Forem: Shahriyar Al Mustakim Mitul

DevOps Prerequisite (Part 9): SSL and TLS

Shahriyar Al Mustakim Mitul — Wed, 02 Oct 2024 10:35:17 +0000

TLS is a certificate ensures the communication is encrypted and server is actually what it actually say it is

For example, assume that you are john and want to access to your account from the website my-bank.com

A hacker might hack the traffic and get your password and then claim your account.

To solve this issue, we use a secret key which is then applied to your password to make it unique

Now, once you want to get access to the server, your encrypted data is passed on the traffic and the hacker might get the data. Still he can't decrypt it

But here is an issue, you need to send a copy of your password to the server to decrypt it.

While doing so, hacker can get the key as well!!! This is called symmetric encryption (uses same key to encrypt and decrypt)

To solve this issue, we use assymmetric encryption (public and private key)

Let's call public key as public lock for now.

Firstly, we encrypt the data with public key/lock. Then we share the name and password along the public key/public lock

But the password can be decrypt only with the private key

So, how we generate these keys?

We generate using ssh-keygen

id_rsa is the private key and id_rsa.pub is the public key/lock

You can now lock your server using the public key.

You can also check that the key under /.ssh/autorized_keys. You can see the public key there.
Let's go back to the bank's situation
Now, we will generate public and private keys on the server.

Then the public key/lock is sent to the user and the hacker might get that as well

The user has a key (symmetric) earlier created to encrypt the data. Now this symmetric key and the lock will combine together and will be sent to the server.

The hacker also gets that

The server uses private key to decrypt the public lock/key.

So, this is how the server gets the symmetric key . Now the server can decrypt the user password and get access to data

But the hacker is not happy and somehow copies the whole website in his server and somehow takes you there

You then share your symmetric key to the server

Now, the hacker decrypt your password and you got hacked!!

But how to know know if a public lock that was shared to me is genuine from the bank server or the hacker?

Basically that public key was shared with a certificate.

The certificate looks like this

Anyone can generate the certificate.So, how to know that?

We know that by the signature. If the hacker did that, the hacker will have a signature on it (self signed)

So, this is how it looked once the hacker sent the user public lock

Gladly, all browser has certificate validation

It checks if a certificate is valid or not!

But for the original certificates, we have CA (certificate authorities). Some are Symantec etc.

So, how to generate trusted certificate?

Using the public key, you request for a signing request (CSR). How to do that?
You use openssl to send your public key and domain name to CAs and it generates a CSR request

The certificate authority then checks and it all information is right, they sign the certificate.

For the hackers case, the certificate will not be validated by CAs

So, these CAs can help validating public websites.To solve issue for private websites, you can install their private version and install in your company PC

The real bank server can also ask for the client to generate a csr to verify if he/she is the real user

Using the CA, the user can generate csr and send to the real server.

The whole thing is called as PKI (Public key infrastructure)

Examples of public key/lock and private keys

Mutual TLS

Assume that mybank.com wants to send some data to abc-financials.com
So, how will abc-financials will know that mybank.com is actually sending data?

This is where mutual TLS works and client and sever will now verify the authenticity of each other.

Assuming my-bank (client) sends some data to abc-financials (server)

Client first requests the server's public certificate.

THe server replies back it's public certificate

The client checks with the CA, if the certificate is valid

Once verified, the client sends a certificate to the server and also shares a symmetric key which is encrypted with the public key of the server.

The server now validates with the CA if the client indeed belong to the mybank

So, in this way, they have both mutually verified each other.

TinyML - Harvard University : Part 1

Shahriyar Al Mustakim Mitul — Wed, 24 Jan 2024 11:15:24 +0000

Learn from the Harvard Professor & Google Engineers

In this blog, I will share my learning from him

How many of you have said, OK, Google?
What happens when you say that?
The machine wakes up and it knows to respond to you.
OK, fine.

You might have said, hey, Siri. Same thing, the machine wakes up and responds back to you.

All right, all right, fine. Perhaps you have said Alexa.

No matter what you have said, they all represent an important application of what's in TinyML.
It's called keyword spotting or hotword detection.

Now, the key difference is that while they resemble the application of TinyML, these devices are largely plugged into the wall, or they require charging. I'm talking about putting TinyML onto these tiny, tiny little processors that are on this board and then forgetting about them.

Let's talk about autonomous drones, drones that are completely independent, that operate fully by themselves.
Imagine autonomous drones that are able to do video surveillance in order to keep us safe by figuring out what's a threat, what's normal, and so forth.

For instance, later on, we'll talk about how
drones are being used in the Amazon forest for preserving our wildlife. So for instance, when the forests are deforested,
we actually can go in and autonomously plant new seeds
so that we can keep the forest growing.

Imagine a situation where you go out into the mall, or marketplace,
or you're at a party. And how many times have you had to say, I'm sorry,
could you repeat that again, right? Imagine if these glasses had contextual hearing.

Or let's talk about what Elon Musk is doing,
where he's implanting chips inside the brain so that they can send
signals to understand brain activity.

By measuring the electrical signals that are emitted by neurons,
we might be able to learn things about our brain.
And in doing so, we might be able to cure diseases like treat depression, insomnia, or any other disease.

To introduce you to a variety of these different kinds of applications
where the fundamental technology that sits in the palm of my hand,
for instance, has the ability to actually have impact at a global level.
So let me be specific and give you an example:

Here, I'm talking about an ElephantEdge project.
There's a growing crisis in Africa right now
about diminishing elephant population.
So organizations are coming together in order to protect the gentle beast.

Now, if we're not careful, these elephants can be wiped out in 10 years, so it's a very important thing.
So how do we help take care of the gentle giants?
Well, we need data. We need lots of data.

So what if we could build some sort of intelligent device
like a smart collar that goes on these elephants that
is totally non-intrusive, does not harm them, but is there,
constantly sensing interesting signals so that we
can help them have a better life?

For instance, if we had a smart collar, we
might be able to do risk monitoring from poaching.
What if we could build machine learning models that
could be put onto small, little devices where
they were able to figure out if, for instance, the elephants were moving
into a high-risk area and then be able to send real-time notification to park
rangers to keep them safe?
The park rangers could then react to them
and to make sure that the elephants go away from that danger zone.
Or perhaps, we can do human conflict monitoring.

We could build intelligent machine learning
models that are able to sense and alert when elephants are heading into an area
where, for instance, farmers live.
So that they can proactively get out of the way
or do something in order to make sure that they're safe
and the animals are safe.

We might be able to do activity monitoring.
We might be able to learn things about the animals.
When are they swimming, drinking water, or sleeping, and so forth?
And by learning all these things, we might
be able to take better care of them.

We might also be able to do communication monitoring.
What we mean by that is that by sensing sound,
we might be able to understand how these animals are actually
communicating together.

But in order to do all of that, we need TinyML.
We need to be right there where the data is, where that information, those sounds, those signals, where all of that is, so that we can do real-time machine
learning.

These are all remarkable applications of TinyML.

So, that's it for this blog. Let's learn more in another blogs.

Unlocking the Power of Auth0: Streamlining Authentication and Authorization for Modern Apps

Shahriyar Al Mustakim Mitul — Thu, 18 Jan 2024 15:28:28 +0000

Auth0 is a powerful tool that can help streamline the authentication and authorization process for modern applications. With Auth0, developers can easily support different flows in their own applications and APIs without worrying about OIDC/OAuth 2.0 specifications or other technical aspects of authentication and authorization .

Auth0 uses the OpenID Connect (OIDC) Protocol and OAuth 2.0 Authorization Framework to authenticate users and get their authorization to access protected resources . This means that developers can easily implement login, signup, and secure API calls using modern security protocols including OAuth 2.0, OpenID Connect, and JWT tokens.

Auth0 supports scenarios for server-side, mobile, desktop, client-side, machine-to-machine, and device applications . This makes it easy for developers to use Auth0 in a variety of different contexts.

One of the key benefits of Auth0 is that it provides a universal login experience for users . This means that users can log in once and then access all of the applications that they have access to without having to log in again. This can help to improve the user experience and reduce the amount of time that users spend logging in and out of different applications.

Another benefit of Auth0 is that it provides a range of different authentication and authorization flows that developers can use in their own applications and APIs . These flows include the Authorization Code Flow, Implicit Flow, Hybrid Flow, and Client Credentials Flow. Each of these flows is designed to support different use cases and scenarios.

In summary, Auth0 is a powerful tool that can help streamline the authentication and authorization process for modern applications. With Auth0, developers can easily support different flows in their own applications and APIs without worrying about OIDC/OAuth 2.0 specifications or other technical aspects of authentication and authorization. Auth0 supports scenarios for server-side, mobile, desktop, client-side, machine-to-machine, and device applications. It provides a universal login experience for users and a range of different authentication and authorization flows that developers can use in their own applications and APIs .

MBA with me : Mitul Shahriyar ( Part 9) Projecting Financial Management

Shahriyar Al Mustakim Mitul — Thu, 18 Jan 2024 10:52:36 +0000

Check if the TAM - Total Addressable Market ( The amount of customer or business one can do with his/her product)
Assume the TAM for one's product is $50 billions and the founder thinks his company can capture 10% of it in 10years

Then build the model building using excel.

Let's now find out what his sales is??

let's just say the average selling price, the product that this company is making, the average selling price of the ASP is $100,000. And so if we take $5 billion in revenue divided by $100,000 per unit, or the average price, then that gets you to 50,000 units sold in year 10.

We only care about revenue.

So, logically this is how the sells should be:

I'm forecasting the year over year growth in the number of units, and so by year 10 you see that they're expecting 50,000 units, and I'll just kind of walk through it until I get the right numbers set up,

and I'll always list everything I'm thinking about as I go through this process, so when I revisit my model I can understand the logic that was in my head at that time.

Okay, so I'm gonna read some of the line items off of my Excel spreadsheet here. So in year three, our guy said he can get to $500 million in revenue, hmm, this seems pretty aggressive. Let's assume it's $400 million.

Now
Okay, so here's where I'm at right now. So, 50,000 units in year 10, I'm at 51,000 now. In 2015 there's 20 units coming to launch then,
200 the next year, then four grand, then 2018 that got 8,400, and then you can see the year over year growth there, which is high. It's still way too high. Look at that triple digit year over year growth there in year 2020 through 2024, unrealistic, unrealistic. But the reason I'm showing this slide is because

I want to show you that the revenue line item is, quite simply, the number of units multiplied by the average selling price of 100 grand.

So I wrote here, again, there must be competition at some point, so we have to haircut the average selling price. So we'll assume competition enters the market in three years, and at that point the price drops from 100 grand down to something else.

So we'll assume competition enters the market in three years, and at that point the price drops from 100 grand down to something else. And so I did it right here, you see that, actually by the end of the third year and into the fourth year, I assume that the pricing point is no longer $100,000.

It actually drops to $90,000. That's why I multiply it by 0.9.

Okay, so we took a haircut pricing wise.

NOTE: $100 Grand was our ASP

And then I assume that by year 10, or 2024, whatever it is, you get a 40% price cut.

What about Expense??

So for this company
we have a cost of goods sold model out there as 10% gross margins (GM).

And it goes down to 60% or it goes up to 60% in 2018.

Higher is better because you're making more gross margin profit on that item.

You add sales and marketing that's S&M, general administrative that's G&A, and then R&D, which is research and development. And almost all companies have these three lineups,

Okay, so we don't really put it in tax until year three because we weren't profitable until year three.

say you lost 20 million bucks in year one and year two, you can carry that forward and you'll never pay taxes until you make up for that $20 million in losses.

So that means that the first $20 million going forward, for example, in taxes you're supposed to pay, you're not paying them.

They're carried forward. Those are called NOLS or net operating losses.

I wanted to make this a very quick study for you. So I ask now is the $350 million valuation that we paid from a venture capital perspective to invest in this company attractive or not?

you might not know for quite some time, but people are usually growth or value on that spectrum.

And if you're stuck in the middle, then that's called GARP or growth at a reasonable price.

And so venture capital investors and tech investors are growth investors. And people that like to buy stuff that's cheap, meaning outside of tech, are value investors.

And all great companies in technology go from growth, and then when they mature, remember the last stage, remember the red bar with a shark, when large companies or tech companies, when growth slows they mature, they transition from growth slowly to value.

And that transition when these companies are big and mature takes at least 10 years. And that's purgatory from an investing perspective.

Why?

Because growth investors won't touch the stock because it's not growing fast enough. And value investors won't touch the stock because it's not cheap enough.

And our value investors who value based on earnings are paying 10 times earnings in five years.

So 2020, roughly at that point in time, the company will be valued at $5 billion or 10 times $500 million in earnings. Great.

Practice Optimizing Prompts

Shahriyar Al Mustakim Mitul — Fri, 05 Jan 2024 06:04:02 +0000

The objective here is to begin your journey and build confidence in your ability to master AI in the future.

Step 1: Choose Your Scenario
The following are two scenarios where you might want to have the support of AI. Choose one that best suits your interest or think of your own real world scenario.

Scenario A Content Creation

You, as a member of our marketing team, are tasked with creating a blog post about our company's [latest product release]. The blog post is due in three days. Your mission is to provide essential information and product details, defining your target audience. To help expedite the process, you plan to generate an initial draft of the post.

Scenario B Meeting Preparation

You are a project manager at [company/department] and you have a crucial [project update] meeting with the executive team scheduled for tomorrow. To help create a concise and impactful presentation that showcases the project's success and addresses any potential issues, you would like to prepare using support from AI. You plan to prompt the AI Chatbot to generate the following: a summary of the project's progress, key milestones, and potential challenges.

Step 2: Trial with your initial prompt

Once you have signed up for one of the AI Chatbot platforms (e.g.,
ChatGPT
,
Google Bard
, or
Microsoft Bing
). Start with your selected scenario and think about how you would pose your first initial prompt. This is your chance to start experimenting!

You might need to customize the scenario and add more details in the placeholders. Just remember to consider data privacy and avoid sharing sensitive information.

Enter your prompt into the chatbox. Pay attention to the AI response and make note of how it responded to your initial input. Was it clear? On-point? Did it meet your expectations?

Step 3: Revise your prompt

Based on the AI response, review and revise your prompt. You might need to clarify or add additional context to improve the AI's responses. Enhance your prompt by specifying your intent and defining the required tone or formatting. Moreover, you can provide examples to delineate the desired structures or outcomes. In other words, you are teaching the AI to tailor its responses according to your question or instruction. Repeat this step as many times as needed.

Example:

Step 4: Compare and reflect

After multiple rounds of interaction, compile all the prompts you have used and the responses you have received (AI Chatbots may archive the conversations automatically for you). Analyze the changes made and observe how AI has responded differently. Reflect on your learning throughout this process. How has each revision improved the outcome? Is the final result more precise, relevant, and in line with what you anticipated? Document your observations, as this will be an important resource in learning to optimize AI interactions in your future tasks and you may share your thoughts in the discussion forum.

MBA with me : Mitul Shahriyar ( Part 7) Managing the Cash Flow

Shahriyar Al Mustakim Mitul — Mon, 04 Dec 2023 05:23:37 +0000

And you have to always know when your year ends && there's something called the fiscal year, and most companies have a calendar year, meaning that's their last quarter, the fourth quarter, ends in December, okay.

But some companies actually have fiscal years that end during different months.

And I know it sounds very strange. So, retail companies, for example, they tend to have their fiscal year ending in January, meaning the fourth quarter for them ends in January.

Why? Because they want to account for the holiday shopping and returns after the holidays as well. And so, a lot of retail stores will have these Black Friday events, which is, I think, the last Friday in November in the United States, where there'll be a lot of deals, and it's right after American Thanksgiving, and people line up around the block all night long, and they get to buy stuff from stores very cheap, for very low price. And this is called Black Friday because most retail companies in the United States are in the red for the whole year, meaning they're losing money, until Black Friday, when they break even, they're in the black.

I know it sounds unfair, but there are companies out there that have quarterly numbers, and they have to make those quarterly targets or Wall Street punishes their stock. And some companies will actually pull revenue in from the next quarter into the current quarter, meaning each quarter, instead of having 90 days, has 95 or 96 days, which obviously it doesn't, and they break the law. And a lot of these people go to jail. So, just be really careful when you're forecasting and when you work with others that forecast as well.

So, how long can we measure, or how can we measure how long it takes for assets and liabilities to actually turn into cash? Well that's something called the "cash conversion period ratio."

So, here's the example, if we have $5000 of inventory, right, or banana watches, we have $5000 worth. And the average daily cost of goods sold for our banana watches is 100 bucks, then that means we have 50 days worth of cost of goods sold in inventory.

Okay, so another way to think about this is, if we put another one dollar into inventory, it won't be converted into cash, or cost of goods sold, for another 50 days, okay So inventory is just gonna absolutely destroy a company.

so producing too much stuff in inventory is a big mistake. And the Japanese kinda perfected this process back in the '80s called a "just-in-time," or JIT. Where they only produce stuff the second you need it.

Okay, another ratio is the inventory to sale conversion period. And that's basically average inventories divided by cost of goods sold, divided by 365. And that's to kinda measure on a yearly basis. If you want to measure on a quarterly basis, of course you'd use 90 days instead of 365.

Okay so, if we sell our product on credit, right, meaning we don't get cash, somebody pays us with a credit card.

Can we track how long it takes for us to collect the cash? We sure can. It's called the "sale to cash conversion period," and you basically take average receivables divided by sales, divided by 365.

It's actually good practice, like I've mentioned before, to pay your bills as late as you can, without upsetting your business partners or incurring late fees. And there's a way to measure this, and that way is as follows:

it's called the "purchase to payment conversion period," and it's average payables plus average accrued liabilities divided by cost of goods sold, divided by 365.

All right, so short term forecasting is primarily about cash flow estimates.Many assumptions are made and many assumptions are based on sales. Right, so, forecast sales first, and then everything else is just a percent of sales going forward.

MBA with me : Mitul Shahriyar ( Part 6)

Shahriyar Al Mustakim Mitul — Wed, 29 Nov 2023 14:52:22 +0000

"Confidence is contagious . So as lack of confidence" - Vince Lombardi

We are here now:

Assume that you have a company called Banana Watch

Balance Sheet
What you own or what things people own from you etc.

Stuffs you own = assets
People who own stuffs == Equity
Banks own from you == Liabilities

assets = equity + liabilities.

So, assets can be broken down further, into current assets which is stuff you can sell in less than year, and long term assets, which is stuff that you can't sell in less than a year.

Meaning it takes you more than a year to sell the stuff. Liabilities can be broken down as follows. Current liabilities is debt that you owe in less than a year like credit cards, and long term liabilities is debt that you owe in greater than one year like your mortgage. And then equity is just the people that own your stuff including you.

So, assets, current assets equals cash because cash can be converted into itself (laughs) within less than a year, and treasury bills.

So, say you're on treasuries or bonds. That kind of stuff, you can cash in, in less than a year in this example. And then, liabilities, or sorry.Long term assets is stuff like a factory. You see there's a factory there in that picture. That's a very famous album and somebody please, write in the comment section on this course what album cover that is for what band. I'll be really impressed, I'm dating myself here. I'm older than a lot of you, I'm sure, watching this. Okay, liabilities, current liabilities includes credit cards as well as payroll. You have to pay your employees in under a year.
You've got to pay back a credit card in usually a month or less.
Long term liabilities, in this case, let's assume it's banks, okay?

I included mini banks and I mentioned this earlier, I'm gonna reinforce it again. You've always gotta make sure that if you deal with banks, and you shouldn't early on, but if you do later onin the lifecycle of your company, you've gotta deal with multiple banks.
Small increments, why?

Because you want those banks to compete. You want them to compete with you to give you the best rate possible. You want to keep them in check. Kind of like you'd never just have one employee responsible for everything because she or he could quit and you're screwed.Or she or he could ask for more money. You wanna have many employees with different tasks if possible. And then equity is just the people, including yourself, that own your assets, own your company. You'll notice that the left side, assets, has to equal liabilities and equities.

Income Statement

Okay, so in our hypothetical corny example that I created,

the Banana Watch Corporation, we've sold $1000 watches. So look at the sales on there, okay? We sold 1,000 watches at $300 each.
That's $300,000 in sales or revenue, same thing. The cost to make those watches we sold, is about $200 each. So $200 times 1,000 watches is $200,000 so sales minus the cost of goods sold or COGS is sales minus the cost of goods sold, is $300,000 minus $200,000 and that's $100,000 and that's called gross profit. Don't ask me why the accounting idiots call it gross profit, it is what it is, okay.

It's just profit that's gross, I don't know why it's gross profit, stupid. So that's $100,000.

And then below that we have all these other expenses and those are called operating expenses or the cost to operate our business. And there sales marketing, S&M, R&D, research and development and also other expenses like, G&A or general expenses. And then we got something called depreciation. And this is messed up, man, but you're allowed to deduct the cost, or the amount you used your machine or car each month. And that's how much it depreciate, like wear and tear. What is the wear and tear on your car? It's so crazy but you can deduct it, right? And it's awesome you can do that and I'll tell you why.
Because the government wants you to invest in your business by buying more machines or more cars. And so you can, the tax benefits is this, if you can deduct that as an expense each month or each quarter, the depreciation expense, even though it's not real, then the tax you pay is lower, right? Okay, so sales minus the cost gets sold is gross profit. Gross profit minus the cost to operate your business, like sales marketing, general expenses, R&D, depreciation, that equals something called operating profit, Or earning before interest and taxes, or EBIT or E-B-I-T, earnings before interest and taxes. And you're saying, why the hell do I need to know about earnings before interest and taxes, Chris?

Why don't you just go to the bottom line? Go to net income, well you can't. Why? The reason is because every country in the world, and every state, and every industry, and every company, has a different way of paying taxes. Everyone pays a little bit different taxes. Just like you pay different tax than somebody else does in your class or in your company. I pay different taxes than my neighbor.

My parents pay different taxes than me. Why do I mention this? Why is this important? Because it's not apples to apples for me to compare the Banana Watch Company to a company in Switzerland for example, where they make inferior watches to our Banana watch, right?

And so, in Switzerland they have a different tax and interest rate structure. And so, investors in our Banana Watch Company wants to understand how our company compares financials-wise, to the inferior Swiss watches. I'm just joking, if anybody Swiss is watching this, then the Banana Watch sucks, okay?

So that's how you do it. You look at operating profit or earnings before taxes. And then what happens is that's called the line, it's accounting nerd speak, don't ask me why. and below that line you have below the line items, right so, below the line items are interest and taxes, which again are different. And the bottom line is that income. That's why an income statement is set up that way, okay.

It is pretty simplistic, right? But it sounds more complicated than that, that's all it is. And so you might ask yourself, okay Mitul that's pretty cool, so I've got $30,000 in net income.

Obviously Mitul, that means I have $30,000 more in my pocket than before.

No it doesn't. It doesn't. Your cash balance is not going to increase by $30,000. Why?

Because you had non-cash items, okay. Remember depreciation that you got a benefit there, right?

We're not getting $30,000 more in our pocket. We are getting something else. Let's figure out what that something else is.

Okay, so we start with net income at the top of our cash flow statement, right?

We have to deduct that. We want a depreciation on our income statement, so that our earnings are less and we pay less taxes. It's a beautiful thing, right?

And then we're gonna add back the increase in depreciation, right?

Because that cash didn't really leave our pocket, right? We got that benefit from not paying taxes on it. So woo woo, we're up to $32,000 but hold on a second. On our balance sheet, in the current assets section, there's something called accounts receivable and that's gonna hurt our cash balance. Say what?

Well when you sell something, like we sell our Banana Watches, we either sell them for cash or we sell then people use their credit cards, right? Why? Because they just want to pay for it later, right? And so that's called accounts receivable. We have received that cash yet, so we already deduct that okay? So and then what happened was, we actually owed some of our partners money. We bought a lot of supplies for our watches from a company that makes really cool sapphire crystal and sapphire crystal is actually the watch face on our Banana Watch.

And so, we got $20,000 worth of material sapphire crystals but we haven't paid for it yet. That's called accounts payable, right? And so get got $20,000 benefit, temporarily here. So our net cash flow from operations is $42,000. Okay and so you can see the math there in front of you. And so let me just do a side topic before we moving on here.

Okay so let's talk about cash flow from investing. Okay so we bought, we bought a machine. We paid $40,000 for it, right? And so we invested in our company and so that's gonna hurt us we lose $40,000 there, right? But we actually have cash flow from financing of $20,000, because we got a loan for $20,000. So that's more cash in our pocket, right? It's not a good thing but just more cash for now. Right, so if we net all that stuff up, that's a $22,000 increase not a $30,000 increase, okay?

So our beginning bank balance for cash from our balance sheet before was $60,000 and now our ending cash balances is $82,000.

The x-axis is time, the y-axis is the size of the firm, small firm, medium firm to big firm.

Liquidity Ratios

Leverage Ratios

EBITDA means "earnings before interest, taxes, depreciation and amortization."

Okay, other ratios are return on assets.

Whenever you hear the term "return on" something, it basically means net income on the top or profits, same thing, divided by whatever you're returning on. So, net income over assets. Net income over equity.

Suggestions:

When you're managing people you always want to praise in public and criticize in private. OK?
And you always want to approach your boss and ask her him for feedback every three months or so. How am I doing?
You'll never get a raise unless you ask Get a raise. Remember the Steve Jobs ask video.
So you have to ask to get promoted and how do you do this? Well, you sit down with your boss and you ask her him, What do I need to be considered for promotion to the next level?

And they'll tell you. And you create a list of those items, and once you achieve them, just very politely sit down with them and say, I've achieved all these milestones that we spoke about.
Can I please get a promotion or can I please get a raise?

Note:
Depreciation;

Current Ratio:

Interest coverage ratio:

Generative AI in Google Cloud

Shahriyar Al Mustakim Mitul — Sat, 11 Nov 2023 19:42:51 +0000

What is AI?
AI is a branch of computer science that deals with the creation of intelligence agents, which are systems that can reason, and learn, and act autonomously. Essentially, AI has to do with the theory and methods to build machines that think and act like humans. In this discipline, we have machine learning, which is a subfield of AI. It is a program or system that trains a model from input data. That trained model can make useful predictions from new or never before seen data drawn from the same one used to train the model.

What is ML?
Machine learning gives the computer the ability to learn without explicit programming.

Two of the most common classes of machine learning models are unsupervised and supervised ML models.

The key difference between the two is that, with supervised models, we have labels.

Labeled data is data that comes with a tag like a name, a type, or a number.

Unlabeled data is data that comes with no tag.

This graph is an example of the problem that a supervised model might try to solve. For example, let's say you are the owner of a restaurant. You have historical data of the bill amount and how much different people tipped based on order type and whether it was picked up or delivered. In supervised learning, the model learns from past examples to predict future values, in this case tips. So here the model uses the total bill amount to predict the future tip amount based on whether an order was picked up or delivered.

This is an example of the problem that an unsupervised model might try to solve. So here you want to look at tenure and income and then group or cluster employees to see whether someone is on the fast track. Unsupervised problems are all about discovery, about looking at the raw data and seeing if it naturally falls into groups.

Let's get a little deeper and show this graphically as understanding these concepts are the foundation for your understanding of generative AI. In supervised learning, testing data values or x are input into the model. The model outputs a prediction and compares that prediction to the training data used to train the model. If the predicted test data values and actual training data values are far apart, that's called error. And the model tries to reduce this error until the predicted and actual values are closer together. This is a classic optimization problem

What is Deep Learning?

Deep learning is a type of machine learning that uses artificial neural networks, allowing them to process more complex patterns than machine learning.

Deep learning models typically have many layers of neurons, which allows them to learn more complex patterns than traditional machine learning models. And neural networks can use both labeled and unlabeled data. This is called semi-supervised learning. In semi-supervised learning, a neural network is trained on a small amount of labeled data and a large amount of unlabeled data. The labeled data helps the neural network to learn the basic concepts of the task while the unlabeled data helps the neural network to generalize to new examples.

What is Generative AI then?

Gen AI is a subset of deep learning, which means it uses artificial neural networks, can process both labeled and unlabeled data using supervised, unsupervised, and semi-supervised methods.

What is LLM then?

Large language models are also a subset of deep learning.

Deep learning models, or machine learning models in general, can be divided into two types, generative and discriminative. A discriminative model is a type of model that is used to classify or predict labels for data points. Discriminative models are typically trained on a data set of labeled data points. And they learn the relationship between the features of the data points and the labels. Once a discriminative model is trained, it can be used to predict the label for new data points. A generative model generates new data instances based on a learned probability distribution of existing data. Thus generative models generate new content

Take this example here. The discriminative model learns the conditional probability distribution or the probability of y, our output, given x, our input, that this is a dog and classifies it as a dog and not a cat. The generative model learns the joint probability distribution or the probability of x and y and predicts the conditional probability that this is a dog and can then generate a picture of a dog.

The top image shows a traditional machine learning model which attempts to learn the relationship between the data and the label, or what you want to predict. The bottom image shows a generative AI model which attempts to learn patterns on content so that it can generate new content.

If the y is the number, like predicted sales, it is not gen AI. If y is a sentence, like define sales, it is generative as the question would elicit a text response. The response would be based on all the massive large data the model was already trained on

The gen AI process can take training code, label data, and unlabeled data of all data types and build a foundation model. The foundation model can then generate new content. For example, text, code, images, audio, video, et cetera.

In the generative wave, we as users can generate our own content, whether it be text, images, audio, video, et cetera, for example models like PaLM or Pathways Language Model, or LaMDA, Language Model for Dialogue Applications, ingest very, very large data from the multiple sources across the internet and build foundation language models we can use simply by asking a question, whether typing it into a prompt or verbally talking into the prompt itself. So when you ask it what's a cat, it can give you everything it has learned about a cat. Now we come to our formal definition.

Gen AI is a type of artificial intelligence that creates new content based on what it has learned from existing content. The process of learning from existing content is called training and results in the creation of a statistical model when given a prompt. AI uses the model to predict what an expected response might be and this generates new content. Essentially, it learns the underlying structure of the data and can then generate new samples that are similar to the data it was trained on. As previously mentioned, a generative language model can take what it has learned from the examples it's been shown and create something entirely new based on that information.

A generative image model takes an image as input and can output text, another image, or video. For example, under the output text, you can get visual question answering while under output image, an image completion is generated. And under output video, animation is generated.

A generative language model takes text as input and can output more text, an image, audio, or decisions. For example, under the output text, question answering is generated. And under output image, a video is generated. We've stated that generative language models learn about patterns and language through training data, then, given some text, they predict what comes next. Thus generative language models are pattern matching systems.

Here is another example. The meaning of life is-- and Bart gives you a contextual answer and then shows the highest probability response. The power of generative AI comes from the use of transformers.

Transformers produced a 2018 revolution in natural language processing. At a high level, a transformer model consists of an encoder and decoder. The encoder encodes the input sequence and passes it to the decoder, which learns how to decode the representation for a relevant task.

In transformers, hallucinations are words or phrases that are generated by the model that are often nonsensical or grammatically incorrect. Hallucinations can be caused by a number of factors, including the model is not trained on enough data, or the model is trained on noisy or dirty data, or the model is not given enough context, or the model is not given enough constraints. Hallucinations can be a problem for transformers because they can make the output text difficult to understand.

What is Prompt?
A prompt is a short piece of text that is given to the large language model as input. And it can be used to control the output of the model in a variety of ways. Prompt design is the process of creating a prompt that will generate the desired output from a large language model

We've shown illustrations of the types of input based upon data. Here are the associated model types. Text-to-text. Text-to-text models take a natural language input and produces a text output. These models are trained to learn the mapping between a pair of text, e.g. for example, translation from one language to another

Text-to-image. Text-to-image models are trained on a large set of images, each captioned with a short text description. Diffusion is one method used to achieve this.

Text-to-video and text-to-3D. Text-to-video models aim to generate a video representation from text input. The input text can be anything from a single sentence to a full script. And the output is a video that corresponds to the input text. Similarly, text-to-3D models generate three dimensional objects that correspond to a user's text description. For example, this can be used in games or other 3D worlds.

Text-to-task. Text-to-task models are trained to perform a defined task or action based on text input. This task can be a wide range of actions such as answering a question, performing a search, making a prediction, or taking some sort of action. For example, a text-to-task model could be trained to navigate a web UI or make changes to a doc through the GUI.

A foundation model is a large AI model pre-trained on a vast quantity of data designed to be adapted or fine tuned to a wide range of downstream tasks, such as sentiment analysis, image captioning, and object recognition. Foundation models have the potential to revolutionize many industries, including health care, finance, and customer service. They can be used to detect fraud and provide personalized customer support.

Vertex AI offers a model garden that includes foundation models. The language foundation models include PaLM API for chat and text. The vision foundation models includes stable diffusion, which has been shown to be effective at generating high quality images from text descriptions.

Let's say you have a use case where you need to gather sentiments about how your customers are feeling about your product or service. You can use the classification task sentiment analysis task model for just that purpose. And what if you needed to perform occupancy analytics? There is a task model for your use case. Shown here are gen AI applications.

Let's look at an example of code generation shown in the second block under code at the top. In this example, I've input a code file conversion problem, converting from Python to JSON. I use Bard. And I insert into the prompt box the following. I have a Pandas DataFrame with two columns, one with the file name and one with the hour in which it is generated. I'm trying to convert this into a JSON file in the format shown onscreen.

Bard returns the steps I need to do this and the code snippet.

And here my output is in a JSON format. It gets better. I happen to be using Google's free, browser-based Jupyter Notebook, known as Colab. And I simply export the Python code to Google's Colab.

To summarize, Bart code generation can help you debug your lines of source code, explain your code to you line by line, craft SQL queries for your database, translate code from one language to another, and generate documentation and tutorials for source code. Generative AI Studio lets you quickly explore and customize gen AI models that you can leverage in your applications on Google Cloud. Generative AI Studio helps developers create and deploy Gen AI models by providing a variety of tools and resources that make it easy to get started!

Generative AI Studio helps developers create and deploy Gen AI models by providing a variety of tools and resources that make it easy to get started. For example, there's a library of pre-trained models. There is a tool for fine tuning models. There is a tool for deploying models to production. And there is a community forum for developers to share ideas and collaborate. Generative AI App Builder lets you create gen AI apps without having to write any code. Gen AI App Builder has a drag and drop interface that makes it easy to design and build apps. It has a visual editor that makes it easy to create and edit app content. It has a built-in search engine that allows users to search for information within the app. And it has a conversational AI Engine that helps users to interact with the app using natural language. You can create your own digital assistants, custom search engines, knowledge bases, training applications, and much more.

PaLM API lets you test and experiment with Google's large language models and gen AI tools. To make prototyping quick and more accessible, developers can integrate PaLM API with Maker suite and use it to access the API using a graphical user interface. The suite includes a number of different tools such as a model training tool, a model deployment tool, and a model monitoring tool.

MBA with me : Mitul Shahriyar ( Part 5 )

Shahriyar Al Mustakim Mitul — Wed, 25 Oct 2023 05:54:55 +0000

So we're now in years 3 to 4 on our journey, in terms of what's next after this. After this eventually we'll get ready to go public.

Let's learn from a situation:
Assume this famous athlete created Paypal and submitted it's Proof of Concept to venture Capitalists

So he's got kind of a test version, or a proof of concept version of this terminal.

Okay?

But he needs a million bucks to build a real version of it, not just a prototype version, a real version. And so, here comes Sequoia. And Sequoia is the best hedge capital firm in the world and they wanna back him.

Initially, Giancarlo launched his payment company, last year he had $10,000 in equity capital, or of his own money, okay?

And he decided to launch the company then last year with 2 million shares, okay? Don't over think this, just accept, 2 million shares, right?

Now,
He needs to negotiate with Sequoia on how many shares they are going to get in his company in return for money that he can use to fund his growth.

So Sequoia and Giancarlo agree that in 5 years his company is gonna make a million bucks in net income, that's pretty good, five years from now, he'll make a million bucks.

Okay, a competitor of Giancarlo's just went public, just an initial public offering, okay? And this competitor did this at a valuation of 20 million dollars, and this competitor had 2 million dollars in income. That means the price range ratio is 20 million valuation, the price, divided by the earnings, 2 million, 10 times.

A 10 times p/e multiple,

So in five years,

Giancarlo wants to go public as well, okay? And so the valuation of his company in five years should be as follows. If the competitor of Giancarlo's firm is public, and trades at 10 times earnings, then his firm should trade at 10 times earnings in five years.

Giancarlo's firm is gonna make a million bucks. And that means a valuation of 10 million (10*1 million [earned in 5 years]) bucks in five years.

In five years, his company will be worth 10 million dollars.

So what is his firm worth today?

So here's how we get there. Sequoia expects to make 50% per year, okay? So we have to calculate what his company

in five years is worth today. So again in five years, his company is worth 10 million bucks, and Sequoia is only gonna invest if they can make 50% return every year, okay?

So, here's the math. So we discount that 10 million bucks to today. And the way you discount, and we'll cover this during our DCF

we're discounting that 10 million bucks. The value of his company in five years, to today. And we're doing it at Sequoia's expected rate of return, which is 50%, okay?

So, currently

So the value today is that Sequoia owns a million bucks worth, remember they're investing a million bucks?

Divided by 1.32 million (Valuation this year), so they own 76% of the company.

So that means the owner own 24%, okay? Or Giancarlo owns 24%.

And he's got 2 million shares initially, right?

Now, let's learn how much he has left with

So total shares is 2 million divided his .24 (24%), which equals 8.3 million shares, it's just math.

2000000%(.24)=8333333.33 shares = 8.3 million shares

That means Sequoia owns 6.3 million shares.

8.3 million (now shares) - 2 million ( initial shares) = 6.3 million shares

So the share price is 15.8 cents per share. That's what the share price is. Right?
1000000 (Sequoia invested 1 million) % *6.3*1000000) million shares ( Sequoia ownes 6.3 million shares now) = $ 0.158730 = 15.8 cents

So how much does Giancarlo own?

Well he owns 2 million shares (Initially started with this) times 15.8 cents per share. Right, which is $316,000 dollars. This is called the pre money valuation of his company, right?

And then the total valuation of the company is 8.3 million shares (Previously total shares is 2 million divided his .24 (24% owned by the owner now), which equals 8.3 million shares,).

You know, his 2 million plus Sequoia's 6.3,

time 15.8 cents, which equals 1.31 million dollars!!

So the post money valuation, the value of the company after the money was given from Sequoia is 1.31 million dollars.

So, in 5 years, the company worth is going to be 10 million dollars and he has 24% of the company and he will be worth $2.4 millions now

Unless anything goes wrong!

After the valuation, it is 10 million dollars

So Sequoia just led what's called the A round, or the first round, okay?
Giancarlo (The owner) just did an A round with Sequoia, lucky him, Sequoia's awesome.

Uh oh, oh shoot.Breaking news!!!

So, what happened was

Giancarlo (The owner) got injured, right? This is a bit of a setback, he's gonna be okay, he got injured.

Okay, so something happened,

Giancarlo got hurt, his company got hurt.

Okay?

So now we're in year three and we need more money. Shoot, we ran out of money faster than we thought we would.

Alright, so. Cash is king, okay?

So, we did the A round with Sequoia in year one, okay? And in year five we wanna go public, right? And then Kleiner is now, the second venture capital firm, and they're leading the B round, okay?v

So, we're in year three, and we need another million bucks, yeesh.

We still wanna go public in year five at a valuation of 10 million dollar

So Kleiner expects a 25% return for 2 years until the company goes public. How did they come up with the map?

Well Sequoia still expects a 50% annual return, and unfortunately,

Kleiner Perkins, which is a great firm and so is Sequoia, and what they're doing in this hypothetical example it's not their fault, it's the banner's fault. But Kleiner Perkins needs shares, right?

So Kleiner's expected return is a million bucks, and thus they are

investing a million bucks now at 25% return over 2 years.

Which means that in 2 years, their million dollar investment is 1.5625 million dollars, okay?

1000000 ( 1 million Kleiner is investing) * (1+25%)^2 = 1.5625 Million
Here they are expecting 25% return and in 2 years because within 2 years, this company is going to be public.

So Kleiner's ownership is 1.56 million dollars divided by 10 million bucks or 15.6%, okay?

Sequoia remains there shares and lost nothing

But the owner becomes the victim and comes in dillution.

So our ownership, or Giancarlo's ownership goes from 24%, to 8%.

So, how many shares are available now???

So, sequoia now have 18 million shares

As, 24 million shares new exist and 76% is owned by sequoia

It actually gets worse because, we as Giancarlo forgot about employee ownership via stock options, remember,

you always want to incentivize employees, right? By giving them options, right?

And these options only vest or become valid or you're allowed to cash them in every four years.

So it's the golden handcuffs keeping you in place as an employee.

Alright let's move on. So, employees need shares too.

So, right now, we had to give 6% of shares away to employees, and remember we owned 8.4% of the company? Well now that we have to give 6% of shares away to employees because we forgot to include that in our legal documents early on, we only own 2.4% of the company now, that's tragic, tragic!!

It's not Sequoia's fault.

It's not Kleiner's fault.

It's my fault, I'm Giancarlo.

why do we issue stock options?

Well, it's cheaper than paying a salary, because we don't have that much money, right? So I'm gonna give my employees part of the company. It motivates everybody to work hard as a team, and it's basically golden handcuffs. And there's something called vesting, which means, you can't benefit from ownership in stock options until you've held them for four years, okay?

They vest. Vest every four years.

So, the company have 82 million shares now!!

And the options (That we give to employees; their percentage is 6%) are that many shares,5 million shares, so,

we got diluted by 90%, yeesh!

outside venture capital investors are protected against dilution.

Why?

Because they own preferred shares, they're preferred. We get common, (Giancarlo gets common) Okay?

Don't know what is common share and what is preferred?
Read this out

And so, you need lawyers, you need lawyers. And founders of companies really need to understand dilution before dealing with venture capital firms.

It's not all that bad though, because founders of companies get massive option grants anyway, and, every year, like Larry Ellison would get a lot of options every year,

So, he could actually, hypothetically speaking, be worth a heck of a lot more, if the value of his company goes up materially after the IPO. It works out well.

But you do get diluted, just keep in mind, if you deal with a venture capital firm, or equity investors as opposed to banks, you're gonna give up ownership of your company.

But hopefully your company's worth a lot more money over time so it becomes a moot point.

But don't, don't do debt, if you're an early stage company, because if you have one little hiccup like we just did here with Giancarlo, you're done, you're done, banks don't care.

If you miss one payment, they'll screw you, they'll take everything.

But it's okay, because you're protected, and so is your family, because you have an LLC, or a limited liability corporation structure set up.

A lot of the most successful entrepreneurs in the world have failed many, many times, before they succeeded.

Michael Jordan once had this great quote. He's the best basketball player of history, of course, in history, he said that,


"I failed many, many times in life,

"and that is why I succeeded."

So venture is very hard, in order to return the capital on a 400 million dollar fund, you have to have 20% of your funds or two unicorns in your fund, it's really, really tough,

the Silicon valley is where all the old school companies are, right by Stanford. Ebay, Google, old school, I know. Yahoo!, Oracle, EA.

And all the cool new companies are up in San Francisco there, like Airbnb, or Uber, or Salesforce. AppDirect, Udemy of course, which is an awesome company by the way

Read this called Internet Trends

So, we are done!

MBA with me : Mitul Shahriyar ( Part 4 )

Shahriyar Al Mustakim Mitul — Mon, 23 Oct 2023 13:52:09 +0000

History of Silicon Valley and Venture Capital

If any atom boma would hit USA, using internet , the government could contact at least.
So, this was one of the priority that time.

So, it was part of USA Government Military Research and most tools we use now is part of that too.

But all these brands only exist because of government

funding of weapons research to compete with Russia And there's big push-back as well on this

America was absolutely terrified of Russia, and Russian military might, and so what happened was America invested in weapons research, which led to the invention of many technologies.

I'll give you some more examples,'cause this really is interesting.
GPS, which we all use in our cell phones for when we use map navigation, was created from guided missile research.

The database where all information is stored exists only because of the CIA's project Oracle, which was Oracle's first customer in the 1970s
The microchip was actually financed by NASA so that NASA could put the first person on the moon before the Russians could.
And Palantir, which is the largest employer right now in Palo Alto, even larger than Facebook, Palantir was financed by the CIA's venture capital division, and for those of you that haven't heard of Palantir, it's this amazing software company here in the Bay area that is solving the world's biggest problems. In fact, the Obama administration would not have found Osama bin Laden if it weren't for Palantir software. So it's artificial intelligence based software that solves the world's biggest problems, founded here in the Bay Area because of government research.

So, the Cold War and competition to compete with Russia is one of the reasons that many great technologies exist, so anyway, a little bit of background. So that's enough about war.

Then the peace movement, racial discrimination reduction and many movement came up.

And so, the richest family in America was the Rockefellers. As you know, they owned Exxon, right?

They had a VC division called Venrock, and Venrock invested in a company in the '60s called Fairchild Semiconductor. And the reason they did was because Sputnik, or the Russian satellite, beat America to space, and so America were brokenhearted during the early 1960s.

And so, the Kennedy administration decided to create NASA, which is awesome, and then NASA basically wanted to get the first person on the moon before the Russians did. It was a national pride issue. And they couldn't do it, because they couldn't fit 100,000 little transistors or chips into the fuselage or top part of a rocket. And so, what happened was NASA financed this company called Fairchild, and Fairchild figured it out.

Fairchild got too big,therefore they couldn't innovate anymore, which was tragic, right? And so, they became bureaucratic and many people quit. And many people quit and a lot of Fairchildren (laughs) companies were born,

A couple examples of those chip companies include AMD, NVIDIA, and of course Intel. All those companies came out of Fairchild, right, and so the semiconductor sector was very vibrant in the Bay Area, and the hardware sector kicked ass with companies like HP, and then software around that like Oracle and all these other great firms, and then the internet sector: Google, Facebook, et cetera.
You get it!!

Because if you're an executive at a large company and the founder leaves, the founder wanted to change the world. The rest of the executives just care about climbing the corporate ladder, and politics sets in. And so, these executives climb the ladder. All they care about is trying to get to the top because they get paid more. And the second they try to innovate or step out of line to innovate, if they're not successful, they're done, man.

They're not climbing the corporate ladder anymore. And if they are successful, they're not gonna get paid anyway.

Why?

Cause nobody wants to disrupt the whole corporate pay structure in a big bureaucracy with the founders no longer there. So, the incentive is to leave, start a company, and get funded by high net worth investors, angel investors, seed investors, or venture capitalists.

And in the internet space here in the Valley, the PayPal Mafia runs the Valley today. Hey, what does that mean, Mitul?

Well, PayPal is the most important company to go public in the past 20 years.
Yeah, controversial, I know. More important than Google, more important than Facebook, more important than any of those other companies, because PayPal went public and was the first successful IPO after 9/11. And then more importantly, what happened was a lot
of amazing executives came out of PayPal, and they came out of PayPal and started their own companies.

I'll give you examples.

The founder of LinkedIn worked at PayPal. His name is Reid Hoffman.

The founder of Tesla and SpaceX worked at LinkedIn, or pardon me, worked at PayPal. Of course, he's Elon Musk.
The founder of Yelp came from there. The founder of YouTube came from PayPal, et cetera. So, we call that the PayPal Mafia.

I mention that story because I wanted to reinforce the importance of betting on a strong management team that's had a past exit, okay. And the PayPal Mafia, they had a fantastic exit, and they've been incredibly successful. And so, many other companies that I haven't even talked about came out of PayPal, including Clarium.

Peter Thiel, of course, runs Clarium. He's probably one of the best investors on the planet. And other firms like Yammer, et cetera. And so, venture capital firms love backing the same executives again, because the probability again of you making money by investing in somebody that's already been successful and has already had exits is higher than those that have not, okay. And so, basically the top venture capital firms get all of the great deals.

It's just how it works. The top 10 firms or so are the most relevant, and it's hard to compete.

Other companies include Sequoia.

So, Sequoia is incredible. It's the best venture capital firm here in the Bay Area. And check this next slide out. They really emphasize the founders of these companies and not the underlying companies as much.

It's actually brilliant.

Most venture capital in America is in the Bay Area. Now, the sector is extraordinarily cyclical. You tend to only get good exits every 10 years or so.

And so, I mentioned before how a lot of engineers and founders in the Valley are born overseas.

In fact, 60% of engineers in the Valley are born overseas and they come here. And there's a whole notion of if you wanna be an actor, move to Hollywood or Bollywood, and if you wanna be working in technology, move to whatever. And I'm not saying Silicon Valley is the only place in the world where technology companies can prosper. Certainly not the case. But it's interesting to study the environment.

What made them successful here?

So, a lot of dreamers come here. A lot of dreampreneurs. I love it.

There's really a sense of optimism and there's no limits to what you can accomplish here in the Bay Area. And it all started up because of war and peace and the hippie movement, and that took 50 years to develop. And so, other regions of the world that try to develop a commencer infrastructure, you can't do it overnight.

"Be fearful when others are greedy "and greedy when others are fearful." And basically all that means is buy low, sell high, (laughs) that sort of thing. So, there's a reason why they call him the Sage of Omaha. You wanna be a contrarian when it comes to investing always.

So, let's move on to talk about what kind of venture capital firm should you target if you're trying to raise money. Well, you wanna know their stage focus, right? If they're early stage, meaning A or B, and you're an earlier stage company, approach them.

If the firm is later stage, like C or D or sometimes E, late stage, then approach them. Don't approach investors that have no shot of investing in your company because of a different stage focus philosophy.

There's a reason why Peter Thiel's, who's the first investor in Facebook, Peter Thiel's venture capital firm is called Founders Fund. They back founders, right?

So, make sure the venture capital firm you're dealing with hasn't fired a ton of founders.

And so, you wanna only partner with venture capital firms that are somewhat founder friendly. Okay, are they growth or value?

Okay, great. So, how do venture capital firms make money?

We covered this.
2% management fee. I wanna emphasize it again. 2% annual fee they get, right?
And then they get 20% incentive fee. So, again, if you start a company that costs 100 bucks, or you invest 100 bucks in a VC firm and then it's a 10-bagger, so it's worth 1,000 bucks, you get 800 bucks. They keep 20%. So, it's called two and 20, similar to hedge fund, yeah. VC legal paperwork, okay. So, venture capital firms can only have accredited or high net worth investors investing in a VC firm. They give what's called an offering memorandum, which is just legal documents that everyone has to read or at least receive before they can invest.

Okay, so how do venture capital firms get deals? Network, network, network. Did I say network? So, relationships, and I've stressed this so much. It's so damn important. Relationships are more important than product knowledge. And we get the best deals by networking, right?

Okay, so how do VC firms do due diligence?

They do pretty in depth background checks on the management team. They also size up the total adjustable market. They analyze the competitor environment as well.

Whom VCs back?

Security Structures

All right, let's talk about common stock, okay? This is the lowest of the low, okay? It's the last claim on the company, okay?
And, it can be sold to others. And so, what happens is if you invest in a company that is publicly traded, like say Microsoft, MSFT is the ticker, you'll most likely receive common stock.

Early on, venture capital firms, if they invest in your company, they will get better than common stock. You'll get common, if you're the founder.

They'll get preferred shares, right? And so, if a company goes belly up (Earns a lot of money), the first company that get paid, or get the money back first, is the banks, the debt holders, then the preferred share holders, then the common share holders, okay?

So, what are preferred shares?

Well again, they have a senior claim to common shares, right?

They have more power, a liquidation preference as well, meaning if the firm goes belly up or goes IPO, that preferred share holders get paid first. They also get dividends before the common share holders do, right?

So, who gets these shares?
Venture capital firms get preferred shares. They get preferential treatment. because they're taking on a lot of risk. And, the employees get common stock, okay?

What is Convertible Preferred?

So at the IPO, preferred shares convert into common shares, right?

So, what happens if I'm a venture capital firm and I invest in your company, and your company goes public, right? What happens is my shares convert from preferred share into regular common shares. And, I'm not allowed to sell for six months after the IPO, right?So at the IPO, preferred shares convert into common shares, right?

That's called the IPO lockup. And, that's why stocks go down six months after IPO sometimes.

Now, don't ever, ever, please, start a company and have people give you money, get investors, and value the company too high.

I know it sounds ludicrous but I'm gonna give you an example, okay? Let's say you started a company that made clickers, right?

Let's say you started a company that made

clickers, right? And, you don't have any revenue yet. And, some rich dude gives you, I don't know, 100,000 dollars, right? And he says, okay. will only give you a hundred grand . If you value your company at 50 million bucks, right.

And so, say you own half the company after this. And you're like, wow, I'm worth 25 million on paper. Well, you're not, right? And, it's the death wish because you'll never be able to do another round higher. And, what happens is, bare with me here, when somebody does the A round and they invest in your company, it's done at a certain valuation. And, people will only do the B round, or give you more money, at a higher valuation.

Why? Because these people want to get a return on their investment, right? They want to mark it up, right? If these people have to do an investment round below, right, or a new investor's coming in to do below, then what happens is all your early investors get really pissed off. They get really pissed off at you because they're losing money on their investment now.

Let's learn by an example:

OK, so a venture capital firm called Sequoia is going to invest.

They're going to lead the series A.

Now you the entrepreneur own 10% of the company at a valuation of a million dollars ($1000000), right?

So basically that means that you own a hundred thousand ($100000 or 100k [1 Million's 10%]) dollars worth, right?

Or a hundred thousand shares. Let's assume there's a hundred thousand shares.

OK, so now Kleiner Perkins, another amazing metro-capital firm comes in, and they do the series B at a 100% premium valuation (Previously it was 1million and at stage B, new investors are adding 1 million more to the previous valuation which makes it a 2 million dollar valuation),

a two million dollar valuation, and so new shares are created so that you can give the shares to Kleiner Perkins.

And Sequoia's not selling their shares,

nor should they, it's not fair.

So all of a sudden, you, the entrepreneur, you used to own 10% of your company, now you own less than that.

So all of a sudden, you, the entrepreneur, you used to own 10% of your company, now you own less than that. You got diluted because you had to bring in a new investor, right? I know, it doesn't seem fair, does it? So a lot of shares were created for Kleiner Perkins.

So, anyway, the value of your stake in the company goes up a lot

but you're not 100% richer, right, even though the valuation in the most recent round was two million versus one million in the first round. In fact you own about 7% of the company.

This is why vc firms usually invest close to 80% of a fund, and they leave 20% leftover so that they can invest more money so they don't get diluted in the good deals. Not all deals, but the good deals And that's called a capital call,the vc firm will then call their investors and say, "Hey, I'm calling for capital." And then you'll contribute more of your investment.

**
Convertible Debt**

Say you're a startup. And you just did your A round with Sequoia. You wanna do the B round in two years, but unfortunately six months before that two year mark is up, you're SOL, you're in big trouble because you need money. And so you're not ready to do the B round yet. And so you might be able to call up a bank like Silicon Valley Bank, and do a convert, or approach a high net worth investor. And say, "Listen, I'm gonna do another round "in six months from now.

"Why don't you invest with me now, it'll be like a loan, I'll give you 8% interest per year, and then when I do that next round, your loan will convert into ownership in the next round at a 20% discount. So you'll get that 20% bump up there."

Warrants

So a startup can incentivise some investors by giving them warrants, which is basically the options to get shares later for free. It's kind of like stock options. And what happens is a lot of service providers, like legal firms you deal with, you can pay them with cash for their legal fees which are really high usually, and you can also give them warrants, or the option to get shares later on. And of course options,

And options are basically an opportunity for employees to not just get cash for salary, but to get stock as well, or the option to buy stocks at a certain very low price in the future.

MBA with me : Mitul Shahriyar ( Part 3 )

Shahriyar Al Mustakim Mitul — Sat, 21 Oct 2023 10:10:07 +0000

We've raised some seed money,used amazing presentation skills to raise money.Okay, you raised it from angel investorsor seed investors,those are just terms for peoplethat fund early stage companies by giving them a couple hundred grand to start a firm. Alright, so, your company is now a bit bigger, right?

You started generating revenue. And now you need a lot of money to get to the next level, and so, I don't want to use a bank, ever, okay? Because remember, early on, with banks, if you miss one payment, they will seize everything in your company, they will terminate your company, they don't care, they're ruthless, they're blood suckers.

Okay?we've raised some seed money, used amazing presentation skills to raise money. Okay, you raised it from angel investors or seed investors, those are just terms for people that fund early stage companies by giving them a couple hundred grand to start a firm.

Alright, so, your company is now a bit bigger, right?

Okay?

Assume that you are here now year 2-3

So, how to get it? It's not always about the business model rather the guy who asks for it.

Remember, The jockey's more important than the horse.

The business model is irrelevant, unless you have a great management team.

So, your chances to get investment depends:

If you had a company before which you build and sold. This shows your experience. They will ask why you sold it and how was the income when it was running.

Yes, it's tough. So, what you can do is:
Go to LinkedIn and search for Googlers or talented minds who are your Alumni and well as they are currently working at good places.
You can ask help from them. Surely, you would love to have them as the board of advisors.

May be the message might look like this:


John, hope all is well,
and I'm also from Canada, and I live in the Bay Area, or I also went to San Francisco State, I live in the Bay Area, or I also went to,I don't know, NYU and I live in the Bay Area. Or I also went to IIT and live in the Bay Area. Please let me know if you have time for a coffee in the next few weeks.

Thanks, Chris.

How VC earns?
Well venture capital or VC firms make money

in two ways,

one way is a charge of 2% annual fee on the money that you invest in them, right? And that just pays for salaries, rent, expenses.

And here's the kicker.

They make most of their money on what's called the carry, which is a 20% incentive that they get. So what does that mean? Well let's say you invest $100 in a venture capital firm. And you make 10 times your money,

so you make $1000. About 20% of that will go to the venture capital firm. They'll make $200 off you, and you'll make $800.

2 and 20, those are the terms.

And hedge fund actually works the same way as well. An annual 2% manage fee. And a 20% incentive.

So the seed stage is the first stage. When you kind of have a product, approved concept, sort of, developing it, and then,

the last stage is called the initial public offering, IPO. And that's when revenue growth starts to slow a bit, but still positive, and later on.

So, everything lying between Seed stage and IPO are Venture Capital (VC)

Alright so, the A round is when Sequoia (A company) gives us a lot of money for our company.

And a year and a half after our A round, or 2 years later, we're running out of money.

And so we're gonna wanna do a B round. Again, from Kleiner. And 2 years later, whatever, we're gonna need a little bit more money

before we go public from Meritech, a great venture capital firm,

and Silicon Valley Bank.

so, from birth to IPO,And so, from birth to IPO, is usually seven or eight years

So what returns do venture capital firms look for?

Well they typically look for what's called a five by five.And that means a 500% return within five years.

Why so big? Because most investments go belly up. In fact most companies that get started end up declaring bankruptcy within a couple of years.

Okay, what about valuation?

Well, in venture capital, you never look at valuation this year or next year, in fact, the best investments you'll make in your life in your life, whether they're private companies or public companies, ask yourself one question before analyzing that company.

Which is this.
In five years, in this company that I might invest in going to be more relevant or less relevant than it is today?

Let me say that again.
In five years, is this company going to be more relevant or less relevant than it is today? Okay, it teaches you to be a long term investor, like Warren Buffet, which works exceptionally well, instead of playing the month to month gyrations of the idiotic hedge fund market where I used to work.

There's a reason why I'm in venture capital now. And so, in five years, is this company going to be more relevant or less relevant

than it is today?

And so let's say we're looking at Amazon, or LinkedIn, two amazing companies. I think one day Amazon will have the largest market capital in the world, they're the biggest company in the world. But if you look at earnings this year and next year, it's over a hundred times earnings, and goodness, who would waste their money

investing in that company?

Well, a lot of people lost a lot of money shorting or betting against Amazon, because, they're just too short term focused, remember, you wanna be long term greedy, right? And so, longer term, Amazon will make a ton of money. And the same thing with LinkedIn.

Two big sales techniques:

that I've learned from dealing with some of the most successful CEOs in the world is they do this.

They stopped talking once they sense the sale is done, OK, once once they sense that their customer actually wants the product or service they're trying to sell. They actually shut up.

Why?

Because what happens is if you keep selling past the close, then people are going to sense desperation and think that there's something wrong here and that you might be over selling your product or service

so you want to stop speaking Once you sense that the sale has been made, OK.

And the second thing is.

Keep selling until You're convinced that they're not interested. OK, so if they're interested, stop talking. But if you're not sure if they're interested, you keep going, man, you've got to be a a pit bull on a pork chop, so to speak.

Venture capital firms focus primarily on having a superb management team unlike this dude presenting to venture capitalists and high net worth investors. Pay very close attention to what not to do in this video: https://youtu.be/48TR0vUPQCs?si=Hkq8LkUpl1qWmCyX

MBA with me : Mitul Shahriyar ( Part 2 )

Shahriyar Al Mustakim Mitul — Wed, 11 Oct 2023 15:06:15 +0000

Creating our presentation keeping these in mind:

Less is more : Less points with jokes to interact
Keep it simple
The medium is often more important than the message: How you present is often more important than what you present. For example. Check out Kennedy-Nixon First Presidential Debate where Kennedy had a better style and he won for that basically
You need to inspire people
You need to show passion. For example:
Best Motivational Speech by Larry Ellison
Bill Gates presenting, Steve jobs
Deliver an experience rather and example. Steve jobs was pro in it.
Practice a lot.
3 words work a lot. For example, Obama used to say 'Yes, we can'. Amazon uses 'And you're done',
Nike "Just do it" etc.
Marketing is theatre : You are the actor (CEO) and presenting (acting) before so many people.
Create a passion/mission statement.
Short video clip works
Showing product works
Inform, educate & entertain : Make it entertaining and let them know about your product.
For example. Starbucks founder said, "It's not about coffee. It's about passion and experience"
Present with passion : Right from the heart . Don't read script. Watch Matthew McConaughey's OSCAR winning moment
Us vs them creates loyaly:
Show bad guy and then introduce a hero.
Check 1984 Super Bowl APPLE MACINTOSH Ad by Ridley Scott

Here the enemy is IBM and the women is Apple. Haha!
Also, windows vs MAC user

Clarity is important.

Meryl here present very clearly . See here

Humor and self 'deprecation' (making fun of own) works well.
Example: Conan O'brien's speech
Use your hands to interact
Use dramatic pauses.
Be honest and sincere
Learn something for 10,000 hours to be an expert - Malcolm Gladwell
Talk for 4 min at max
Check best example by Barak Obama's 4 minute speech

Before that, no one knew him . He started relating his story with the audience.

Hire slowly and fire quickly

Focus on the active performance of your employee and fire if needed.