administrative concerns after your first ebook sale.
After my first ebook sale, I did this: I made additional cash!
After every sale, I tell myself, "I built a new semi-passive revenue source."
This thinking shift helps me become less busy while increasing my income and quality of life.
Besides helping others, folks sell evergreen digital things to earn passive money.
It's in my second ebook.
I explain how I built and sold 50+ copies of my SEO writing ebook without being an influencer.
I show how anyone can sell ebooks on Gumroad and automate their sales process.
This is my ebook.
After publicizing the ebook release, I sold three copies within an hour.
Wow, or meh?
I don’t know.
The answer is different for everyone.
These three sales came from a small email list of 40 motivated fans waiting for my ebook release.
I had bigger plans.
I'll market my ebook on Medium, my website, Quora, and email.
I'm testing affiliate partnerships this time.
One of my ebook buyers is now promoting it for 40% commission.
Become my affiliate if you think your readers would like my ebook.
My ebook is a few days old, but I'm interested to see where it goes.
My SEO writing book started without an email list, affiliates, or 4,000 website visitors. I've made four figures.
I'm slowly expanding my communication avenues to have more impact.
Even a small project can open doors you never knew existed.
So began my writing career.
In summary
If you dare, every concept can become a profitable trip.
Before, I couldn't conceive of creating an ebook.
How to Sell eBooks on Gumroad is my second digital product.
Marketing and writing taught me that anything can be sold online.