More on Entrepreneurship/Creators
Bradley Vangelder
3 years ago
How we started and then quickly sold our startup
From a simple landing where we tested our MVP to a platform that distributes 20,000 codes per month, we learned a lot.
Starting point
Kwotet was my first startup. Everyone might post book quotes online.
I wanted a change.
Kwotet lacked attention, thus I felt stuck. After experiencing the trials of starting Kwotet, I thought of developing a waitlist service, but I required a strong co-founder.
I knew Dries from school, but we weren't close. He was an entrepreneurial programmer who worked a lot outside school. I needed this.
We brainstormed throughout school hours. We developed features to put us first. We worked until 3 am to launch this product.
Putting in the hours is KEY when building a startup
The instant that we lost our spark
In Belgium, college seniors do their internship in their last semester.
As we both made the decision to pick a quite challenging company, little time was left for Lancero.
Eventually, we lost interest. We lost the spark…
The only logical choice was to find someone with the same spark we started with to acquire Lancero.
And we did @ MicroAcquire.
Sell before your product dies. Make sure to profit from all the gains.
What did we do following the sale?
Not far from selling Lancero I lost my dad. I was about to start a new company. It was focused on positivity. I got none left at the time.
We still didn’t let go of the dream of becoming full-time entrepreneurs. As Dries launched the amazing company Plunk, and I’m still in the discovering stages of my next journey!
Dream!
You’re an entrepreneur if:
You're imaginative.
You enjoy disassembling and reassembling things.
You're adept at making new friends.
YOU HAVE DREAMS.
You don’t need to believe me if I tell you “everything is possible”… I wouldn't believe it myself if anyone told me this 2 years ago.
Until I started doing, living my dreams.
Navdeep Yadav
2 years ago
31 startup company models (with examples)
Many people find the internet's various business models bewildering.
This article summarizes 31 startup e-books.
1. Using the freemium business model (free plus premium),
The freemium business model offers basic software, games, or services for free and charges for enhancements.
Examples include Slack, iCloud, and Google Drive
Provide a rudimentary, free version of your product or service to users.
Google Drive and Dropbox offer 15GB and 2GB of free space but charge for more.
Freemium business model details (Click here)
2. The Business Model of Subscription
Subscription business models sell a product or service for recurring monthly or yearly revenue.
Examples: Tinder, Netflix, Shopify, etc
It's the next step to Freemium if a customer wants to pay monthly for premium features.
Subscription Business Model (Click here)
3. A market-based business strategy
It's an e-commerce site or app where third-party sellers sell products or services.
Examples are Amazon and Fiverr.
On Amazon's marketplace, a third-party vendor sells a product.
Freelancers on Fiverr offer specialized skills like graphic design.
Marketplace's business concept is explained.
4. Business plans using aggregates
In the aggregator business model, the service is branded.
Uber, Airbnb, and other examples
Marketplace and Aggregator business models differ.
Amazon and Fiverr link merchants and customers and take a 10-20% revenue split.
Uber and Airbnb-style aggregator Join these businesses and provide their products.
5. The pay-as-you-go concept of business
This is a consumption-based pricing system. Cloud companies use it.
Example: Amazon Web Service and Google Cloud Platform (GCP) (AWS)
AWS, an Amazon subsidiary, offers over 200 pay-as-you-go cloud services.
“In short, the more you use the more you pay”
When it's difficult to divide clients into pricing levels, pay-as-you is employed.
6. The business model known as fee-for-service (FFS)
FFS charges fixed and variable fees for each successful payment.
For instance, PayU, Paypal, and Stripe
Stripe charges 2.9% + 30 per payment.
These firms offer a payment gateway to take consumer payments and deposit them to a business account.
Fintech business model
7. EdTech business strategy
In edtech, you generate money by selling material or teaching as a service.
edtech business models
Freemium When course content is free but certification isn't, e.g. Coursera
FREE TRIAL SkillShare offers free trials followed by monthly or annual subscriptions.
Self-serving marketplace approach where you pick what to learn.
Ad-revenue model The company makes money by showing adverts to its huge user base.
Lock-in business strategy
Lock in prevents customers from switching to a competitor's brand or offering.
It uses switching costs or effort to transmit (soft lock-in), improved brand experience, or incentives.
Apple, SAP, and other examples
Apple offers an iPhone and then locks you in with extra hardware (Watch, Airpod) and platform services (Apple Store, Apple Music, cloud, etc.).
9. Business Model for API Licensing
APIs let third-party apps communicate with your service.
Uber and Airbnb use Google Maps APIs for app navigation.
Examples are Google Map APIs (Map), Sendgrid (Email), and Twilio (SMS).
Business models for APIs
Free: The simplest API-driven business model that enables unrestricted API access for app developers. Google Translate and Facebook are two examples.
Developer Pays: Under this arrangement, service providers such as AWS, Twilio, Github, Stripe, and others must be paid by application developers.
The developer receives payment: These are the compensated content producers or developers who distribute the APIs utilizing their work. For example, Amazon affiliate programs
10. Open-source enterprise
Open-source software can be inspected, modified, and improved by anybody.
For instance, use Firefox, Java, or Android.
Google paid Mozilla $435,702 million to be their primary search engine in 2018.
Open-source software profits in six ways.
Paid assistance The Project Manager can charge for customization because he is quite knowledgeable about the codebase.
A full database solution is available as a Software as a Service (MongoDB Atlas), but there is a fee for the monitoring tool.
Open-core design R studio is a better GUI substitute for open-source applications.
sponsors of GitHub Sponsorships benefit the developers in full.
demands for paid features Earn Money By Developing Open Source Add-Ons for Current Products
Open-source business model
11. The business model for data
If the software or algorithm collects client data to improve or monetize the system.
Open AI GPT3 gets smarter with use.
Foursquare allows users to exchange check-in locations.
Later, they compiled large datasets to enable retailers like Starbucks launch new outlets.
12. Business Model Using Blockchain
Blockchain is a distributed ledger technology that allows firms to deploy smart contracts without a central authority.
Examples include Alchemy, Solana, and Ethereum.
Business models using blockchain
Economy of tokens or utility When a business uses a token business model, it issues some kind of token as one of the ways to compensate token holders or miners. For instance, Solana and Ethereum
Bitcoin Cash P2P Business Model Peer-to-peer (P2P) blockchain technology permits direct communication between end users. as in IPFS
Enterprise Blockchain as a Service (Baas) BaaS focuses on offering ecosystem services similar to those offered by Amazon (AWS) and Microsoft (Azure) in the web 3 sector. Example: Ethereum Blockchain as a Service with Bitcoin (EBaaS).
Blockchain-Based Aggregators With AWS for blockchain, you can use that service by making an API call to your preferred blockchain. As an illustration, Alchemy offers nodes for many blockchains.
13. The free-enterprise model
In the freeterprise business model, free professional accounts are led into the funnel by the free product and later become B2B/enterprise accounts.
For instance, Slack and Zoom
Freeterprise companies flourish through collaboration.
Start with a free professional account to build an enterprise.
14. Business plan for razor blades
It's employed in hardware where one piece is sold at a loss and profits are made through refills or add-ons.
Gillet razor & blades, coffee machine & beans, HP printer & cartridge, etc.
Sony sells the Playstation console at a loss but makes up for it by selling games and charging for online services.
Advantages of the Razor-Razorblade Method
lowers the risk a customer will try a product. enables buyers to test the goods and services without having to pay a high initial investment.
The product's ongoing revenue stream has the potential to generate sales that much outweigh the original investments.
Razor blade business model
15. The business model of direct-to-consumer (D2C)
In D2C, the company sells directly to the end consumer through its website using a third-party logistic partner.
Examples include GymShark and Kylie Cosmetics.
D2C brands can only expand via websites, marketplaces (Amazon, eBay), etc.
D2C benefits
Lower reliance on middlemen = greater profitability
You now have access to more precise demographic and geographic customer data.
Additional space for product testing
Increased customisation throughout your entire product line-Inventory Less
16. Business model: White Label vs. Private Label
Private label/White label products are made by a contract or third-party manufacturer.
Most amazon electronics are made in china and white-labeled.
Amazon supplements and electronics.
Contract manufacturers handle everything after brands select product quantities on design labels.
17. The franchise model
The franchisee uses the franchisor's trademark, branding, and business strategy (company).
For instance, KFC, Domino's, etc.
Subway, Domino, Burger King, etc. use this business strategy.
Many people pick a franchise because opening a restaurant is risky.
18. Ad-based business model
Social media and search engine giants exploit search and interest data to deliver adverts.
Google, Meta, TikTok, and Snapchat are some examples.
Users don't pay for the service or product given, e.g. Google users don't pay for searches.
In exchange, they collected data and hyper-personalized adverts to maximize revenue.
19. Business plan for octopuses
Each business unit functions separately but is connected to the main body.
Instance: Oyo
OYO is Asia's Airbnb, operating hotels, co-working, co-living, and vacation houses.
20, Transactional business model, number
Sales to customers produce revenue.
E-commerce sites and online purchases employ SSL.
Goli is an ex-GymShark.
21. The peer-to-peer (P2P) business model
In P2P, two people buy and sell goods and services without a third party or platform.
Consider OLX.
22. P2P lending as a manner of operation
In P2P lending, one private individual (P2P Lender) lends/invests or borrows money from another (P2P Borrower).
Instance: Kabbage
Social lending lets people lend and borrow money directly from each other without an intermediary financial institution.
23. A business model for brokers
Brokerages charge a commission or fee for their services.
Examples include eBay, Coinbase, and Robinhood.
Brokerage businesses are common in Real estate, finance, and online and operate on this model.
Buy/sell similar models Examples include financial brokers, insurance brokers, and others who match purchase and sell transactions and charge a commission.
These brokers charge an advertiser a fee based on the date, place, size, or type of an advertisement. This is known as the classified-advertiser model. For instance, Craiglist
24. Drop shipping as an industry
Dropshipping allows stores to sell things without holding physical inventories.
When a customer orders, use a third-party supplier and logistic partners.
Retailer product portfolio and customer experience Fulfiller The consumer places the order.
Dropshipping advantages
Less money is needed (Low overhead-No Inventory or warehousing)
Simple to start (costs under $100)
flexible work environment
New product testing is simpler
25. Business Model for Space as a Service
It's centered on a shared economy that lets millennials live or work in communal areas without ownership or lease.
Consider WeWork and Airbnb.
WeWork helps businesses with real estate, legal compliance, maintenance, and repair.
26. The business model for third-party logistics (3PL)
In 3PL, a business outsources product delivery, warehousing, and fulfillment to an external logistics company.
Examples include Ship Bob, Amazon Fulfillment, and more.
3PL partners warehouse, fulfill, and return inbound and outbound items for a charge.
Inbound logistics involves bringing products from suppliers to your warehouse.
Outbound logistics refers to a company's production line, warehouse, and customer.
27. The last-mile delivery paradigm as a commercial strategy
Last-mile delivery is the collection of supply chain actions that reach the end client.
Examples include Rappi, Gojek, and Postmates.
Last-mile is tied to on-demand and has a nighttime peak.
28. The use of affiliate marketing
Affiliate marketing involves promoting other companies' products and charging commissions.
Examples include Hubspot, Amazon, and Skillshare.
Your favorite youtube channel probably uses these short amazon links to get 5% of sales.
Affiliate marketing's benefits
In exchange for a success fee or commission, it enables numerous independent marketers to promote on its behalf.
Ensure system transparency by giving the influencers a specific tracking link and an online dashboard to view their profits.
Learn about the newest bargains and have access to promotional materials.
29. The business model for virtual goods
This is an in-app purchase for an intangible product.
Examples include PubG, Roblox, Candy Crush, etc.
Consumables are like gaming cash that runs out. Non-consumable products provide a permanent advantage without repeated purchases.
30. Business Models for Cloud Kitchens
Ghost, Dark, Black Box, etc.
Delivery-only restaurant.
These restaurants don't provide dine-in, only delivery.
For instance, NextBite and Faasos
31. Crowdsourcing as a Business Model
Crowdsourcing = Using the crowd as a platform's source.
In crowdsourcing, you get support from people around the world without hiring them.
Crowdsourcing sites
Open-Source Software gives access to the software's source code so that developers can edit or enhance it. Examples include Firefox browsers and Linux operating systems.
Crowdfunding The oculus headgear would be an example of crowdfunding in essence, with no expectations.
Nick
3 years ago
This Is How Much Quora Paid Me For 23 Million Content Views
You’ll be surprised; I sure was
Blogging and writing online as a side income has now been around for a significant amount of time. Nowadays, it is a continuously rising moneymaker for prospective writers, with several writing platforms existing online. At the top of the list are Medium, Vocal Media, Newsbreak, and the biggest one of them, Quora, with 300 million active users.
Quora, unlike Medium, is a question-and-answer format platform. On Medium you are permitted to write what you want, while on Quora, you answer questions on topics that you have expertise about. Quora, like Medium, now compensates its authors for the answers they provide in comparison to the previous, in which you had to be admitted to the partner program and were paid to ask questions.
Quora just recently went live with this new partner program, Quora Plus, and the way it works is that it is a subscription for $5 a month which provides you access to metered/monetized stories, in turn compensating the writers for part of that subscription for their answers.
I too on Quora have found a lot of success on the platform, gaining 23 Million Content Views, and 300,000 followers for my space, which is kind of the Quora equivalent of a Medium article. The way in which I was able to do this was entirely thanks to a hack that I uncovered to the Quora algorithm.
In this article, I plan on discussing how much money I received from 23 million content views on Quora, and I bet you’ll be shocked; I know I was.
A Brief Explanation of How I Got 23 Million Views and How You Can Do It Too
On Quora, everything in terms of obtaining views is about finding the proper question, which I only understood quite late into the game. I published my first response in 2019 but never actually wrote on Quora until the summer of 2020, and about a month into posting consistently I found out how to find the perfect question. Here’s how:
The Process
Go to your Home Page and start scrolling… While browsing, check for the following things…
Answers from people you follow or your followers.
Advertisements
These two things are the two things you want to ignore, you don’t want to answer those questions or look at the ads. You should now be left with a couple of recommended answers. To discover which recommended answer is the best to answer as well, look at these three important aspects.
Date of the answer: Was it in the past few days, preferably 2–3 days, even better, past 24 hours?
Views: Are they in the ten thousands or hundred thousands?
Upvotes: Are they in the hundreds or thousands?
Now, choose an answer to a question which you think you could answer as well that satisfies the requirements above. Once you click on it, as all answers on Quora works, it will redirect you to the page for that question, in which you will have to select once again if you should answer the question.
Amount of answers: How many responses are there to the given question? This tells you how much competition you have. My rule is beyond 25 answers, you shouldn’t answer, but you can change it anyway you’d like.
Answerers: Who did the answering for the question? If the question includes a bunch of renowned, extremely well-known people on Quora, there’s a good possibility your essay is going to get drowned out.
Views: Check for a constant quantity of high views on each answer for the question; this is what will guarantee that your answer gets a lot of views!
The Income Reveal! How Much I Made From 23 Million Content Views
DRUM ROLL, PLEASE!
8.97 USD. Yes, not even ten dollars, not even nine. Just eight dollars and ninety-seven cents.
Possible Reasons for My Low Earnings
Quora Plus and the answering partner program are newer than my Quora views.
Few people use Quora+, therefore revenues are low.
I haven't been writing much on Quora, so I'm only making money from old answers and a handful since Quora Plus launched.
Quora + pays poorly...
Should You Try Quora and Quora For Money?
My answer depends on your needs. I never got invited to Quora's question partner program due to my late start, but other writers have made hundreds. Due to Quora's new and competitive answering partner program, you may not make much money.
If you want a fun writing community, try Quora. Quora was fun when I only made money from my space. Quora +'s paywalls and new contributors eager to make money have made the platform less fun for me.
This article is a summary to save you time. You can read my full, more detailed article, here.
You might also like
Vitalik
3 years ago
Fairness alternatives to selling below market clearing prices (or community sentiment, or fun)
When a seller has a limited supply of an item in high (or uncertain and possibly high) demand, they frequently set a price far below what "the market will bear." As a result, the item sells out quickly, with lucky buyers being those who tried to buy first. This has happened in the Ethereum ecosystem, particularly with NFT sales and token sales/ICOs. But this phenomenon is much older; concerts and restaurants frequently make similar choices, resulting in fast sell-outs or long lines.
Why do sellers do this? Economists have long wondered. A seller should sell at the market-clearing price if the amount buyers are willing to buy exactly equals the amount the seller has to sell. If the seller is unsure of the market-clearing price, they should sell at auction and let the market decide. So, if you want to sell something below market value, don't do it. It will hurt your sales and it will hurt your customers. The competitions created by non-price-based allocation mechanisms can sometimes have negative externalities that harm third parties, as we will see.
However, the prevalence of below-market-clearing pricing suggests that sellers do it for good reason. And indeed, as decades of research into this topic has shown, there often are. So, is it possible to achieve the same goals with less unfairness, inefficiency, and harm?
Selling at below market-clearing prices has large inefficiencies and negative externalities
An item that is sold at market value or at an auction allows someone who really wants it to pay the high price or bid high in the auction. So, if a seller sells an item below market value, some people will get it and others won't. But the mechanism deciding who gets the item isn't random, and it's not always well correlated with participant desire. It's not always about being the fastest at clicking buttons. Sometimes it means waking up at 2 a.m. (but 11 p.m. or even 2 p.m. elsewhere). Sometimes it's just a "auction by other means" that's more chaotic, less efficient, and has far more negative externalities.
There are many examples of this in the Ethereum ecosystem. Let's start with the 2017 ICO craze. For example, an ICO project would set the price of the token and a hard maximum for how many tokens they are willing to sell, and the sale would start automatically at some point in time. The sale ends when the cap is reached.
So what? In practice, these sales often ended in 30 seconds or less. Everyone would start sending transactions in as soon as (or just before) the sale started, offering higher and higher fees to encourage miners to include their transaction first. Instead of the token seller receiving revenue, miners receive it, and the sale prices out all other applications on-chain.
The most expensive transaction in the BAT sale set a fee of 580,000 gwei, paying a fee of $6,600 to get included in the sale.
Many ICOs after that tried various strategies to avoid these gas price auctions; one ICO notably had a smart contract that checked the transaction's gasprice and rejected it if it exceeded 50 gwei. But that didn't solve the issue. Buyers hoping to game the system sent many transactions hoping one would get through. An auction by another name, clogging the chain even more.
ICOs have recently lost popularity, but NFTs and NFT sales have risen in popularity. But the NFT space didn't learn from 2017; they do fixed-quantity sales just like ICOs (eg. see the mint function on lines 97-108 of this contract here). So what?
That's not the worst; some NFT sales have caused gas price spikes of up to 2000 gwei.
High gas prices from users fighting to get in first by sending higher and higher transaction fees. An auction renamed, pricing out all other applications on-chain for 15 minutes.
So why do sellers sometimes sell below market price?
Selling below market value is nothing new, and many articles, papers, and podcasts have written (and sometimes bitterly complained) about the unwillingness to use auctions or set prices to market-clearing levels.
Many of the arguments are the same for both blockchain (NFTs and ICOs) and non-blockchain examples (popular restaurants and concerts). Fairness and the desire not to exclude the poor, lose fans or create tension by being perceived as greedy are major concerns. The 1986 paper by Kahneman, Knetsch, and Thaler explains how fairness and greed can influence these decisions. I recall that the desire to avoid perceptions of greed was also a major factor in discouraging the use of auction-like mechanisms in 2017.
Aside from fairness concerns, there is the argument that selling out and long lines create a sense of popularity and prestige, making the product more appealing to others. Long lines should have the same effect as high prices in a rational actor model, but this is not the case in reality. This applies to ICOs and NFTs as well as restaurants. Aside from increasing marketing value, some people find the game of grabbing a limited set of opportunities first before everyone else is quite entertaining.
But there are some blockchain-specific factors. One argument for selling ICO tokens below market value (and one that persuaded the OmiseGo team to adopt their capped sale strategy) is community dynamics. The first rule of community sentiment management is to encourage price increases. People are happy if they are "in the green." If the price drops below what the community members paid, they are unhappy and start calling you a scammer, possibly causing a social media cascade where everyone calls you a scammer.
This effect can only be avoided by pricing low enough that post-launch market prices will almost certainly be higher. But how do you do this without creating a rush for the gates that leads to an auction?
Interesting solutions
It's 2021. We have a blockchain. The blockchain is home to a powerful decentralized finance ecosystem, as well as a rapidly expanding set of non-financial tools. The blockchain also allows us to reset social norms. Where decades of economists yelling about "efficiency" failed, blockchains may be able to legitimize new uses of mechanism design. If we could use our more advanced tools to create an approach that more directly solves the problems, with fewer side effects, wouldn't that be better than fiddling with a coarse-grained one-dimensional strategy space of selling at market price versus below market price?
Begin with the goals. We'll try to cover ICOs, NFTs, and conference tickets (really a type of NFT) all at the same time.
1. Fairness: don't completely exclude low-income people from participation; give them a chance. The goal of token sales is to avoid high initial wealth concentration and have a larger and more diverse initial token holder community.
2. Don’t create races: Avoid situations where many people rush to do the same thing and only a few get in (this is the type of situation that leads to the horrible auctions-by-another-name that we saw above).
3. Don't require precise market knowledge: the mechanism should work even if the seller has no idea how much demand exists.
4. Fun: The process of participating in the sale should be fun and game-like, but not frustrating.
5. Give buyers positive expected returns: in the case of a token (or an NFT), buyers should expect price increases rather than decreases. This requires selling below market value.
Let's start with (1). From Ethereum's perspective, there is a simple solution. Use a tool designed for the job: proof of personhood protocols! Here's one quick idea:
Mechanism 1 Each participant (verified by ID) can buy up to ‘’X’’ tokens at price P, with the option to buy more at an auction.
With the per-person mechanism, buyers can get positive expected returns for the portion sold through the per-person mechanism, and the auction part does not require sellers to understand demand levels. Is it race-free? The number of participants buying through the per-person pool appears to be high. But what if the per-person pool isn't big enough to accommodate everyone?
Make the per-person allocation amount dynamic.
Mechanism 2 Each participant can deposit up to X tokens into a smart contract to declare interest. Last but not least, each buyer receives min(X, N / buyers) tokens, where N is the total sold through the per-person pool (some other amount can also be sold by auction). The buyer gets their deposit back if it exceeds the amount needed to buy their allocation.
No longer is there a race condition based on the number of buyers per person. No matter how high the demand, it's always better to join sooner rather than later.
Here's another idea if you like clever game mechanics with fancy quadratic formulas.
Mechanism 3 Each participant can buy X units at a price P X 2 up to a maximum of C tokens per buyer. C starts low and gradually increases until enough units are sold.
The quantity allocated to each buyer is theoretically optimal, though post-sale transfers will degrade this optimality over time. Mechanisms 2 and 3 appear to meet all of the above objectives. They're not perfect, but they're good starting points.
One more issue. For fixed and limited supply NFTs, the equilibrium purchased quantity per participant may be fractional (in mechanism 2, number of buyers > N, and in mechanism 3, setting C = 1 may already lead to over-subscription). With fractional sales, you can offer lottery tickets: if there are N items available, you have a chance of N/number of buyers of getting the item, otherwise you get a refund. For a conference, groups could bundle their lottery tickets to guarantee a win or a loss. The certainty of getting the item can be auctioned.
The bottom tier of "sponsorships" can be used to sell conference tickets at market rate. You may end up with a sponsor board full of people's faces, but is that okay? After all, John Lilic was on EthCC's sponsor board!
Simply put, if you want to be reliably fair to people, you need an input that explicitly measures people. Authentication protocols do this (and if desired can be combined with zero knowledge proofs to ensure privacy). So we should combine the efficiency of market and auction-based pricing with the equality of proof of personhood mechanics.
Answers to possible questions
Q: Won't people who don't care about your project buy the item and immediately resell it?
A: Not at first. Meta-games take time to appear in practice. If they do, making them untradeable for a while may help mitigate the damage. Using your face to claim that your previous account was hacked and that your identity, including everything in it, should be moved to another account works because proof-of-personhood identities are untradeable.
Q: What if I want to make my item available to a specific community?
A: Instead of ID, use proof of participation tokens linked to community events. Another option, also serving egalitarian and gamification purposes, is to encrypt items within publicly available puzzle solutions.
Q: How do we know they'll accept? Strange new mechanisms have previously been resisted.
A: Having economists write screeds about how they "should" accept a new mechanism that they find strange is difficult (or even "equity"). However, abrupt changes in context effectively reset people's expectations. So the blockchain space is the best place to try this. You could wait for the "metaverse", but it's possible that the best version will run on Ethereum anyway, so start now.
Johnny Harris
3 years ago
The REAL Reason Putin is Invading Ukraine [video with transcript]
Transcript:
[Reporter] The Russian invasion of Ukraine.
Momentum is building for a war between Ukraine and Russia.
[Reporter] Tensions between Russia and the West
are growing rapidly.
[Reporter] President Biden considering deploying
thousands of troops to Eastern Europe.
There are now 100,000 troops
on the Eastern border of Ukraine.
Russia is setting up field hospitals on this border.
Like this is what preparation for war looks like.
A legitimate war.
Ukrainian troops are watching and waiting,
saying they are preparing for a fight.
The U.S. has ordered the families of embassy staff
to leave Ukraine.
Britain has sent all of their nonessential staff home.
And now the U.S. is sending tons of weapons and munitions
to Ukraine's army.
And we're even considering deploying
our own troops to the region.
I mean, this thing is heating up.
Meanwhile, Russia and the West have been in Geneva
and Brussels trying to talk it out,
and sort of getting nowhere.
The message is very clear.
Should Russia take further aggressive actions
against Ukraine the costs will be severe
and the consequences serious.
It's a scary, grim momentum that is unpredictable.
And the chances of miscalculation
and escalation are growing.
I want to explain what's going on here,
but I want to show you that this isn't just
typical geopolitical behavior.
Stuff that can just be explained on the map.
Instead, to understand why 100,000 troops are camped out
on Ukraine's Eastern border, ready for war,
you have to understand Russia
and how it's been cut down over the ages
from the Slavic empire that dominated this whole region
to then the Soviet Union,
which was defeated in the nineties.
And what you really have to understand here
is how that history is transposed
onto the brain of one man.
This guy, Vladimir Putin.
This is a story about regional domination
and struggles between big powers,
but really it's the story about
what Vladimir Putin really wants.
[Reporter] Russian troops moving swiftly
to take control of military bases in Crimea.
[Reporter] Russia has amassed more than 100,000 troops
and a lot of military hardware
at the border with Ukraine.
Let's dive back in.
Okay. Let's get up to speed on what's happening here.
And I'm just going to quickly give you the highlight version
of like the news that's happening,
because I want to get into the juicy part,
which is like why, the roots of all of this.
So let's go.
A few months ago, Russia started sending
more and more troops to this border.
It's this massive border between Ukraine and Russia.
They said they were doing a military exercise,
but the rest of the world was like,
"Yeah, we totally believe you Russia. Pshaw."
This was right before this big meeting
where North American and European countries
were coming together to talk about a lot
of different things, like these countries often do
in these diplomatic summits.
But soon, because of Russia's aggressive behavior
coming in and setting up 100,000 troops
on the border with Ukraine,
the entire summit turned into a whole, "WTF Russia,
what are you doing on the border of Ukraine," meeting.
Before the meeting Putin comes out and says,
"Listen, I have some demands for the West."
And everyone's like, "Okay, Russia, what are your demands?
You know, we have like, COVID19 right now.
And like, that's like surging.
So like, we don't need your like,
bluster about what your demands are."
And Putin's like, "No, here's my list of demands."
Putin's demands for the summit were this:
number one, that NATO, which is this big military alliance
between U.S., Canada, and Europe stop expanding,
meaning they don't let any new members in, okay.
So, Russia is like, "No more new members to your, like,
cool military club that I don't like.
You can't have any more members."
Number two, that NATO withdraw all of their troops
from anywhere in Eastern Europe.
Basically Putin is saying,
"I can veto any military cooperation
or troops going between countries
that have to do with Eastern Europe,
the place that used to be the Soviet Union."
Okay, and number three, Putin demands that America vow
not to protect its allies in Eastern Europe
with nuclear weapons.
"LOL," said all of the other countries,
"You're literally nuts, Vladimir Putin.
Like these are the most ridiculous demands, ever."
But there he is, Putin, with these demands.
These very, very aggressive demands.
And he sort of is implying that if his demands aren't met,
he's going to invade Ukraine.
I mean, it doesn't work like this.
This is not how international relations work.
You don't just show up and say like,
"I'm not gonna allow other countries to join your alliance
because it makes me feel uncomfortable."
But what I love about this list of demands
from Vladimir Putin for this summit
is that it gives us a clue
on what Vladimir Putin really wants.
What he's after here.
You read them closely and you can grasp his intentions.
But to grasp those intentions
you have to understand what NATO is.
and what Russia and Ukraine used to be.
(dramatic music)
Okay, so a while back I made this video
about why Russia is so damn big,
where I explain how modern day Russia started here in Kiev,
which is actually modern day Ukraine.
In other words, modern day Russia, as we know it,
has its original roots in Ukraine.
These places grew up together
and they eventually became a part
of the same mega empire called the Soviet Union.
They were deeply intertwined,
not just in their history and their culture,
but also in their economy and their politics.
So it's after World War II,
it's like the '50s, '60s, '70s, and NATO was formed,
the North Atlantic Treaty Organization.
This was a military alliance between all of these countries,
that was meant to sort of deter the Soviet Union
from expanding and taking over the world.
But as we all know, the Soviet Union,
which was Russia and all of these other countries,
collapsed in 1991.
And all of these Soviet republics,
including Ukraine, became independent,
meaning they were not now a part
of one big block of countries anymore.
But just because the border's all split up,
it doesn't mean that these cultural ties actually broke.
Like for example, the Soviet leader at the time
of the collapse of the Soviet Union, this guy, Gorbachev,
he was the son of a Ukrainian mother and a Russian father.
Like he grew up with his mother singing him
Ukrainian folk songs.
In his mind, Ukraine and Russia were like one thing.
So there was a major reluctance to accept Ukraine
as a separate thing from Russia.
In so many ways, they are one.
There was another Russian at the time
who did not accept this new division.
This young intelligence officer, Vladimir Putin,
who was starting to rise up in the ranks
of postSoviet Russia.
There's this amazing quote from 2005
where Putin is giving this stateoftheunionlike address,
where Putin declares the collapse of the Soviet Union,
quote, "The greatest catastrophe of the 20th century.
And as for the Russian people, it became a genuine tragedy.
Tens of millions of fellow citizens and countrymen
found themselves beyond the fringes of Russian territory."
Do you see how he frames this?
The Soviet Union were all one people in his mind.
And after it collapsed, all of these people
who are a part of the motherland were now outside
of the fringes or the boundaries of Russian territory.
First off, fact check.
Greatest catastrophe of the 20th century?
Like, do you remember what else happened
in the 20th century, Vladimir?
(ominous music)
Putin's worry about the collapse of this one people
starts to get way worse when the West, his enemy,
starts showing up to his neighborhood
to all these exSoviet countries that are now independent.
The West starts selling their ideology
of democracy and capitalism and inviting them
to join their military alliance called NATO.
And guess what?
These countries are totally buying it.
All these exSoviet countries are now joining NATO.
And some of them, the EU.
And Putin is hating this.
He's like not only did the Soviet Union divide
and all of these people are now outside
of the Russia motherland,
but now they're being persuaded by the West
to join their military alliance.
This is terrible news.
Over the years, this continues to happen,
while Putin himself starts to chip away
at Russian institutions, making them weaker and weaker.
He's silencing his rivals
and he's consolidating power in himself.
(triumphant music)
And in the past few years,
he's effectively silenced anyone who can challenge him;
any institution, any court,
or any political rival have all been silenced.
It's been decades since the Soviet Union fell,
but as Putin gains more power,
he still sees the region through the lens
of the old Cold War, Soviet, Slavic empire view.
He sees this region as one big block
that has been torn apart by outside forces.
"The greatest catastrophe of the 20th century."
And the worst situation of all of these,
according to Putin, is Ukraine,
which was like the gem of the Soviet Union.
There was tons of cultural heritage.
Again, Russia sort of started in Ukraine,
not to mention it was a very populous
and industrious, resourcerich place.
And over the years Ukraine has been drifting west.
It hasn't joined NATO yet, but more and more,
it's been electing proWestern presidents.
It's been flirting with membership in NATO.
It's becoming less and less attached
to the Russian heritage that Putin so adores.
And more than half of Ukrainians say
that they'd be down to join the EU.
64% of them say that it would be cool joining NATO.
But Putin can't handle this. He is in total denial.
Like an exboyfriend who handle his exgirlfriend
starting to date someone else,
Putin can't let Ukraine go.
He won't let go.
So for the past decade,
he's been trying to keep the West out
and bring Ukraine back into the motherland of Russia.
This usually takes the form of Putin sending
secret soldiers from Russia into Ukraine
to help the people in Ukraine who want to like separate
from Ukraine and join Russia.
It also takes the form of, oh yeah,
stealing entire parts of Ukraine for Russia.
Russian troops moving swiftly to take control
of military bases in Crimea.
Like in 2014, Putin just did this.
To what America is officially calling
a Russian invasion of Ukraine.
He went down and just snatched this bit of Ukraine
and folded it into Russia.
So you're starting to see what's going on here.
Putin's life's work is to salvage what he calls
the greatest catastrophe of the 20th century,
the division and the separation
of the Soviet republics from Russia.
So let's get to present day. It's 2022.
Putin is at it again.
And honestly, if you really want to understand
the mind of Vladimir Putin and his whole view on this,
you have to read this.
"On the History of Unity of Russians and Ukrainians,"
by Vladimir Putin.
A blog post that kind of sounds
like a ninth grade history essay.
In this essay, Vladimir Putin argues
that Russia and Ukraine are one people.
He calls them essentially the same historical
and spiritual space.
Kind of beautiful writing, honestly.
Anyway, he argues that the division
between the two countries is due to quote,
"a deliberate effort by those forces
that have always sought to undermine our unity."
And that the formula they use, these outside forces,
is a classic one: divide and rule.
And then he launches into this super indepth,
like 10page argument, as to every single historical beat
of Ukraine and Russia's history
to make this argument that like,
this is one people and the division is totally because
of outside powers, i.e. the West.
Okay, but listen, there's this moment
at the end of the post,
that actually kind of hit me in a big way.
He says this, "Just have a look at Austria and Germany,
or the U.S. and Canada, how they live next to each other.
Close in ethnic composition, culture,
and in fact, sharing one language,
they remain sovereign states with their own interests,
with their own foreign policy.
But this does not prevent them
from the closest integration or allied relations.
They have very conditional, transparent borders.
And when crossing them citizens feel at home.
They create families, study, work, do business.
Incidentally, so do millions of those born in Ukraine
who now live in Russia.
We see them as our own close people."
I mean, listen, like,
I'm not in support of what Putin is doing,
but like that, it's like a pretty solid like analogy.
If China suddenly showed up and started like
coaxing Canada into being a part of its alliance,
I would be a little bit like, "What's going on here?"
That's what Putin feels.
And so I kind of get what he means there.
There's a deep heritage and connection between these people.
And he's seen that falter and dissolve
and he doesn't like it.
He clearly genuinely feels a brotherhood
and this deep heritage connection
with the people of Ukraine.
Okay, okay, okay, okay. Putin, I get it.
Your essay is compelling there at the end.
You're clearly very smart and wellread.
But this does not justify what you've been up to. Okay?
It doesn't justify sending 100,000 troops to the border
or sending cyber soldiers to sabotage
the Ukrainian government, or annexing territory,
fueling a conflict that has killed
tens of thousands of people in Eastern Ukraine.
No. Okay.
No matter how much affection you feel for Ukrainian heritage
and its connection to Russia, this is not okay.
Again, it's like the boyfriend
who genuinely loves his girlfriend.
They had a great relationship,
but they broke up and she's free to see whomever she wants.
But Putin is not ready to let go.
[Man In Blue Shirt] What the hell's wrong with you?
I love you, Jessica.
What the hell is wrong with you?
Dude, don't fucking touch me.
I love you. Worldstar!
What is wrong with you? Just stop!
Putin has constructed his own reality here.
One in which Ukraine is actually being controlled
by shadowy Western forces
who are holding the people of Ukraine hostage.
And if that he invades, it will be a swift victory
because Ukrainians will accept him with open arms.
The great liberator.
(triumphant music)
Like, this guy's a total romantic.
He's a history buff and a romantic.
And he has a hill to die on here.
And it is liberating the people
who have been taken from the Russian motherland.
Kind of like the abusive boyfriend, who's like,
"She actually really loves me,
but it's her annoying friends
who were planting all these ideas in her head.
That's why she broke up with me."
And it's like, "No, dude, she's over you."
[Man In Blue Shirt] What the hell is wrong with you?
I love you, Jessica.
I mean, maybe this video should be called
Putin is just like your abusive exboyfriend.
[Man In Blue Shirt] What the hell is wrong with you?
I love you, Jessica!
Worldstar! What's wrong with you?
Okay. So where does this leave us?
It's 2022, Putin is showing up to these meetings in Europe
to tell them where he stands.
He says, "NATO, you cannot expand anymore. No new members.
And you need to withdraw all your troops
from Eastern Europe, my neighborhood."
He knows these demands will never be accepted
because they're ludicrous.
But what he's doing is showing a false effort to say,
"Well, we tried to negotiate with the West,
but they didn't want to."
Hence giving a little bit more justification
to a Russian invasion.
So will Russia invade? Is there war coming?
Maybe; it's impossible to know
because it's all inside of the head of this guy.
But, if I were to make the best argument
that war is not coming tomorrow,
I would look at a few things.
Number one, war in Ukraine would be incredibly costly
for Vladimir Putin.
Russia has a far superior army to Ukraine's,
but still, Ukraine has a very good army
that is supported by the West
and would give Putin a pretty bad bloody nose
in any invasion.
Controlling territory in Ukraine would be very hard.
Ukraine is a giant country.
They would fight back and it would be very hard
to actually conquer and take over territory.
Another major point here is that if Russia invades Ukraine,
this gives NATO new purpose.
If you remember, NATO was created because of the Cold War,
because the Soviet Union was big and nuclear powered.
Once the Soviet Union fell,
NATO sort of has been looking for a new purpose
over the past couple of decades.
If Russia invades Ukraine,
NATO suddenly has a brand new purpose to unite
and to invest in becoming more powerful than ever.
Putin knows that.
And it would be very bad news for him if that happened.
But most importantly, perhaps the easiest clue
for me to believe that war isn't coming tomorrow
is the Russian propaganda machine
is not preparing the Russian people for an invasion.
In 2014, when Russia was about to invade
and take over Crimea, this part of Ukraine,
there was a barrage of state propaganda
that prepared the Russian people
that this was a justified attack.
So when it happened, it wasn't a surprise
and it felt very normal.
That isn't happening right now in Russia.
At least for now. It may start happening tomorrow.
But for now, I think Putin is showing up to the border,
flexing his muscles and showing the West that he is earnest.
I'm not sure that he's going to invade tomorrow,
but he very well could.
I mean, read the guy's blog post
and you'll realize that he is a romantic about this.
He is incredibly idealistic about the glory days
of the Slavic empires, and he wants to get it back.
So there is dangerous momentum towards war.
And the way war works is even a small little, like, fight,
can turn into the other guy
doing something bigger and crazier.
And then the other person has to respond
with something a little bit bigger.
That's called escalation.
And there's not really a ceiling
to how much that momentum can spin out of control.
That is why it's so scary when two nuclear countries
go to war with each other,
because there's kind of no ceiling.
So yeah, it's dangerous. This is scary.
I'm not sure what happens next here,
but the best we can do is keep an eye on this.
At least for now, we better understand
what Putin really wants out of all of this.
Thanks for watching.
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.