I thought it would be interesting to share how much TikTok paid me in 2021.

Onward!

Oh, you get paid by TikTok?

Yes.

They compensate thousands of creators. My Tik Tok account

I launched my account in March 2020 and generally post about money, finance, and side hustles.

TikTok creators are paid in several ways.

• Fund for TikTok creators

• Sponsorships (aka brand deals)

• Affiliate promotion

• My own creations

Only one, the TikTok Creator Fund, pays me.

The TikTok Creator Fund: What Is It?

TikTok's initiative pays creators.

YouTube's Shorts Fund, Snapchat Spotlight, and other platforms have similar programs.

Creator Fund doesn't pay everyone. Some prerequisites are:

• age requirement of at least 18 years

• In the past 30 days, there must have been 100,000 views.

• a minimum of 10,000 followers

If you qualify, you can apply using your TikTok account, and once accepted, your videos can earn money.

My earnings from the TikTok Creator Fund

Since 2020, I've made $273.65. My 2021 payment is $77.36.

Yikes!

I made between $4.91 to around $13 payout each time I got paid.

TikTok reportedly pays 3 to 5 cents per thousand views.

To live off the Creator Fund, you'd need billions of monthly views.

Top personal finance creator Sara Finance has millions (if not billions) of views and over 700,000 followers yet only received $3,000 from the TikTok Creator Fund.

Goals for 2022

TikTok pays me in different ways, as listed above.

My largest TikTok account isn't my only one.

In 2022, I'll revamp my channel.

It's been a tumultuous year on TikTok for my account, from getting shadow-banned to being banned from the Creator Fund to being accepted back (not at my wish).

What I've experienced isn't rare. I've read about other creators' experiences.

So, some quick goals for this account…

• 200,000 fans by the year 2023

• Consistent monthly income of $5,000

• two brand deals each month

For now, that's all.

If asked, run.

An entrepreneur asked me about her pitch deck. A Platform as a Service (PaaS).

She told me she hadn't done her 5-year forecasts but would soon.

I said, Don't bother. I added "time-wasting."

“I've been asked”, she said.

“Who asked?”

“a VC”

“5-year forecast?”

“Yes”

“Get another VC. If he asks, it's because he doesn't understand your solution or to waste your time.”

Some VCs are lagging. They're still using steam engines.

10-years ago, 5-year forecasts were requested.

Since then, we've adopted a 3-year plan.

But It's outdated.

Max one year.

What has happened?

Revolutionary technology. NO-CODE.

Revolution's consequences?

Product viability tests are shorter. Hugely. SaaS and PaaS.

Let me explain:

• Building a minimum viable product (MVP) that works only takes a few months.

• 1 to 2 months for practical testing.

• Your company plan can be validated or rejected in 4 months as a consequence.

After validation, you can ask for VC money. Even while a prototype can generate revenue, you may not require any.

Good VCs won't ask for a 3-year business plan in that instance.

One-year, though.

If you want, establish a three-year plan, but realize that the second year will be different.

You may have changed your business model by then.

A VC isn't interested in a three-year business plan because your solution may change.

Your ability to create revenue will be key.

• But also, to pivot.

• They will be interested in your value proposition.

• They will want to know what differentiates you from other competitors and why people will buy your product over another.

• What will interest them is your resilience, your ability to bounce back.

• Not to mention your mindset. The fact that you won’t get discouraged at the slightest setback.

• The grit you have when facing adversity, as challenges will surely mark your journey.

• The authenticity of your approach. They’ll want to know that you’re not just in it for the money, let alone to show off.

• The fact that you put your guts into it and that you are passionate about it. Because entrepreneurship is a leap of faith, a leap into the void.

• They’ll want to make sure you are prepared for it because it’s not going to be a walk in the park.

• They’ll want to know your background and why you got into it.

• They’ll also want to know your family history.

• And what you’re like in real life.

So a 5-year plan…. You can bet they won’t give a damn. Like their first pair of shoes.

Yes, salary details ought to be mentioned in job postings. Recruiters and candidates both agree, so why doesn't it happen?

The short answer is “Unfortunately, it’s not the Recruiter’s decision”. The longer answer is well… A LOT.

Starting in November 2022, NYC employers must include salary ranges in job postings. It should have started in May, but companies balked.

I'm thrilled about salary transparency. This decision will promote fair, inclusive, and equitable hiring practices, and I'm sure other states will follow suit. Good news!

Candidates, recruiters, and ED&I practitioners have advocated for pay transparency for years. Why the opposition?

Let's quickly review why companies have trouble sharing salary bands.

💰 Pay Parity

Many companies and leaders still oppose pay parity. Yes, even in 2022.

💰 Pay Equity

Many companies believe in pay parity and have reviewed their internal processes and systems to ensure equality.

However, Pay Equity affects who gets roles/promotions/salary raises/bonuses and when. Enter the pay gap!

💰Pay Transparency and its impact on Talent Retention

Sharing salary bands with external candidates (and the world) means current employees will have access to that information, which is one of the main reasons companies don't share salary data.

If a company has Pay Parity and Pay Equity issues, they probably have a Pay Transparency policy as well.

Sharing salary information with external candidates without ensuring current employees understand their own salary bands and how promotions/raises are decided could impact talent retention strategies.

This information should help clarify recent conversations.

Overview

Ethereum blockchain is a network of nodes that validate transactions. Any network node can be queried for blockchain data for free. To write data as a transition requires processing and writing to each network node's storage. Fee is paid in ether and is also called as gas.

We'll examine how user-initiated transactions flow across the network and into the blockchain.

Flow of transactions

• A user wishes to move some ether from one external account to another. He utilizes a cryptocurrency wallet for this (like Metamask), which is a browser extension.

• The user enters the desired transfer amount and the external account's address. He has the option to choose the transaction cost he is ready to pay.

• Wallet makes use of this data, signs it with the user's private key, and writes it to an Ethereum node. Services such as Infura offer APIs that enable writing data to nodes. One of these services is used by Metamask. An example transaction is shown below. Notice the “to” address and value fields.

var rawTxn = {
    nonce: web3.toHex(txnCount),
    gasPrice: web3.toHex(100000000000),
    gasLimit: web3.toHex(140000),
    to: '0x633296baebc20f33ac2e1c1b105d7cd1f6a0718b',
    value: web3.toHex(0),
    data: '0xcc9ab24952616d6100000000000000000000000000000000000000000000000000000000'
};

• The transaction is written to the target Ethereum node's local TRANSACTION POOL. It informed surrounding nodes of the new transaction, and those nodes reciprocated. Eventually, this transaction is received by and written to each node's local TRANSACTION pool.

• The miner who finds the following block first adds pending transactions (with a higher gas cost) from the nearby TRANSACTION POOL to the block.

• The transactions written to the new block are verified by other network nodes.

• A block is added to the main blockchain after there is consensus and it is determined to be genuine. The local blockchain is updated with the new node by additional nodes as well.

• Block mining begins again next.

The image above shows how transactions go via the network and what's needed to submit them to the main block chain.

References

ethereum.org/transactions How Ethereum transactions function, their data structure, and how to send them via app. ethereum.org

Google announced 6% layoffs recently (or 12,000 people). This aligns it with most tech companies. A publicly contrite CEO explained that they had overhired during the COVID-19 pandemic boom and had to address it, but they were sorry and took full responsibility. I thought this was "bullshit" too. Meta, Amazon, Microsoft, and others must feel similarly. I spent 10 years at Google, and these things don't reflect well on the company's leaders.

All publicly listed companies have a fiduciary duty to act in the best interests of their shareholders. Dodge vs. Ford Motor Company established this (1919). Henry Ford wanted to reduce shareholder payments to offer cheaper cars and better wages. Ford stated.

My ambition is to employ still more men, to spread the benefits of this industrial system to the greatest possible number, to help them build up their lives and their homes. To do this we are putting the greatest share of our profits back in the business.

The Dodge brothers, who owned 10% of Ford, opposed this and sued Ford for the payments to start their own company. They won, preventing Ford from raising prices or salaries. If you have a vocal group of shareholders with the resources to sue you, you must prove you are acting in their best interests. Companies prioritize shareholders. Giving activist investors a stick to threaten you almost enshrines short-term profit over long-term thinking.

This underpins Google's current issues. Institutional investors who can sue Google see it as a wasteful company they can exploit. That doesn't mean you have to maximize profits (thanks to those who pointed out my ignorance of US corporate law in the comments and on HN), but it allows pressure. I feel for those navigating this. This is about unrestrained capitalism.

When Google went public, Larry Page and Sergey Brin knew the risks and worked hard to keep control. In their Founders' Letter to investors, they tried to set expectations for the company's operations.

Our long-term focus as a private company has paid off. Public companies do the same. We believe outside pressures lead companies to sacrifice long-term opportunities to meet quarterly market expectations.

The company has transformed since that letter. The company has nearly 200,000 full-time employees and a trillion-dollar market cap. Large investors have bought company stock because it has been a good long-term bet. Why are they restless now?

Other big tech companies emerged and fought for top talent. This has caused rising compensation packages. Google has also grown rapidly (roughly 22,000 people hired to the end of 2022). At $300,000 median compensation, those 22,000 people added $6.6 billion in salary overheads in 2022. Exorbitant. If the company still makes $16 billion every quarter, maybe not. Investors wonder if this value has returned.

Investors are right. Google uses people wastefully. However, by bluntly reducing headcount, they're not addressing the root causes and hurting themselves. No studies show that downsizing this way boosts productivity. There is plenty of evidence that they'll lose out because people will be risk-averse and distrust their leadership.

The company's approach also stinks. Finding out that you no longer have a job because you can’t log in anymore (sometimes in cases where someone is on call for protecting your production systems) is no way to fire anyone. Being with a narcissistic sociopath is like being abused. First, you receive praise and fancy perks for making the cut. You're fired by text and ghosted. You're told to appreciate the generous severance package. This firing will devastate managers and teams. This type of firing will take years to recover self-esteem. Senior management contributed to this. They chose the expedient answer, possibly by convincing themselves they were managing risk and taking the Macbeth approach of “If it were done when ’tis done, then ’twere well It were done quickly”.

Recap. Google's leadership did a stupid thing—mass firing—in a stupid way. How do we get rid of enough people to make investors happier? and "have 6% less people." Empathetic leaders should not emulate Elon Musk. There is no humane way to fire 12,000 people, but there are better ways. Why is Google so wasteful?

Ambition answers this. There aren't enough VP positions for a group of highly motivated, ambitious, and (increasingly) ruthless people. I’ve loitered around the edges of this world and a large part of my value was to insulate my teams from ever having to experience it. It’s like Game of Thrones played out through email and calendar and over video call.

Your company must look a certain way to be promoted to director or higher. You need the right people at the right levels under you. Long-term, growing your people will naturally happen if you're working on important things. This takes time, and you're never more than 6–18 months from a reorg that could start you over. Ambitious people also tend to be impatient. So, what do you do?

Hiring and vanity projects. To shape your company, you hire at the right levels. You value vanity metrics like active users over product utility. Your promo candidates get through by subverting the promotion process. In your quest for growth, you avoid performance managing people out. You avoid confronting toxic peers because you need their support for promotion. Your cargo cult gets you there.

Its ease makes Google wasteful. Since they don't face market forces, the employees don't see it as a business. Why would you do when the ads business is so profitable? Complacency causes senior leaders to prioritize their own interests. Empires collapse. Personal ambition often trumped doing the right thing for users, the business, or employees. Leadership's ambition over business is the root cause. Vanity metrics, mass hiring, and vague promises have promoted people to VP. Google goes above and beyond to protect senior leaders.

The decision-makers and beneficiaries are not the layoffees. Stock price increase beneficiaries. The people who will post on LinkedIn how it is about misjudging the market and how they’re so sorry and take full responsibility. While accumulating wealth, the dark room dwellers decide who stays and who goes. The billionaire investors. Google should start by addressing its bloated senior management, but — as they say — turkeys don't vote for Christmas. It should examine its wastefulness and make tough choices to fix it. A 6% cut is a blunt tool that admits you're not running your business properly. why aren’t the people running the business the ones shortly to be entering the job market?

This won't fix Google's wastefulness. The executives may never regain trust after their approach. Suppressed creativity. Business won't improve. Google will have lost its founding vision and us all. Large investors know they can force Google's CEO to yield. The rich will get richer and rationalize leaving 12,000 people behind. Cycles repeat.

It doesn’t have to be this way. In 2013, Nintendo's CEO said he wouldn't fire anyone for shareholders. Switch debuted in 2017. Nintendo's stock has increased by nearly five times, or 19% a year (including the drop most of the stock market experienced last year). Google wasted 12,000 talented people. To please rich people.

AI images are like funhouse mirrors.

Google's AI Blog introduced the puppy-slug in the summer of 2015.

Puppy-slug isn't a single image or character. "Puppy-slug" refers to Google's DeepDream's unsettling psychedelia. This tool uses convolutional neural networks to train models to recognize dataset entities. If researchers feed the model millions of dog pictures, the network will learn to recognize a dog.

DeepDream used neural networks to analyze and classify image data as well as generate its own images. DeepDream's early examples were created by training a convolutional network on dog images and asking it to add "dog-ness" to other images. The models analyzed images to find dog-like pixels and modified surrounding pixels to highlight them.

Puppy-slugs and other DeepDream images are ugly. Even when they don't trigger my trypophobia, they give me vertigo when my mind tries to reconcile familiar features and forms in unnatural, physically impossible arrangements. I feel like I've been poisoned by a forbidden mushroom or a noxious toad. I'm a Lovecraft character going mad from extradimensional exposure. They're gross!

Is this really how AIs see the world? This is possibly an even more unsettling topic that DeepDream raises than the blatant abjection of the images.

When these photographs originally circulated online, many friends were startled and scandalized. People imagined a computer's imagination would be literal, accurate, and boring. We didn't expect vivid hallucinations and organic-looking formations.

DeepDream's images didn't really show the machines' imaginations, at least not in the way that scared some people. DeepDream displays data visualizations. DeepDream reveals the "black box" of convolutional network training.

Some of these images look scary because the models don't "know" anything, at least not in the way we do.

These images are the result of advanced algorithms and calculators that compare pixel values. They can spot and reproduce trends from training data, but can't interpret it. If so, they'd know dogs have two eyes and one face per head. If machines can think creatively, they're keeping it quiet.

You could be forgiven for thinking otherwise, given OpenAI's Dall-impressive E's results. From a technological perspective, it's incredible.

Arthur C. Clarke once said, "Any sufficiently advanced technology is indistinguishable from magic." Dall-magic E's requires a lot of math, computer science, processing power, and research. OpenAI did a great job, and we should applaud them.

Dall-E and similar tools match words and phrases to image data to train generative models. Matching text to images requires sorting and defining the images. Untold millions of low-wage data entry workers, content creators optimizing images for SEO, and anyone who has used a Captcha to access a website make these decisions. These people could live and die without receiving credit for their work, even though the project wouldn't exist without them.

This technique produces images that are less like paintings and more like mirrors that reflect our own beliefs and ideals back at us, albeit via a very complex prism. Due to the limitations and biases that these models portray, we must exercise caution when viewing these images.

The issue was succinctly articulated by artist Mimi Onuoha in her piece "On Algorithmic Violence":

As we continue to see the rise of algorithms being used for civic, social, and cultural decision-making, it becomes that much more important that we name the reality that we are seeing. Not because it is exceptional, but because it is ubiquitous. Not because it creates new inequities, but because it has the power to cloak and amplify existing ones. Not because it is on the horizon, but because it is already here.