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What Amazon Doesn’t Want You to Know About Its Automation Strategy

November 22, 2019 in Biohacking

Being at the forefront of automation, why is Amazon downplaying the impact of AI and robotics?

Breakthroughs in machine learning (ML) and robotics are drastically enabling a faster and cheaper means of delivery and manufacturing. We all want our packages instantly at lower costs and companies want higher margins. But what’s the overall impact on our society as we automate more and more tasks in factories and warehouses?

Among the world’s largest companies, Amazon, in particular, has faced heightened scrutiny. The e-commerce giant has been the major driving force behind the now widespread reality of warehouse automation and same-day delivery, pushing its peers and suppliers like DHL to test a range of robotic technology just to keep up.

Amazon was criticized for pressing workers to physical limits while continuously automating jobs, impacting 125,000 full-time hourly associates and an additional 120,000 seasonal workers across its logistics and warehouse centers in the United States. Against the backdrop of public scrutiny, we see Amazon delaying, rather than encouraging, more candid and transparent discussions of how we as a society transition.

During a recent press tour, Scott Anderson, director of Amazon Robotics Fulfillment said that fully automated workstations in warehouses are at least 10 years away. More specifically, he thinks that it would take at least 10 years to automate the processing of a single order picked by a worker inside a warehouse. Is this fact or a publicity ploy to distract the public from an urgently needed discussion of how we transition and get ready for this inevitable massive trend?

What Amazon Got Right

While we may still be years away from “fully” automating every step of complete orders in warehouses, certain stages of orders are already being automated, and there will be a cascade of automation during the next few years. In other words, the technology is already here to automate enough to be efficient and cost-effective.

In addition, while mobile robots like Kiva and Fetch are currently in use, robotic arms used for piece picking are only just beginning to deploy. Why? As mentioned in my previous article, most robotic arms are powerful but blind. They are programmed to perform the same tasks repetitively. Even small changes could pause the production line for recalibration. They can’t adapt to changes in the environment and are not nearly as dexterous as human arms.

Compared to robots, humans are still much more flexible and have a better visual perception as well as gripping capabilities (We still haven’t invented any gripper that is nearly as dexterous as human fingers).

Furthermore, humans don’t use low-level languages to describe seemingly intuitive tasks like grasping. While most of us can easily pick and place various objects without even thinking about it, robots need to learn to grasp from scratch as they lack crucial context including physics like friction and center of gravity. (That’s why we can’t simply apply current metrics for human to robotic grasping. I will explain more about this in my next post.)

The picking process can be really complex, ranging from zone picking, discrete picking, all the way to batch picking. It also involves several steps including receiving, sorting, palletizing, depalletizing, picking, checking and packing, labeling, and shipping. Many of these steps have been automated but we are still years away from fully automating this process. Amazon is right in highlighting the limitations of current AI and robotics technology compared to the superior cognitive and manipulation ability of humans. However, there are important trends that Amazon hopes you miss.

What Amazon Hopes You Missed

Total automation (level 5) isn’t needed. Simply automating part of the order assembly is sufficient to automate many jobs. Labor costs account for an average of 65% of most warehouse facilities’ operating budgets. Given that whopping number, it’s not hard to understand why budget-conscious warehouses are driven to automate wherever they can along the process. That’s also why the warehouse robotics market is forecasted to exceed USD 4 billion by 2022 with a CAGR of 11.8% according to MarketsandMarkets. The rapidly growing market demands have attracted not only robotics companies like ABB, Fanuc, and KUKA but also agile robot maker, Boston Dynamics, who recently acquired California based startup Kinema.
Robots are also getting smarter. A good example is piece picking, which has been the holy grail of robotics for many years. Now startups like Osaro and PlusOne are deploying machine learning-enabled robot arms that can recognize and manipulate a wide range of objects in warehouses. Even if the robots can only deal with 80% of the work and people still need to handle the rest of edge cases, this 80/20 strategy of automation to human intervention already ensures companies can reduce significant costs on labor and system integration.
Additionally, over time, the algorithm will improve and get closer to full autonomy as these level 4 autonomous robotic systems collect more data and learn from trial and error. The recent development in cloud robotics, meta-learning, and transfer-learning also accelerates the process of robots learning and adapting to changes in the environment.
As mentioned in my previous post, the market is growing rapidly. According to Tractica, worldwide sales of warehouse automation technology are expected to increase from $8.3 billion in 2018 to $30.8 billion in 2022. Industry giants including robotics makers (e.g. ABB, KUKA, Fanuc), material handling companies (e.g. Muratec, Dematic), retailers (e.g. Amazon, Ocado) are heavily investing in AI and robotics technology by building in house teams as well as working with startups that disrupt the industry with innovative solutions. 

High-density storage system startups like Attabotics and Commonsense Robotics emerged as retailers demand faster and more efficient delivery solutions.

The needs for AI-enabled robotics extend beyond warehouses. As a recent Mckinsey report suggests, an estimated $766 billion total wages in the US are spent for predictable physical work, which is more likely to be automated by robots.

The top three markets where the most predictable physical work resides are:

  1. Accommodation and food
  2. Manufacturing
  3. Transportation and warehousing (source: Mckinsey report)

    According to the US Bureau of Labor Statistics, the number of warehouse workers grew from 662k in 2009 to over 1.18m in 2019 with a CAGR of 5.96%. If the growth continues, there will be over 2.1m warehouse workers by the year 2029. Even if it really takes Amazon and other retailers 10 years to “fully automate every step of order”, that implies that more than two million jobs being automated in the next decade.

    Is 10 years a long time? Is it enough time for millions of workers and for the society to get ready for such a drastic shift? What we do know for sure is that millions of people will be impacted if we continue to deny the inevitable future of automation and waste the last chance we have to get prepared.

    Whether discontinuing its “Amazon picking challenge” or putting out articles downplaying the pace of automation, Amazon seems to be trying everything it can to avoid public scrutiny. There is no doubt that repetitive jobs will be replaced by automation, as they should be. Amazon knows this better than anyone else. Why would the company be planning to spend $700m over the next six years to retrain a third of its U.S workers, if they are not anticipating large job cuts in the near future? Is this too little too late?

    Can big companies including Amazon take a much more active role in making their plans for automation more transparent and beneficial to all parties?

    If we do it right, this new wave of automation can result in a much brighter future where companies will enjoy higher productivity and employees will be freed from repetitive and physically demanding jobs and have better working conditions. A recent Harvard study found that workers are more eager to embrace change and learn new skills than their employers give them credit for. People are not afraid of automation but they are definitely fearing uncertainty.

    Instead of wrongly assuming that workers don’t want to change and therefore soft-pedaling plans for automation, companies should work with their employees to transition to working with robots in jobs that are dangerous or repetitive and that workers would rather not do by themselves. This will help people get higher-skilled jobs with better wages in our future economy.

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Leveraging Multithreading To Read Large Files Faster In Go

November 22, 2019 in Biohacking

The other day I was interviewing at one of the companies, and I was asked the following question, how can you count occurrences of a word in a 50gb file with 4gb of RAM. The trick is to not load the whole file into memory and keep processing each word as we keep on moving the pointer of the file. With this, we can easily process the whole file with a minimal amount of memory resources.

Now the followup question was how can we speed up this process using multithreading? The solution is we keep multiple pointers at different parts of the file and each thread reads chunks of the file concurrently.

Finally, the result can be combined.

This simply shows how the whole file will be divided. And the various pointers of the file. Let’s say the file is 1GB huge. Each of 5 threads will process 200MB. The consecutive pointer will start reading from the byte of the last read byte of the previous pointer.


When it comes to multithreading the easier option which comes to mind is go-routines. I will walk you through a program that reads a large text file and creates a dictionary of words.

This program demonstrates reading a 1GB file using 5 go-routines with each thread reading 200MB each.

const mb = 1024 * 1024
const gb = 1024 * mb

func main() {
	// A waitgroup to wait for all go-routines to finish.
	wg := sync.WaitGroup{}

	// This channel is used to send every read word in various go-routines.
	channel := make(chan (string))

	// A dictionary which stores the count of unique words.
	dict := make(map[string]int64)

	// Done is a channel to signal the main thread that all the words have been
	// entered in the dictionary.
	done := make(chan (bool), 1)

	// Read all incoming words from the channel and add them to the dictionary.
	go func() {
		for s := range channel {

		// Signal the main thread that all the words have entered the dictionary.
		done <- true

	// Current signifies the counter for bytes of the file.
	var current int64

	// Limit signifies the chunk size of file to be processed by every thread.
	var limit int64 = 500 * mb

	for i := 0; i < 2; i++ {

		go func() {
			read(current, limit, "gameofthrones.txt", channel)
			fmt.Printf("%d thread has been completed n", i)

		// Increment the current by 1+(last byte read by previous thread).
		current += limit + 1

	// Wait for all go routines to complete.

	// Wait for dictionary to process all the words.

func read(offset int64, limit int64, fileName string, channel chan (string)) {
	file, err := os.Open(fileName)
	defer file.Close()

	if err != nil {

	// Move the pointer of the file to the start of designated chunk.
	file.Seek(offset, 0)
	reader := bufio.NewReader(file)

	// This block of code ensures that the start of chunk is a new word. If
	// a character is encountered at the given position it moves a few bytes till
	// the end of the word.
	if offset != 0 {
		_, err = reader.ReadBytes(' ')
		if err == io.EOF {

		if err != nil {

	var cummulativeSize int64
	for {
		// Break if read size has exceed the chunk size.
		if cummulativeSize > limit {

		b, err := reader.ReadBytes(' ')

		// Break if end of file is encountered.
		if err == io.EOF {

		if err != nil {

		cummulativeSize += int64(len(b))
		s := strings.TrimSpace(string(b))
		if s != "" {
			// Send the read word in the channel to enter into dictionary.
			channel <- s

Over here we also have to handle an edge case. What if the start of the chunk is not the start of a new word. Similarly what if the end of a chunk is not the end of the chunk.

We handle this by extending the end of the chunk till the end of the word and by moving the start of the consecutive chunk to the start of the next word.

We are using channels to unify all the words read by various threads into a single dictionary. A sync. Waitgroup can be used for synchronization of threads and ensure that all the threads have completed reading the file


It was observed that the performance was doubled and the time required to process the 1GB file was halved concurrently as compared to doing it in a serial manner.

The reason that we did not get 5x performance i.e number of threads is that, although the goroutines are lightweight threads, the process of reading a file requires the resource of one whole os level CPU core. It has no sleep time. Hence on a dual-core system it effectively only doubles the performance of file processing.

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How C Program Converts Into Assembly

November 22, 2019 in Biohacking

/!: Originally published @

A bit about function stack frames

  • During function code execution, a new stack frame is created in stack memory to allow access to function parameters and local variables.
  • The direction of stack frame growth totally depends on compiler ABI which is out of our scope for this article.
  • The complete information on stack frame size, memory allocation, returning from stack frame is decided at compile time.
  • Before diving into assembly code you should be aware of two things :
  1. CPU registers of x86 machine.
  2. x86 assembly instructions: As this is a very vast topic & updating quite frequently, we will only see the instructions needed for our examples.

x86 CPU Registers

General Purpose Registers

Pointer Register

Segment Register

Index Registers

Apart from all these, there are many other registers as well which even I don’t know about. But above-mentioned registers are sufficient to understand the subsequent topics.

How C program converts into assembly?

We will consider the following example with its disassembly inlined to understand its different aspect of its working at machine level :

We will focus on a stack frame of the function


. But before analysing stack frame of it, we will see how the calling of function happens

Function calling

Function calling is done by call instruction(see Line 15) which is subroutine instruction equivalent to:

push rip + 1 ; return address is address of next instructions
jmp func


store the


(not that +1 is just for simplicity, technically this will be substituted by the size of instruction) in the stack which is return address once call to



Function stack frame

A function stack frame is divided into three parts
1. Prologue/Entry: As you can see instructions(line 2 to 4) generated against start bracket


is prologue which is setting up the stack frame for


, Line 2 is pushing the previous frame pointer into the stack & Line 3 is updating the current frame pointer with stack end which is going to be a new frame start.


is basically equivalent to :

sub esp, 4   ; decrements ESP by 4 which is kind of space allocation
mov [esp], X ; put new stack item value X in

Parameter passing

Argument of 


 is stored in 


register on Line 14 before calling 


instruction. If there is more argument then it will be stored in a subsequent register or stack & address will be used.

Line 4 in 


 is reserving space by pulling frame pointer(pointed by 


 register) down by 4 bytes for the parameter 


as it is of type 


. Then 


instruction will initialize it with value store in


. This is how parameters are passed & stored in the current stack frame.

          ---|-------------------------|--- main()
             |                         |          
             |                         |          
             |                         |          
             |    main frame pointer   |          
rbp & rsp ---|-------------------------|--- func()
in func()    |           arg           |          
             |            a            |          
             |-------------------------|    stack 
             |            +            |      |   
             |            +            |      |   
             |            +            |      |   
          ---|-------------------------|---  |/  
             |                         |          
             |                         |          

Allocating space for local variables

2. User code: Line 5 is reserving space for a local variable 


, again by pulling frame pointer further down by 4 bytes. 


 instruction will initialize that memory with a value 



Accessing global & local static variables

  • As you can see above, 

    is addressed directly with its absolute addressing because its address is fixed which lies in the data segment.

  • This is not the case all the time. Here we have compiled our code for  x86 mode, that’s why it is accessing it with an absolute address.
  • In the case of x64 mode, the address is resolved using 

     register which meant that the assembler and linker should cooperate to compute the offset of 

    from the ultimate location of the current instruction which is pointed by 



  • The same statement stands true for the local static variables also.
3. Epilogue/Exit: After the user code execution, the previous frame pointer is retrieved from the stack by 


 instruction which we have stored in Line 2. 


is equivalent to:

mov X, [esp] ; put top stack item value into X 
add esp, 4   ; increments ESP by 4 which is kind of deallocation

Return from function


instruction jumps back to the next instruction from where


called by retrieving the jump address from stack stored by 




 is subroutine instruction which is equivalent to:

If any return value specified then it will be stored in 


register which you can see in Line 16.

Intuitive FAQs 

Q. How do you determine the stack growth direction ?

A. Simple…! by comparing the address of two different function’s local variables.

int *main_ptr = NULL;
int *func_ptr = NULL;
void func() { int a; func_ptr = &a; }
int main()
    int a; main_ptr = &a;
    (main_ptr > func_ptr) ? printf("DOWNn") : printf("UPn");
    return 0;

Q. How do you corrupt stack deliberately ?

A. Corrupt the SFR values stored in the stack frame.

void func()
    int a;
    memset(&a, 0, 100); // Corrupt SFR values stored in stack frame
int main()
    return 0;

Q. How you can increase stack frame size ?



 is the answer. Google about it or see this. Although this is not recommended.

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Why [Its Important] to Choose Free Play Games vs Real Online Gambling Sites

November 21, 2019 in Biohacking

I’ve been an iGaming affiliate for a long time now (19 years) and a casino gambler for even longer (25 years). I’ve played blackjack more than 1/2 of my life and know far too much about the game for my own good.

Most importantly, over the year’s I learned first hand how difficult it is to make money in a casino on a regular basis. It is possible for sure, but as soon as you start making money consistently the casinos will always find a way to stop you one way or the other. So you have to move around a lot to different casinos that don’t see you coming. This gets costly too!

Sometimes a casino will even pull a few dirty tricks if you’re an advantage gambler hanging around long enough to afford them the opportunity to stoop so low.

A wise gambler does not stay that long, however.

Unfortunately for myself, I’m an adrenaline gambler and I play for the rush. As a result, I and end up play extremely long sessions. 104 hours of playing blackjack with no sleep was my longest run ever. A bit extreme I’d say. What I’ve learned is this.

Casinos are in the gambling business to make money and don’t like it when “advantage players” win at blackjack.

I believe that legitimate online casinos are by their very nature more fair than traditional real world casinos are. The legit internet casinos are actually more fair in my personal opinion.

I say this because from my thousands of hours spent inside a real life casino gambling life’s precious time away, I observed too many consistent anomalies that can only be explained as the single consistent variable being most casino games are probably rigged or can be adjusted on demand in some way.

I don’t have cold hard facts to prove that casinos rig games so I’m not making claims and can only share my opinions, perspectives and observations. I can tell you about one rather interesting fact I’ve learned about video slots over time.

The Problem With Slot Machines

Inside of real world casinos, the slot machines are connected to a central computing command center where the casino has complete control over the game and it’s outcomes.

If that does not sound like a dodgy doorway to rig a slot machine then I’m not sure what does. I have read both official patent documentation online as well as slot machine manufacturer documents so I know this part is certain. Casinos do have control over the slots so they’re not always as “random” as we’d like to believe they are.

Obstacles in Blackjack

In blackjack, things are done a bit differently since the dealer must deal the cards from the deck or shoe. Because of this, they have other ways to rig blackjack games. Here 3 good reasons to play free blackjack apps instead.
  1. In blackjack, casinos like to order the cards in such a way that basic blackjack strategy becomes less effective for the player.
  2. If that doesn’t get you, many casinos have fake players that will join the table at just the right moment to crush your bankroll. They have total hidden control of the outcomes in my opinion.
  3. If you’re a high roller and you get on a good table game with a no mid-shoe entry rule and you get past all of those other lines of defense, the casino can still bring in a card mechanic.

You stand no chance at all when they bring in the big guns (aka the mechanic). Trust me on that, its lights out at that point.

So after a lifetime of playing blackjack I’ve lost my interest in gambling high stakes which I used to have a passion for. Now I know the game far to well and I get a rush out of defying the odds of the mathematics behind basic strategy. Consequently, that puts a card counter target on my back rather quickly if they don’t already know me (the casinos know me already in most cases).

The Sports Betting Gold Rush

If you are a sports bettor then things are a bit different. For many people in a growing number of states across the United States of America, U.S. citizens are able to bet on sports legally on the internet. The rush into sports betting in the United States has been fast and furious. Much like the online sports betting markets in UK and Europe have been, the US market has been growing steadily over recent years.

In Europe companies are raking in billions of Euros from regulated online sports betting. The future looks equally promising for the USA sports betting market on the internet. Mobile sports betting growth is massive and more of the major online gambling companies are entering the market which is good for free market competition and in turn good for gamblers too.

Free GambleRock Games

Take a look at the gambling forums on GambleRock, sign up and say hello to other players. Its a social networking site with free gambling games, live chat features and lots of professional gambling content to read and learn from on the internet.
There are so many great free casino apps to use these days that I don’t see much value in betting with real money when I can play the same games online absolutely free. My favorite free online slots game I’m playing often is gRock’s all new Slots 777 game. Give it a spin with 1,000 free coins just for kicks!
Should you decide you going to gamble on internet casinos then please choose carefully where you play. I’ve reviewed some of the top ranked gambling sites and visitors/readers can also rate the online casinos & online sportsbooks listed on

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Buying Upwork Reviews: Is Your Freelancer Really a 5-Star Freelancer?

November 21, 2019 in Biohacking

Freelancing is all about – the trust. And, trust is all about – the reviews.

Now, are all the reviews out there worthy of your trust? How many times have you hired a freelancer or decided to work for a client or chosen a freelance platform, based on reviews?

I don’t know about you, but I don’t even bother reading five-star reviews. Why? Well, because they’re all the same, more or less. Instead, I dive straight into the negative reviews. For a change, one-star reviews in particular, are emotional, lengthy, and above all, rich in useful details.

Have you ever doubted reviews, even for a moment? I didn’t. Until now.

Upwork Review Farms

I had to borrow this brilliant term from Twitter.

I said to myself, kudos to a guy who came up with this line first. Can it be true? It took only a few clicks and then I stumbled upon this link, where you can buy Upwork reviews.

C’mon guys, you can’t be serious about it. No freelancer in his right mind would’ve invested money in buying Upwork reviews. Right?

I thought that this was a ridiculous thing to consider even for a minute. Then, the “Description” and “Additional Information” caught my attention. As a writer, I can tell you, this is one hell of a good copy. Nicely written and structured. Straight to the point. These guys have worked out all possible scenarios. They have covered all reasonable questions.

You really have to give them credit for all the effort.

They didn’t try to avoid the most unpleasant and logical questions about their “business.”

As I said, all angles are covered and all doubts confronted with the reasonable explanations.

Obviously, there’s honor among thieves and fair-play among the sellers of Upwork reviews.

You can even buy negative Upwork reviews. Now, why in the world a freelancer would want to buy negative reviews? Well, when you think about it for a moment, it makes the perfect sense. A negative review here and there certainly makes your Upwork account look more “authentic.” You can’t have all five-star reviews. It’s just too good to be true.

OK. So, this is a clearly indecent proposal all freelancers with integrity should avoid. Upwork is a serious organization. They wouldn’t allow their reviews to be compromised under any circumstances. Or, would they?

Hide and Seek Your Upwork Reviews, You Freelance Geek!

Again, Twitter turned out to be a great source for investigative Upwork journalism. An Invisible Girl on Twitter made one problem with Upwork reviews very visible.

What is she talking about? You can’t hide your freelance reviews. That’s impossible. Something like this conflicts the basic principles of the entire freelance industry. This just can’t be true. So, I decided to prove her all wrong.

What do you know, this “option” has been hiding in plain sight on the official Upwork’s website.

So, if you are a Top Rated freelancer on Upwork, you can get away with a “murder” of your negative reviews. Seriously?

Oh boy, it gets even worse. Feedback Removal is something that’s openly discussed in Upwork Community.

Pay attention guys! This Upwork user is a veteran. He has been working on Upwork since 2011. Meaning, he probably started at the same time as I did, back on oDesk or Elance, or even both.

He was just expressing his reasonable concern and asking for clarification.

But hey, oh no, as if they were given a single command, the Upwork Community Gurus descended upon this truth-seeker.

These “Gurus” defended the “constitutional right” of Upwork freelancers to remove reviews they don’t like.

My personal favorite is a Guru, who is making a point that this Feedback Removal option on Upwork is limited. Hey, certain “criteria” had to be fulfilled, so you can remove negative reviews from your profile.

Our truth-seeking hero was helpless against the barrage fire of Upwork Community “Kerberos.” It’s understandable that he eventually had to give up(work).

Seek-and-you-shall-find the answers to your questions on Upwork doesn’t apply to reviews. Again, my personal favorite – the razor-blade-Upwork-community-guru – Petra. When I was still a happy Upworker, her answers and comments always stood out. She made sure her reputation of merciless defenders of Upwork universe is well justified.

OK. Let’s draw a line here. Enough is enough. You can buy five-star and/or kill your one-star Upwork reviews, but this doesn’t mean that the whole system is corrupted. At least, Upwork reviews are still trustworthy. Are they?

If You Can’t Trust Trustpilot, Then Who Can You Trust?

It’s not a secret or surprise that Upwork is rated as “poor” and “bad” on Trustpilot. This low rating score makes sense to me. It reflects the Upwork reality, which is far away from a projected idealistic one.

I thought that Upwork’s reputation was damaged beyond repair. I also wondered how was it possible for Upwork to “tolerate” this unfavorable review situation?! Yup, you should be careful about what you wish for. Before I knew it, the Upwork “review machinery” demonstrated its full strength.

In a matter of weeks, Upwork’s Trustpilot score “improved” from 1.4/5.0 to the more “acceptable” 3.7/5.0. How is that even possible?

As I’m writing this article, Upwork’s trust score is getting better and better. The new five-star reviews have been posted on an hourly basis. So, what’s my problem with it?

Well, we clearly had a period when Upwork wasn’t interested about its poor rating. Then, all of a sudden the review-sleeping-beauties on Upwork have awoken and eager to get down to “business.” I paid the close attention. There was a wave after wave of five-star reviewers. You can check out the dates yourself. You can also see for yourself that these “happy” and “spontaneous” Upwork reviewers just wanted to do their “patriotic reviewing duty” as quickly as possible with not too many words left behind.

Here and there, you can still find one-star Upwork reviews on Trustpilot. They stand out sharply not because of their color and number of stars, but because of their content. Again, judge yourself.

From the “technical” point of view, Upwork isn’t doing anything wrong with its reviews on Trustpilot. Upwork reviewers are just being more active than usual. It’s a happy “coincidence” that almost all of them were five-star oriented in the last couple of weeks.

Upwork Reviews and Plastic Screws

Can you build a bridge of trust with the plastic screws?

Yeah, it’s a cheesy question, but it doesn’t mean I’m missing my point. I was looking for a word to rhyme with reviews. Is this the best I could do?

Actually, I asked Google, can you make a plastic bridge? Yes, you can, but I still prefer the good old wood, metal, or concrete in this case.

There’s a phenomenal movie quote from “Kingdom of Heaven:”

It (Jerusalem) is a kingdom of conscience, or nothing.

If you don’t mind, I would like to adapt this quote:

Freelancing is a kingdom of trust, or nothing.

So, nothing, Upwork.

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Tokenized Real Estate: A $17 Trillion Opportunity

November 21, 2019 in Biohacking

The following article is part of our Masters of Blockchain story series. Each piece in the series breaks down a chapter from the popular Masters of Blockchain, written by Andrew Romans. 

In Masters of Blockchain, Romans delivers everything you need to succeed in the blockchain industry. He describes the advantages of blockchain technology, token sale trends, strategies in raising money via ICOs, STOs, and other token offerings, the current regulatory landscape, and numerous other need-to-know topics. In his research, Romans spoke with over 200 of blockchain’s most influential people, recording what it takes to become a true master of blockchain.

Andrew Romans will be speaking live at ELEV8CON this December.

“In 2009 Starwood made a commitment to their shareholders in response to the liquidity crisis in the States that they would become asset light, sell the assets sitting on their balance sheet and concentrate on being a management company. I originally bought the 5-star St. Regis Aspen Colorado Hotel from them for $ 70 million in September 2010, invested another $ 50m into the renovation program and gave Starwood a 50-year management contract subject to performance. I did this using my Bangkok-based OptAsia Capital Co. Ltd in a GP-LP structure. Having done a number of other successful real estate deals in Hollywood and we had a lot of people asking us how to piggy back onto our deals. We then came up with the idea of creating single asset Real Estate Investment Trusts (REITs). Unfortunately, unless you are among the very small percentage of super wealthy families that can buy a $ 300m or $ 70m property you simply do not have access to this assets class. The only way to get any exposure would be to buy into a diversified REIT. What happens there is that you end up investing into a strategy rather than a specific asset. 

We embarked on the first single property hospitality REIT registered with the SEC in January of 2018. We went to IPO, but realized half way through the process that this will not be a scalable business because the cost of a listing on the NYSE is just so prohibitive that it just does not make sense for a single asset. We then observed what was happening with digital assets and ICOs and thought to issue a token with smart contracts that was backed up by a real asset and not simply an idea on a white paper. Our thinking was to connect an investor with a product. We convinced a lawyer to go for it. That was the easy part. Our mortgage lender JP Morgan was much more difficult to convince. To see their name in the same sentence with the word “crypto” was a challenge as they did not want to be guilty by association with any of the scams that were becoming all too common in the ICO universe. The same was true for Marriot. In the end it took us about six months, but eventually they did come around thanks the professional pre-existing relationships we have with these third parties. We were able to complete an $ 18m private placement in October 2018. This is one of the first trophy asset tokenizations where effectively there was an offering document, there was a placement and there is a platform with tokens being issued on the ERC20 platform that will commence trading in October of 2019.”The Wave of Tokenization Is Coming

And the real estate industry stands to benefit more so than most others. Although lucrative, real estate investing has historically been plagued with poor liquidity and start-up costs that prevent the majority of the world from getting involved. On the low end, purchasing a piece of commercial property costs a couple hundred thousand dollars, requiring either a) deep pockets or b) some type of investment fund. 

Real estate tokenization flips that model on its head. Tokenized real estate assets are effectively blockchain-based digital tokens that represent fractional ownership of a property. Creating these tokens reduces costs, improves market efficiency (i.e., liquidity), and lowers the barrier of entry to invest.

Several blockchain platforms have now infiltrated the real estate market, offering cryptocurrency versions of properties around the world. Today, you can purchase tokens that grant you ownership of condominiums, resorts, beachfront properties, and much more.

But it wasn’t until recently that blockchain real estate contained the numerous options that it does today. As late as mid-2018, tokenized real estate securities didn’t even exist.

Meet Stephane De Baets, Tokenized Real Estate Pioneer

Many credit Stephane De Baets, President of Elevated Returns, as launching the first real estate security token offering (STO). Spending his early life in Europe and Thailand, he currently lives in New York, where he specializes in financial structuring, M&A, and most importantly, asset management.

Even though De Baets currently owns several properties, the journey to his impactful real estate STO began with the purchase of a single hotel. In September 2010, De Baets bought the St. Regis Aspen Colorado Hotel from Starwood for $70 million. In an attempt to open up the property investment to the public, De Baets and his team created a single asset Real Estate Investment Trust, or REIT for short. 

But All Didn’t Go as Planned

Their original plan was to sell public shares of the St. Regis REIT through an initial public offering (IPO). However, they quickly ran into issues:

“We went to IPO, but realized halfway through the process that this will not be a scalable business because the cost of a listing on the NYSE is just so prohibitive that it just does not make sense for a single asset.”

So, What Could They Do?

In 2018, as they were scrapping their IPO plans, De Baets and his team took notice of a novel trend taking hold – initial coin offerings (ICOs). Although an interesting concept, they viewed many of the ICOs as nothing but “an idea on a white paper,” offering no real backing. Moving against the grain, they instead decided to leverage this new asset class with something that contained real, inherent value – the St. Regis Hotel.

“[We] thought to issue a token with smart contracts that was backed up by a real asset…Our thinking was to connect an investor with a product.”

A secure token offering (STO) was the obvious route for them to do so. As an SEC-approved asset, it allowed them to give the public a regulated security offering at a fraction of the cost of their dismantled IPO. Through the STO, they were able to eliminate the mountain of intermediaries that an IPO typically requires. De Baets explains,

“…whether it’s your accounting firm, your lawyers, the printers, the Edgar system – these are the people taking a huge amount of money out of the transaction, and it’s just so inefficient.”

An STO utilizes blockchain technology to directly connect investors with the assets in which they wish to invest.

It’s Not All Sunshine and Rainbows, Though

STOs do have some drawbacks. Because they’re SEC-regulated, they contain a strict set of rules that you must follow if you plan to launch one. For example, the SEC required De Baets to enforce a one-year lockup on the St. Regis REIT in which investors couldn’t trade their tokens. Because this rule creates more risk, it lead to a decrease in investor interest.

Additionally, the user experience of STO purchases has not yet reached the level that many consumers expect. While De Baets saw significant interest through an Indiegogo campaign, much of it faltered off when creating an account to purchase the token.

But, De Baets Is Still Confident In a Tokenized Future

He and his partners have plans to tokenize an additional $3 billion worth of real estate assets worldwide. He envisions a future in which your real estate tokens not only grant you part ownership of a property, but can also be spent on rental payments, for instance, from the same developer.

Blockchain companies aren’t limiting themselves to property tokenization, either. Large firms, such as Deloitte and PWC, are exploring blockchain solutions regarding property searches, due diligence, leasing, title management, and several other topics.

We’re still early in the timeline of blockchain real estate. And there will likely be many more applications far different than the uses that anyone is thinking of now. Perhaps, De Baets describes our current situation best:

“…we are at the equivalent of dial-up internet days, and one day people will laugh that anyone was arguing about this back in 2019.”

We couldn’t agree more.

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Long “Unbiased” VPN Reviews That Give You The Short End of the Stick [Deep Dive]

November 21, 2019 in Biohacking

There’s a massive problem in the privacy world. Websites, social media accounts, and other platforms are constantly popping up out of nowhere, telling you to buy The Greatest Service Ever in order to solve all your privacy woes, whatever that may be. These websites often employ marketing teams to make sure their “reviews” are what you see first when you begin your research. Some of them are even operated by VPN providers themselves, operating under anonymous business entities to hide their bias, or doing it right out in the open, hoping you’ll mistake their advertising-filled press releases and blogs as insider knowledge of the VPN space.

When a seemingly “unbiased review” on a site is merely a paid advertisement in disguise, that website is breaking their reader’s trust. From a consumer’s point of view, affiliate marketing and other paid promotional techniques like this make it near impossible to know when a review is genuine or not.

This isn’t going to be a lengthy blog post on advertising being bad, far from it. In fact, many of the VPN providers we recommend at PrivacyTools engage in responsible advertising across various platforms. The key is transparency: Their advertisements should look like advertisements, and nothing else.

The Bad

I’m really looking to take the time here and identify “the bad” sites and resources that use these techniques to profit off a community just looking for reliable answers. Lots of sites like these will claim they’re acting in your best interest, but they’re just here to make money.

One common thing I’ll see on these sites is a ranked list of providers that are ostensibly the best ones to choose from. These sites have supposedly done all the work for you, so you can just click and go, assured you’re making the right choices.

So here’s my issue with ranking VPN providers: Let’s face it, VPN providers are all offering the same service, and they will either protect your information or they won’t. Ranking providers like this only serves as an easy way to guide users to a certain choice (in this case, the choice that will make the reviewers the most money).

Let’s look at one of these “review” sites for example, which will go unnamed for the purposes of this article. On their homepage they prominently list 10 providers as the “best” VPN services, in this order:

  1. NordVPN
  2. Surfshark
  3. ExpressVPN
  4. PerfectPrivacy
  5. IPVanish
  6. Mullvad
  7. CyberGhost
  8. Trust.Zone
  9. ibVPN
  10. Private Internet Access

To their (dubiously earned) credit, this review site also helpfully included an advertising disclosure in their footer. On this fairly well hidden away page, they note that they participate in affiliate programs from 8 providers, as follows:

  • NordVPN
  • SurfShark
  • ExpressVPN
  • Perfect-Privacy
  • IPVanish
  • CyberGhost
  • Trust.Zone
  • Private Internet Access

Hmm. Look familiar? Of the 73 providers this site had reviewed at the time of writing this article, all eight of the VPN providers paying this review site happened to make their top 10 recommendations. In fact, you’d have to scroll down to #6 before you found a provider that wouldn’t pay them, practically buried.

Furthermore, their list includes NordVPN, a company notable for not disclosing security breaches in a timely fashion, and ExpressVPN, a provider notable for using weak 1024-bit encryption keys to protect their users. By any objective standard, these providers do not deserve to be included in a top 10 recommendations list for securing anybody’s information. This review site in particular claims to have set criteria for their recommendations, but this just demonstrates that any criteria can be adjusted to fit any goal you may have.

If these sites truly wanted to be helpful, they would consolidate all the relevant information and present it to their users without making the choice for them. A provider is going to be better or worse for every user depending on their particular situation, and encouraging making an informed choice between options presented equally is far more beneficial to putting one over the other in a largely arbitrary fashion.

But that isn’t to say they should just throw all the providers in a big table and call it a day. Almost worse than the ranking scheme above is when sites provide out of context lists of providers, often just with pricing and a link. Sometimes they will link you to a full review (more on that in a bit), but for the most part these sites just expect you to follow their recommendations blindly.

These read like advertisements, because they usually are. Once again we see the usual suspects — NordVPN, ExpressVPN… — paraded as the gold standard in the VPN space, not out of any inherent value, but based on the value of their affiliate programs. To further this point, let’s take a look at how much each of the five providers above will pay you for a referral (on a one month plan).

  1. ExpressVPN: $13 for first month
  2. NordVPN: $11.95 for first month
  3. VPNArea: $4.95 for first month
  4. $2.90 for first month

Unfortunately, Perfect Privacy would not share their commission rates publicly, but if anyone has any information on that I’d be happy to receive it. What I will say is that based on the information above, I would not be surprised if it fell right between ExpressVPN and NordVPN’s rates. Their one month plan costs $12.99, so assuming a 100% match on the first month (the standard from NordVPN and ExpressVPN) that would add up quite nicely.

Once again, we see a lineup of providers ordered in a way that conveniently pays the most to the website owner. And therein lies the issue with affiliate programs. Once you begin receiving financial compensation on a per-signup basis, you are now motivated to push the most users to the sites that pay more on a monthly basis, rather than the sites that will actually help the user.

Occasionally, these recommendations are coupled with a “review” that is supposedly independent and unbiased, but in reality are simply more marketing tools to persuade you towards their opinions. In most cases, these reviewers will simply copy the VPN provider’s own press releases and even media, presenting their advertising as fact to their readers. These reviews are always hidden away as well, with main navigation links directing users towards the more affiliate-link-laden lists and tables that they’d much rather you browse. The true value of these review articles is the Search Engine Optimization (SEO) advantage they bring in the rankings on Google, and not much more. More traffic = More clicks, at the expense of good, independent content and integrity.

The Good

This isn’t to say all tables or lists are bad, it’s how they’re presented rather that makes or breaks a site. for example sets what is perhaps the gold standard of VPN comparisons:

Here’s the difference. They include virtually every provider — the good and the bad — and present them at equal value to sort through. Instead of providing their readers with answers, they provide them with information that can be used to deduce their own recommendations, based on their values as an individual.

But some users just want the answers, and that’s fine too. I think there is still definitely a way to provide recommendations without introducing financials or bias into the equation. At PrivacyTools, we’ve developed a set list of criteria, and we make that abundantly clear when you read our list of recommended VPN providers.

We also refrain from using affiliate links. As we’ve discussed, they are fundamentally flawed ways to market a service, and using them would break the trust our community has in our recommendations.

We do have a newly-introduced sponsorship program, but all of our finances are handled in an incredibly transparent fashion. As a non-profit organization, the funding we receive cannot be used for private profit, and our community can see both where we receive money from and how it is being spent thanks to Open Collective. Additionally, the recommendations on are handled by an entirely separate team of editors and contributors than the administrative team such as myself that handles the sponsorships and finances. The editors have sole control over our recommendations and operate entirely independently and on a volunteer-basis to ensure the choices we make are for the benefit of the privacy community over one individual.

Ultimately, as a matter of policy our sponsors have no say over our recommendations, or whether they are recommended or a competitor is removed. We have given our community vast access to our website and internal workings to keep us in check and ensure we’re staying true to our word. This separation of management and editors is a strategy that has served the media industry well for decades, and makes all of our team and organization a more credible and trustworthy source of information.

In Summary

We have a lot of points we want to get across. The current landscape of privacy reviewers and “experts” weighing in on topics regarding the very companies that pay for their reviews is morally reprehensible, and just another way for big tech companies to collect all of our data more easily.

Review sites should make it abundantly clear when their reviews are paid for by the VPN companies in any fashion, whether that be via affiliate programs or good old-fashioned sponsorships. This can’t be via a hidden-away disclosure in the footer or not published at all, but clear and close in proximity to the claims published on their site. Customers are not expecting or seeking out these disclosures when they visit review sites, and can’t be expected to immediately discern whether you’re speaking from a place of unbiased fact, or from a place with the greatest financial incentive. Better yet, they should reconsider their entire business model. We built PrivacyTools from the ground up in 2015 based solely on a community donation model that still keeps us sustained. It’s the more difficult way to build a site to be sure, actually working to gain the trust of a huge community, but the difference in quality and integrity is remarkable.

VPN providers should consider spending less money on paid reviews, and more money on securing and validating their infrastructure. Regular security audits are one fantastic way for companies to demonstrate their dedication to keeping their users secure. We strongly believe VPN services should consider the PrivacyTools VPN Criteria, especially in regard to the ownership of their organization. Your VPN provider should not be hiding away in Panama controlled by anonymous leadership. While you as a user deserve privacy, transparency should be required of providers if you are expected to trust them. I would not give my money to some anonymous overseas investor, why would I give all of my internet traffic to some anonymous overseas administrator?
I am the administrator at PrivacyTools, a non-profit organization researching privacy-centric software and services. This article originally appeared at on Nov 20, 2019.

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Behavioral Intent Prediction Is Coming. Are We Ready?

November 21, 2019 in Biohacking

It can feel at times like we live in a science fiction future. We hold the whole of human knowledge in palm-sized devices that are constantly connected to the Internet. We speak to our computers and they respond with seemingly intelligent feedback. 

But while the hardware that powers our lives has advanced at rapid speed in the last three decades, voice assistant technology still relies heavily on the same human input that traditional software programs have for much of that time.

Amazon Alexa, for example, had 63,215 skills in the United States alone through June of this year. These are individually programmed interactions that users can have with their Alexa devices – from ordering products to checking the weather or playing a trivia game. 

But for Alexa to become a true digital assistant, the platform – and those like it in other devices – needs to be more proactive. This is where behavioral intent prediction comes in, utilizing machine learning to evaluate and predict user behaviors based on thousands of inputs.

The result will be a much more human-like interaction – with a device that can predict what a consumer needs and when they need it, much the same as a human assistant.

For companies, this will lead to a boom in data insights that further enhance targeting, personalization, and the likelihood of a sale. 

What is Behavioral Intent Prediction? 

The ability to predict the behavior of a consumer is a holy grail to many corporations. Billions of dollars are spent annually on market research, behavioral analysis, and new technologies to deliver smarter advertising to users. So, it’s no wonder we are starting to see an increase in the sophistication of our voice-activated devices – these are consumer applications after all. 

In 1980, Paul Warshaw summarized a new model for predicting behavior in consumers based on intentions. While the existing models that had long been used by marketers focused on attitude measurements developed by those marketers, the new model is designed to evaluate the subjective intent of an individual to perform a specific behavior. In short, there is a scientific basis for predicting what someone will do based on a number of variables. 

Fast forward nearly forty years and developers are using a similar approach to “teach” VUI’s like Alexa and Siri to learn more about their users and respond in kind. Of course, there are many challenges to successfully doing this as well.

The sheer volume of data that needs to be collected, cataloged and labeled before it can be input into the system is extensive. Amazon, for example, spends a considerable amount of money having thousands of hours of audio annotated each day to help the system better understand key elements based on the content of user speech. 

How Voice Interfaces Learn to Read Intent 

One of the biggest challenges with voice systems in their early iterations was how specific you needed to be. Everyone has attempted to trigger a command with their phone or Echo device and found that they did not use the right combination of words to trigger the action. 

These devices have been improved substantially and now attempt to determine, from context, what the user is asking, even if the specific language that triggers a skill is not used. Colloquialisms and variations on questions allow users to ask, “What’s it like outside?” or “Should I wear my coat?” instead of specific inquiries like “What is the weather in Chicago today?” 

Behavioral Intent Prediction goes beyond the reading of context in vague questions, though. It allows these systems to start evaluating key elements of how a user interfaces with the system each day. This is most evident in “Hunches”, a form of skill that allows Alexa to try and figure out what someone means based on location, time of day, or recent activity.

For homes that have sensors installed or for more advanced applications that interface with IoT devices, this allows for some creative implementations of voice control.

For example, you might say “Alexa, play some music,” and the device would be able to intuit which connected device to play the music on, and what volume to set based on the time of day and the typical volume you choose. 

The number of times that users have to reframe questions repeatedly to get the response they expect and desire is decreasing as these interfaces get smarter and better able to evaluate intent and respond in kind. 

Predictive analytics go well beyond what a company might see in a survey or market research study and analyzes every element of a phone call, VUI interaction, or other recorded discussion. This allows developers and marketers alike to evaluate the root cause of a conversation, why someone’s mood changes during such a conversation (an invaluable resource in customer service), and much more. The result is a better user experience that caters itself to the user, and more actionable data for companies. 

How Emotion AI Supplements Behavioral Intent Prediction?

One of the many barriers to a predictive model in voice assistant technology was the lack of context. Devices could hear commands and respond, and to some degree evaluate the specific words being spoken, but only with a more advanced approach to the context of the words and how they are spoken can the next step be taken. 

Emotion AI is capable of evaluating several elements of the user beyond their words. For example, it can take into account the regional dialect of the user, the micro-cues that indicate a specific emotion that might influence how and why they are saying something.

On a small scale, Alexa is now able to recognize when someone is whispering and whisper back – a godsend for parents trying to check the time or the weather while holding a sleeping baby.

Now imagine when the system could anticipate a mood entirely based on how something was said and respond accordingly, not only with the right content but in a way that is catered to those emotions. 

Behavioral Intent Prediciton is only one example of an emerging technology that is bridging the gap between human and machine. Advancements such as these are inevitable based on the current trajectory of implementation and discovery.

Rather than be fearful or doubtful of their abilities, take this as an opportunity to explore and engage in the understanding of how technology will advance humankind. 

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Where To Find Data To Make Smart Business Decisions

November 21, 2019 in Biohacking

You can make more informed decisions. The decisions can make your business increase its bottom line, evolve, and grow commercially. This decision making is possible when you tap into business intelligence and leveraging on the available digital insights. 

When you analyze, use the right tools of reporting, and accurately measure the available data, you will make the best decisions that are data-driven; thus, your business will thrive. Though you can follow your instincts in making decisions, learn to use figures, facts, and metrics as backups when making the decisions.

Below are the ways which will help you find the data that you can use to make wise business decisions.

Avoid Being Biased

More often, our minds work unconsciously. Thus, it becomes tough to justify the logic that we employed in decision making. Later on, you might feel guilty about the decision you made and wish that you had used the right available data.

Run your business with an excellent unbiased team to help you break down the available data before you make a decision. If you work with a team that has the working data, it will be insightful and helpful in giving the right feedback. 

When you use democracy in the data, you will empower everyone regardless of their level of expertise; they will access it and make decisions that are informed. To achieve this, use dashboard software.

When you have many people who know the working data, you will get insightful feedback that will help you in making decisions. To avoid being biased, collaborate, and create awareness among your colleagues. Additionally, find the information which may bring conflict; thus, you will be able to find other opportunities.

Know Your Objectives

Before you make a decision, ensure that you define and analyze the objectives of the business. Put a strategy in place to ensure that the conclusion that you will make are in line with the needs of the company. Additionally, be aware of the significant performance indicators in your business. Although there are many Key Performance Indicators in the industry, do not overdo yourself by focusing on the ones that are vital in your industry.

Available Data

Gather the right data when it presents itself. When you are operating a startup, collect the data from the day that you begin working. Implement the business dashboard principle in your business to avoid making decisions that are not data-based. 

Finding The Unresolved Questions

Most data are in the unresolved questions. For the business to make the right decisions, it ought to find answers to procedures in the operations and the way that the market operates. To find the correct data, consult the data analysts to know the fields that will be directly affected by your decision. Make a decision that will not adversely affect the operations of the business. 

Understanding And Analyzing

Analyze the process of production, operations of the customer service teams, the consumers, and the market. Store the data for future reference and decision making. Understand the way that they operate to make decisions that are in line with the information that you have obtained. Use alternative data that is available in the departments if you need to make an immediate decision.

Reevaluate And Revisit

More often, the brain is reluctant to consider the available alternatives. Instead, it jumps into conclusions. Always ensure that you revisit your assessments before making a decision. Verify and ensure that the data you have obtained have the correct metrics which will help you in making the right decisions.

To know the biases in the data, share it with the team members for scrutinization. Before you finalize on the decision that you have made, reevaluate it to ensure that it is beneficial. Additionally, note the areas that may not go as planned and rectify them on time. The keenness will ensure that the results that you produce are positive.

Use the available data; furthermore, conduct research, and evaluate the data before making a decision.

*I am no affiliated with any companies or businesses mentioned above.

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Questions On Crypto Cost Basis That You Need to Ask

November 21, 2019 in Biohacking

The pursuit of calculating cost basis for cryptocurrency is one that has been hindered by obstacles from three separate external factors; a gap in guidance for crypto regulation; a lack of legally approved best practices for crypto accounting and taxation; and smart technology to automate and increase accuracy and remove human error out of cost basis results.

To help the crypto community, tax professionals and to keep the world informed on how to calculate cryptocurrency cost basis, here are the most important questions and answers that crypto owners must know.

What is the difference between traditional and crypto cost basis?

Cost basis is a traditional accounting term that refers to the purchase price + fees + other associated purchase costs. The core of “basis” is the same for cryptocurrency cost as it is for traditional cost basis for calculating gains & losses. Essentially, anyone and everyone that makes a profit is expected to pay annual taxes on capital gains.

Traditionally, when calculating gains and losses, professionals will rely on general ledger software such as Quickbooks, accompanied by spreadsheets, calculators and lots of manual data entry and calculations. Additionally, traditional cost basis has clear regulations for tax obligations and compliance, while also having a more understandable financial ecosystem. 

This makes calculations more simple and predictable to calculate. 

To describe crypto cost basis more easily, if Jack purchased a Bitcoin in 2015 for $400, the basis on that Bitcoin is $400. If Jack sold his Bitcoin one-year later for $2000, he would owe taxes based on his gains of $1600. (Fees & other difficult factors are removed for this example)

Jack’s Original Purchase 2015: $400

Jack’s Basis with Fees 2016: $400 

Jack’s Sale Price of Bitcoin: $2000

Jack’s Taxable Gains: $1600

For calculating cryptocurrency cost basis, the process becomes far more complex. There are thousands of different types of cryptocurrencies that operate in different ways. Crypto also contains far more variables such as gas fees for fueling transactions within a crypto network, exchange or transfer fees, mining profits, soft and hard forks, airdrops and dozens of intricate taxable nuances. 

It’s simple to see that crypto can be far more perplexing. 

Why is cost basis important to me?

Cost basis is used to calculate a company or investors total gains or losses on an annual basis, usually for auditing or tax purposes. In the U.S, the government requests and requires all holders of cryptocurrencies to disclose their entire financial portfolio and have it reported annually for capital gain taxes. 

For the IRS to properly audit and assess an investor or businesses financials, they will require a complete overview of asset and transaction history to understand how much or how little a company or individual earned in crypto annually, 

By effectively and accurately reporting cryptocurrency holdings, gains or losses, in adherence to the tax obligations issued by the IRS, cryptocurrency investors that report their earnings not only remain legally safe, but can also see exemptions and other possible benefits of reporting promptly and properly. 

What happens if I don’t calculate or report my crypto cost basis?

While the regulation and legal framework are still being built, the consequences of neglecting to disclose a complete history of a digital asset portfolio can be punished by the federal tax arm of the government, the Internal Revenue Service. It is essential for cryptocurrency owners, investors, businesses and any operations that transacts with crypto to report and pay their annual taxation requirements. 

New tax forms now officially include sections to disclose your cryptocurrency earnings for the year. While the issue of disclosing personal crypto portfolio information has been disputed by many in the crypto community, this is an official law approved by the American federal government, making it unequivocally legal and enforceable. 

There is destined to be edge cases where no legal framework exists, such as if an exchange is defunct and investors lost access to their transaction history. Every case is different, but reporting honestly and proactively, as well as staying informed is the best way to stay on the right side of the law. 

How do I calculate my crypto cost basis?

Calculating cost basis for crypto is exceptionally difficult due to the secure nature and wild web of complex transactions and taxable financial events. The best place to start is by noting down all wallets, exchanges, accounts and portfolios to ensure investors have the full picture of their crypto portfolio. 

Investors and businesses alike may rely on third party accounting services to help calculate crypto cost basis, while small investors will look for software and more feasible solutions. 

It is not recommended to manually calculate cost basis due to the extreme complexities of transaction activity and the behavior of the ecosystem. 

Moreover, calculating gains and losses on 100 transactions manually can take hundreds of hours, pouring over spreadsheets, documents and hoping for an accurate result. Unless your are a well-trained finance professionals, leveraging technology, or accounting firms is usually the safest best for investors and businesses. 

Are there tools to help me calculate my crypto gains and losses?

Other software of startups such as TokenTax exist with the goal of helping crypto businesses and investors with the day-to-day and back office software solutions for managing their crypto or calculating gains and losses. Tech and software can work together to help keep investors and professionals more organized and connected to their crypto with full control and management of assets. 

It is always important to investigate the right platform for each business and individuals, and leveraging technology on a day-to-day basis. This will ultimately help to keep track, organize and prepare for tax season, auditing, financial accounting and other tax obligations.

What is next for cost basis?

The dominance of bitcoin, despite its epic price fluctuations, has made it more important than ever, to begin calculating gains and losses for investors, businesses and institutions. In the eyes of the IRS, anyone and everyone is entitled and liable to pay taxes on crypto earnings. 

The evolving landscape of crypto taxation is slowly changing everyday, and creating new rules and regulations for how to calculate gains and losses and navigate the financial world of cryptocurrencies. 

For businesses, they may already have an internal finance team, or hire external accounting firms to handle bookkeeping and taxation. But for small individual investors, they must rely on more localized and cost effective means for calculating cost basis. Regardless, businesses and investors of all shapes, sizes and networth are all governed by the same tax laws. 

(Disclaimer: The Author is a co-Founder at

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