Taking great financial advice is key to financial success.

A wealthy man told me to INVEST MY MONEY when I was young.

As I entered Starbucks, an older man was leaving. I noticed his watch and expensive-looking shirt, not like the guy in the photo, but one made of fine fabric like vicuna wool, which can only be shorn every two to three years. His Bentley confirmed my suspicions about his wealth.

This guy looked like James Bond, so I asked him how to get rich like him.

"Drug dealer?" he laughed.

Whether he was telling the truth, I'll never know, and I didn't want to be an accessory, but he quickly added, "Kid, invest your money; it will do wonders." He left.

When he told me to invest, he didn't say what. Later, I realized the investment game has so many levels that even if he drew me a blueprint, I wouldn't understand it.

The best advice I received was to invest my earnings. I must decide where to invest.

I'll preface by saying I'm not a financial advisor or Your financial advisor, but I'll share what I've learned from books, links, and sources. The rest is up to you.

Basically:

Invest your Money

Money is money, whether you call it cake, dough, moolah, benjamins, paper, bread, etc.

If you're lucky, you can buy one of the gold shirts in the photo.

Investing your money today means putting it towards anything that could be profitable.

According to the website Investopedia:
“Investing is allocating money to generate income or profit.”

You can invest in a business, real estate, or a skill that will pay off later.

Everyone has different goals and wants at different stages of life, so investing varies.

He was probably a sugar daddy with his Bentley, nice shirt, and Rolex.

In my twenties, I started making "good" money; now, in my forties, with a family and three kids, I'm building a legacy for my grandkids.

“It’s not how much money you make, but how much money you keep, how hard it works for you, and how many generations you keep it for.” — Robert Kiyosaki.

Money isn't evil, but lack of it is.

Financial stress is a major source of problems, according to studies. 

Being broke hurts, especially if you want to provide for your family or do things.

“An investment in knowledge pays the best interest.” — Benjamin Franklin.

Investing in knowledge is invaluable. Before investing, do your homework.

You probably didn't learn about investing when you were young, like I didn't. My parents were in survival mode, making investing difficult.

In my 20s, I worked in banking to better understand money.

So, why invest?

Growth requires investment.

Investing puts money to work and can build wealth. Your money may outpace inflation with smart investing. Compounding and the risk-return tradeoff boost investment growth.

Investing your money means you won't have to work forever — unless you want to.

Two common ways to make money are;

-working hard,

and

-interest or capital gains from investments.

Capital gains can help you invest.

“How many millionaires do you know who have become wealthy by investing in savings accounts? I rest my case.” — Robert G. Allen

If you keep your money in a savings account, you'll earn less than 2% interest at best; the bank makes money by loaning it out.

Savings accounts are a safe bet, but the low-interest rates limit your gains.

Don't skip it. An emergency fund should be in a savings account, not the market.

Other reasons to invest:

Investing can generate regular income.

If you own rental properties, the tenant's rent will add to your cash flow.

Daily, weekly, or monthly rentals (think Airbnb) generate higher returns year-round.

Capital gains are taxed less than earned income if you own dividend-paying or appreciating stock.

Time is on your side

“Compound interest is the eighth wonder of the world. He who understands it, earns it; he who doesn’t — pays it.” — Albert Einstein

Historical data shows that young investors outperform older investors. So you can use compound interest over decades instead of investing at 45 and having less time to earn.

If I had taken that man's advice and invested in my twenties, I would have made a decent return by my thirties. (Depending on my investments)

So for those who live a YOLO (you only live once) life, investing can't hurt.

Investing increases your knowledge.

Lessons are clearer when you're invested. Each win boosts confidence and draws attention to losses. Losing money prompts you to investigate.

Before investing, I read many financial books, but I didn't understand them until I invested.

Now what?

What do you invest in? Equities, mutual funds, ETFs, retirement accounts, savings, business, real estate, cryptocurrencies, marijuana, insurance, etc.

The key is to start somewhere. Know you don't know everything. You must care.

“A journey of a thousand miles must begin with a single step.” — Lao Tzu.

Start simple because there's so much information. My first investment book was:

Robert Kiyosaki's "Rich Dad, Poor Dad"

This easy-to-read book made me hungry for more. This book is about the money lessons rich parents teach their children, which poor and middle-class parents neglect. The poor and middle-class work for money, while the rich let their assets work for them, says Kiyosaki.

There is so much to learn, but you gotta start somewhere.

More books:

***Wisdom

I hope I'm not suggesting that investing makes everything rosy. Remember three rules:

1. Losing money is possible.

2. Losing money is possible.

3. Losing money is possible.

You can lose money, so be careful.

Read, research, invest.

Golden rules for Investing your money

• Never invest money you can't lose.

• Financial freedom is possible regardless of income.

• "Courage taught me that any sound investment will pay off, no matter how bad a crisis gets." Helu Carlos

• "I'll tell you Wall Street's secret to wealth. When others are afraid, you're greedy. You're afraid when others are greedy. Buffett

• Buy low, sell high, and have an exit strategy.

• Ask experts or wealthy people for advice.

• "With a good understanding of history, we can have a clear vision of the future." Helu Carlos

• "It's not whether you're right or wrong, but how much money you make when you're right." Soros

• "The individual investor should act as an investor, not a speculator." Graham

• "It's different this time" is the most dangerous investment phrase. Templeton

Lastly,

• Avoid quick-money schemes. Building wealth takes years, not months.

Start small and work your way up.

Thanks for reading!

This post is a summary. Read the full article here

An email capturing Steve Jobs's philosophy.

Steve Jobs may have been the most inspired and driven entrepreneur.

He worked on projects because he wanted to leave a legacy.

Steve Jobs' final email to himself encapsulated his philosophy.

After his death from pancreatic cancer in October 2011, Laurene Powell Jobs released the email. He was 56.

Read: Steve Jobs by Walter Isaacson (#BestSeller)

The Email:

September 2010 Steve Jobs email:

“I grow little of the food I eat, and of the little I do grow, I do not breed or perfect the seeds.” “I do not make my own clothing. I speak a language I did not invent or refine,” he continued. “I did not discover the mathematics I use… I am moved by music I did not create myself.”

Jobs ended his email by reflecting on how others created everything he uses.

He wrote:

“When I needed medical attention, I was helpless to help myself survive.”

The Apple co-founder concluded by praising humanity.

“I did not invent the transistor, the microprocessor, object-oriented programming, or most of the technology I work with. I love and admire my species, living and dead, and am totally dependent on them for my life and well-being,” he concluded.

The email was made public as a part of the Steve Jobs Archive, a website that was launched in tribute to his legacy.

Steve Jobs' widow founded the internet archive. Apple CEO Tim Cook and former design leader Jony Ive were prominent guests.

Steve Jobs has always inspired because he shows how even the best can be improved.

High expectations were always there, and they were consistently met.

We miss him because he was one of the few with lifelong enthusiasm and persona.

The Lex Fridman podcast host has interviewed Elon Musk.

Lex is a minimalist YouTuber. His videos are sloppy. Suits are his trademark.

In a video, he shares a typical day. I've smashed my 6-month goals using its ideas.

Here's his schedule.

Morning Mantra

Not woo-woo. Lex's mantra reflects his practicality.

Four parts.

Rulebook

"I remember the game's rules," he says.

Among them:

• Sleeping 6–8 hours nightly

• 1–3 times a day, he checks social media.

• Every day, despite pain, he exercises. "I exercise uninjured body parts."

Visualize

He imagines his day. "Like Sims..."

He says three things he's grateful for and contemplates death.

"Today may be my last"

Objectives

Then he visualizes his goals. He starts big. Five-year goals.

Short-term goals follow. Lex says they're year-end goals.

Near but out of reach.

Principles

He lists his principles. Assertions. His goals.

He acknowledges his cliche beliefs. Compassion, empathy, and strength are key.

Here's my mantra routine:

Four-Hour Deep Work

Lex begins a four-hour deep work session after his mantra routine. Today's toughest.

AI is Lex's specialty. His video doesn't explain what he does.

Clearly, he works hard.

Before starting, he has water, coffee, and a bathroom break.

"During deep work sessions, I minimize breaks."

He's distraction-free. Phoneless. Silence. Nothing. Any loose ideas are typed into a Google doc for later. He wants to work.

"Just get the job done. Don’t think about it too much and feel good once it’s complete." — Lex Fridman

30-Minute Social Media & Music

After his first deep work session, Lex rewards himself.

10 minutes on social media, 20 on music. Upload content and respond to comments in 10 minutes. 20 minutes for guitar or piano.

"In the real world, I’m currently single, but in the music world, I’m in an open relationship with this beautiful guitar. Open relationship because sometimes I cheat on her with the acoustic." — Lex Fridman

Two-hour exercise

Then exercise for two hours.

Daily runs six miles. Then he chooses how far to go. Run time is an hour.

He does bodyweight exercises. Every minute for 15 minutes, do five pull-ups and ten push-ups. It's David Goggins-inspired. He aims for an hour a day.

He's hungry. Before running, he takes a salt pill for electrolytes.

He'll then take a one-minute cold shower while listening to cheesy songs. Afterward, he might eat.

Four-Hour Deep Work

Lex's second work session.

He works 8 hours a day.

Again, zero distractions.

Eating

The video's meal doesn't look appetizing, but it's healthy.

It's ground beef with vegetables. Cauliflower is his "ground-floor" veggie. "Carrots are my go-to party food."

Lex's keto diet includes 1800–2000 calories.

He drinks a "nutrient-packed" Atheltic Greens shake and takes tablets. It's:

• One daily tablet of sodium.

• Magnesium glycinate tablets stopped his keto headaches.

• Potassium — "For electrolytes"

• Fish oil: healthy joints

“So much of nutrition science is barely a science… I like to listen to my own body and do a one-person, one-subject scientific experiment to feel good.” — Lex Fridman

Four-hour shallow session

This work isn't as mentally taxing.

Lex planned to:

• Finish last session's deep work (about an hour)

• Adobe Premiere podcasting (about two hours).

• Email-check (about an hour). Three times a day max. First, check for emergencies.

If he's sick, he may watch Netflix or YouTube documentaries or visit friends.

“The possibilities of chaos are wide open, so I can do whatever the hell I want.” — Lex Fridman

Two-hour evening reading

Nonstop work.

Lex ends the day reading academic papers for an hour. "Today I'm skimming two machine learning and neuroscience papers"

This helps him "think beyond the paper."

He reads for an hour.

“When I have a lot of energy, I just chill on the bed and read… When I’m feeling tired, I jump to the desk…” — Lex Fridman

Takeaways

Lex's day-in-the-life video is inspiring.

He has positive energy and works hard every day.

Schedule:

• Mantra Routine includes rules, visualizing, goals, and principles.

• Deep Work Session #1: Four hours of focus.

• 10 minutes social media, 20 minutes guitar or piano. "Music brings me joy"

• Six-mile run, then bodyweight workout. Two hours total.

• Deep Work #2: Four hours with no distractions. Google Docs stores random thoughts.

• Lex supplements his keto diet.

• This four-hour session is "open to chaos."

• Evening reading: academic papers followed by fiction.

"I value some things in life. Work is one. The other is loving others. With those two things, life is great." — Lex Fridman

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 conda

Install 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 --upgrade

Download 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 1

Almost. 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 1

Stable 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 1

The 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 0.8

It 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 ldm

Hugging 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.ckpt

This 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.

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

1. Free: The simplest API-driven business model that enables unrestricted API access for app developers. Google Translate and Facebook are two examples.

2. Developer Pays: Under this arrangement, service providers such as AWS, Twilio, Github, Stripe, and others must be paid by application developers.

3. 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.

1. Paid assistance The Project Manager can charge for customization because he is quite knowledgeable about the codebase.

2. A full database solution is available as a Software as a Service (MongoDB Atlas), but there is a fee for the monitoring tool.

3. Open-core design R studio is a better GUI substitute for open-source applications.

4. sponsors of GitHub Sponsorships benefit the developers in full.

5. 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

1. 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

2. Bitcoin Cash P2P Business Model Peer-to-peer (P2P) blockchain technology permits direct communication between end users. as in IPFS

3. 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).

4. 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

1. 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.

2. 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.

1. Buy/sell similar models Examples include financial brokers, insurance brokers, and others who match purchase and sell transactions and charge a commission.

2. 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

1. 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.

2. Crowdfunding The oculus headgear would be an example of crowdfunding in essence, with no expectations.

Sketch or Figma?

Designers are pissed.

The beast ate the beauty.

Figma deserves $20B.

Do designers deserve Adobe?

Adobe devours new creative tools and spits them out with a slimy Adobe aftertaste.

• Frame.io — $1.3B

• Magento — $1.7B

• Macromedia — $3.6B

Nothing compares to the risky $20B acquisition.

If they can't be beaten, buy them.

And then make them boring.

Adobe's everywhere.

Like that friend who dabbles in everything creatively, there's not enough time to master one thing.

Figma was Adobe's thigh-mounted battle axe.

• a UX design instrument with a sizable free tier.

• a UX design tool with a simple and quick user interface.

• a tool for fluid collaboration in user experience design.

• a web-based UX design tool that functions well.

• a UX design tool with a singular goal of perfection.

UX design software that replaced Adobe XD.

Adobe XD could do many of Figma's things, but it didn't focus on the details. This is a major issue when working with detail-oriented professionals.

UX designers.

Design enthusiasts first used Figma. More professionals used it. Institutions taught it. Finally, major brands adopted Figma.

Adobe hated that.

Adobe dispatched a team of lawyers to resolve the Figma issue, as big companies do. Figma didn’t bite for months.

Oh no.

Figma resisted.

Figma helped designers leave Adobe. Figma couldn't replace Photoshop, but most designers used it to remove backgrounds.

Online background removal tools improved.

The Figma problem grew into a thorn, a knife, and a battle ax in Adobe's soft inner thigh.

Figma appeared to be going public. Adobe couldn’t allow that. It bought Figma for $20B during the IPO drought.

Adobe has a new issue—investors are upset.

The actual cause of investors' ire toward Adobe

Spoiler: The math just doesn’t add up.

According to Adobe's press release, Figma's annual recurring revenue (ARR) is $400M and growing rapidly.

The $20B valuation requires a 50X revenue multiple, which is unheard of.

Venture capitalists typically use:

• 10% to 29% growth per year: ARR multiplied by 1 to 5

• 30% to 99% growth per year: ARR multiplied by 6 to 10

• 100% to 400% growth per year: ARR multiplied by 10 to 20

Showing an investor a 50x multiple is like telling friends you saw a UFO. They'll think you're crazy.

Adobe's stock fell immediately after the acquisition because it didn't make sense to a number-cruncher.

Designers started a Tweet storm in the digital town hall where VCs and designers often meet.

Adobe acquired Workfront for $1.5 billion at the end of 2020. This purchase made sense for investors.

Many investors missed the fact that Adobe is acquiring Figma not only for its ARR but also for its brilliant collaboration tech.

Adobe could use Figmas web app technology to make more products web-based to compete with Canva.

Figma's high-profile clients could switch to Adobe's enterprise software.

However, questions arise:

• Will Adobe make Figma boring?

• Will Adobe tone down Figma to boost XD?

• Would you ditch Adobe and Figma for Sketch?