Technology

Why MicroStrategy Bought 21 Thousand Bitcoin And Why Other Companies Will Too

Yesterday was a landmark moment for Bitcoin and its adoption as a reserve asset, MicroStrategy, a NASDAQ-listed company, bought 21,454 Bitcoin at a total of $250 million.

After the quick takes on Twitter have been made and the dust has settled, we want to have a close look at the press release to find out what really made MicroStrategy choose Bitcoin as a reserve. From there we might just be able to deduct how impactful this fact really could be for the future of Bitcoin.

Their press release starts as follows (bold highlights by me).

TYSONS CORNER, Va.–(BUSINESS WIRE)–Aug. 11, 2020– MicroStrategy® Incorporated (Nasdaq: MSTR), the largest independent publicly-traded business intelligence company, today announced that it has purchased 21,454 bitcoins at an aggregate purchase price of $250 million, inclusive of fees and expenses. The purchase of Bitcoin cryptocurrency was made pursuant to the two-pronged capital allocation strategy previously announced by the company when it released its second quarter 2020 financial results on July 28, 2020.

The main point in this paragraph are the 21,454 Bitcoin purchased at a total of $250 million. Disregarding that fees are included, 21,454 Bitcoin at $250 million comes down to an average price of $11,652.84 per Bitcoin.

This relatively high price, given that Bitcoin only recently reached back up to $12,000 and traded as low as in the 3 thousands in March allows for two possibilities. The first is that MicroStrategy made a wholesale purchase, potentially OTC, over the last few days and did not average into the position over the past couple of months. The second option would be that they have considerable cost allocated to the purchase effort and custody of their Bitcoin, and those costs raise the average buy-in price accordingly. For now we don’t know the answer to this as they have not released how and with whom they custody or when they made their purchase. Yet, we can take a cue from their Q2/2020 results in which they announced their plan on how to invest the $250 million on 28 July 2020. Unnoticed by seemingly everyone, MicroStrategy actually mentioned that they’re considering to invest in “one or more alternative investments…such as bitcoin”. So I assume they had their minds set pretty straight on Bitcoin already at the time of the announcement and bought their share shortly after at prices over $11,000 and custody costs etc. only play a minor part in the average cost per Bitcoin.

They continue with general information referring to their Q2 results again until explaining why they invested in Bitcoin.

“Our investment in Bitcoin is part of our new capital allocation strategy, which seeks to maximize long-term value for our shareholders,” said Michael J. Saylor, CEO, MicroStrategy Incorporated. “This investment reflects our belief that Bitcoin, as the world’s most widely-adopted cryptocurrency, is a dependable store of value and an attractive investment asset with more long-term appreciation potential than holding cash. Since its inception over a decade ago, Bitcoin has emerged as a significant addition to the global financial system, with characteristics that are useful to both individuals and institutions. MicroStrategy has recognized Bitcoin as a legitimate investment asset that can be superior to cash and accordingly has made Bitcoin the principal holding in its treasury reserve strategy.”

Here MicroStrategy is saying one thing and implicitly stating another too. They’ve identified that holding cash, meaning US dollars, is a worse investment for them than buying Bitcoin. Additionally, what they’re not saying but implying is that Bitcoin is a better investment for them, not only than cash but also than "stocks, bonds, commodities such as gold". As, again, per their Q2 results they were considering investments in all these but settled on Bitcoin as the most viable option.

The second statement to note is the conscious decision to call Bitcoin “a dependable store of value”. This aligns fully with the current view of Bitcoin’s main value proposition and main driver until a broader adoption has taken place.

Mr. Saylor continued, “MicroStrategy spent months deliberating to determine our capital allocation strategy. Our decision to invest in Bitcoin at this time was driven in part by a confluence of macro factors affecting the economic and business landscape that we believe is creating long-term risks for our corporate treasury program ― risks that should be addressed proactively. Those macro factors include, among other things, the economic and public health crisis precipitated by COVID-19, unprecedented government financial stimulus measures including quantitative easing adopted around the world, and global political and economic uncertainty. We believe that, together, these and other factors may well have a significant depreciating effect on the long-term real value of fiat currencies and many other conventional asset types, including many of the assets traditionally held as part of corporate treasury operations.”

This section highlights the risks associated with unmitigated government spending that many macroeconomic thinkers, Austrian economists and Bitcoiners have pointed out over the past months and shows that corporate leaders agree with the sentiment that the end of fiat currencies is a real identified risk.

In considering various asset classes for potential investment, MicroStrategy observed distinctive properties of Bitcoin that led it to believe investing in the cryptocurrency would provide not only a reasonable hedge against inflation, but also the prospect of earning a higher return than other investments. Mr. Saylor articulated the opinion, “We find the global acceptance, brand recognition, ecosystem vitality, network dominance, architectural resilience, technical utility, and community ethos of Bitcoin to be persuasive evidence of its superiority as an asset class for those seeking a long-term store of value. Bitcoin is digital gold – harder, stronger, faster, and smarter than any money that has preceded it. We expect its value to accrete with advances in technology, expanding adoption, and the network effect that has fuelled the rise of so many category killers in the modern era.”

This paragraph shows that MicroStrategy has done its homework on what makes Bitcoin valuable – a few things stand out.

They mention the architectural resilience which in my view is pointing to the network security of Bitcoin and how a higher price and rising hash rate leads to a more secure network that makes double spend financially irresponsible to attempt. This is important for companies to understand if they consider Bitcoin as an investment.

Next is the community ethos of Bitcoin. This could mean several things but I don’t think it’s our little community of Bitcoin Twitter but rather the ethos of the community to understand the value of a hard cap of 21 million Bitcoin and the shared understanding that this cap will not be removed.

Last but not least, the network effect. This is what many people outside of tech have still issues with understanding but is essential. Bitcoin was the first of its kind and has grown tremendously over time. The effort, work and time put into developing the system, the community, the hardware, the understanding is so important to Bitcoin and gives it a network effort much bigger than any other cryptocurrency. These qualities cannot be taken away and extend Bitcoin’s reach ever more. And although there are a myriad of other coins out there, money will always accrue to the best money and has been identified correctly by MicroStrategy.

So what does MicroStrategy’s move mean for the future of Bitcoin?

For one, it broke the glass ceiling of Bitcoin not being a viable reserve assett for corporations, mainly due to its fluctuating valuations.

As Andy Yee put nicely, “Paul Tudor Jones removed career risk for hedge fund managers from investing in Bitcoin. MicroStrategy removed career risk for CFOs from putting company treasury into Bitcoin”. This cannot be overstated as it sets a precedent allowing companies to realistically consider Bitcoin as an asset to invest in and profit of its appreciation. With this step taken, many companies will have to evaluate their risk profile and review whether their previous assessments of gold, cash and other assets need revisiting.

Consider for a moment how many companies there are in the world and then take note of the fact postulated by Michael Goldstein that “no more than 860 individuals or companies can have 21,454 bitcoins right now” because that is the total amount of Bitcoin in existence today. So price appreciation will be one big result of more companies dipping their toes into Bitcoin but it’ll also mean less investment into traditional assets that currently would get that investment, leading to them depreciating.

On the time perspective we have to consider the decision making processes and time needed for education. MicroStrategy seemingly has made a call end of July 2020 and invested a big amount on short notice but based on their press release they clearly had done their research on Bitcoin’s value proposition and that is something every company will need to do in their own time horizon. Entertainingly, MicroStrategy’s CEO, Michael Saylor, tweeted in 2013 that “Bitcoin days are numbered” just to seven years later consider it the best option to invest in for his company, so education takes time but CEO’s and CFO’s will get there, but surely not at the same prices as MicroStrategy did.

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Analysis of GPT-3 and its implication for the future

Over the past week Open AI has opened up its private beta access to its latest natural language processing (NLP) model, Generative Pretrained Transformer 3, or GPT-3 for short. It immediately captivated the Twittersphere with a viral tweet by Sharif Shameem showing the impressive capabilities this optimized version has due to being trained on a way larger dataset of 175 billion parameters compared to his predecessor GPT-2, an increase of two magnitudes. A lot of interesting applications for GPT-3 followed and I was intrigued (as is evident from my tweets on GPT-3) to look into it in more detail to understand what it really could be capable off and how it could impact Bitcoin.

So let’s have a look at:

  • what GPT-3 is
  • what it is capable off and what not
  • why it is important to understand it and its implications

What is GPT-3?

GPT-3 is a neural network for natural language processing and creation. This means that GPT-3 is capable of understanding human language (primarily in English but allegedly capable of understanding eleven languages at point of writing) and reacting to it with text generated by itself that is totally unique, not a regurgitation of pre-scripted sentences.

The API provided by Open AI allows to give GPT-3 inputs in form of words and sentences up to ten paragraphs and it will react with an output based on its 175 billion parameters that it was trained on. This huge set of parameters includes information available on the internet up to October 2019 and therefore does not only contain text but also mathematical formulas and code.

Since it’s a limited beta it’s currently not possible to train the model on a specific set of data as it was possible with its predecessor GPT-2 but that might change in the future. At this point GPT-3 is already far more advanced than any other model available and will be considered the de-facto standard for the time being on the road of development to a General Artificial Intelligence (GAI).

What is GPT-3 capable off and what not?

Since the release of the beta access we’ve seen myriads of use cases tested already and it seems the limits are more limited by human creativity than GPT-3’s limitations. This doesn’t mean that GPT-3 can be considered intelligent but it certainly reached the level of successfully tricking people in believing it to be so when the examples published were chosen carefully.

Some of the most extensive testing of GPT-3 regarding its creative use cases has been done by Gwern, as he did before with GPT-2. Additionally Max Woolf has done a lot of work on GPT-2 and now also put GPT-3 through the motions. Here’s a list of impressive results that were achieved by/with GPT-3:

There were many more interesting examples where GPT-3 was able to create SQL and React code, create Figma designs and translate difficult legalese or academic text into understandable explanations for non-experts, all highlighting the fascinating capabilities of the model but also surfacing its limitations.

The creative use cases have shown that GPT-3 became repetitive when creating longer texts, had difficulties rhyming properly and would get into trouble when being asked nonsensical questions. So while very impressive and clearly best in class, GPT-3 is not intelligent and will unlikely be in the near future. A GAI is not realistic yet but it is easily foreseeable that next iterations of GPT will blur the lines between human created works and machine created ones irrevocably.

Why it is important to understand GPT-3 and its implications?

To know where AI and machine learning (ML) is headed, we need to understand where we are. GPT-3 is impressive but even Sam Altman, co-founder of Open AI, is cautioning the hype. So we now have a machine that was able to read and understand a data set of 175 billion parameters – at least to a certain degree. Based on this understanding GPT-3 is able to learn new inputs and try to understand what is asked of it. One example would be that it was able to read 3 rows of Excel data with two populated columns and on the fourth row predict the missing data field based on the first one and how the two columns related to another in the previous rows.

With Moore’s law still intact we can expect the quantity of data a machine can learn and understand to increase exponentially. This exponential expansion makes it difficult to predict for the long- or even mid-term. As Bitcoiners we have a better understanding of exponential growth than many who cannot fathom such increases, but what an ever more knowledgeable machine will be able to do long-term is anyone’s best guess and better located in the world of science fiction.

So short-term, what might be next? I think we can expect GPT-4/5 to be able to communicate like a human so most of us will not be able to identify what is created by a human and what by a machine. This will have far-reaching implications in itself but likely even more in second and third order effects. Texts created by a machine will be translated into other mediums almost without problems. We will see books, audio plays, even movies based on machine generated content. We will have Twitter and Reddit bots filling and leading conversations online, emails will be written between machines; GPT-3 can already write emails based on minimal human input. So the lines will blur online as well as offline – but it will not end at text creation.

Pattern recognition is already strong in GPT-3 and the applications for this are immense. Pattern recognition is one of the most important, innate human capabilities and machines will be so much better at it. We will see constant iteration and continuous improvement on everything from product design, code creation, automation to levels unimaginable today, efficiencies in all disciplines will rise. Even art will not be “spared", the next GPT version might be so good at identifying valuable art and creating new pieces based on existing ones at unhindered speed, ever-creating.

Now we could say that these things will be limited to the digital realm but I wouldn’t be too sure about this. 3D-printing is already picking up speed and moving towards mainstream adoption with smaller and cheaper printers available each year (see also Jeff Booth’s excellent “Price of Tomorrow” on this). It might have a big part to play in this future of constant iteration and optimization by GPT-based machines.

And last but not least there are the financial markets which are already heavily automated and based on neural networks, consuming huge amounts of data to make nanosecond decision to get an edge above the competition. One can only speculate what an openly available (for a price) model like GPT could mean for active trading, it certainly will lead a lot of experimentation.

So where does all this leave us? Some have already wondered whether GPT-3 the "next big thing after Bitcoin” but I wouldn’t go so far just yet. Bitcoin stands on its own and will change the way humanity approaches money all by itself, thereby Bitcoin is still the current and next big thing. So GPT-3 is not the next big thing, GPT-4 might just be. I certainly noticed a leap being taken with the release of GPT-3 and a substantial change in terms of General AI might not be too far out, until then I plan to push Bitcoin adoption along and experiment with the possibilities that GPT-3 opened up.

These are exciting times and I’m keen to see where these technological advances lead to next.

Onward and upwards!

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