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"We curate our lives around this perceived sense of perfection, because we get rewarded in these short term signals: Hearts, likes, thumbs up. We conflate that with value, and we conflate it with truth, and instead, what it really is is fake, brittle popularity that's short term and leaves you even more vacant and empty before you did it."

- Chamath Palihapitiya, Investor.

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Bonsai Guy, artwork from Jeremiah Shaw 3D artwork made with OctaneRender.

Dense Discovery

🎇 2021: A Hopeful Year 
 

We are back with our regular Sunday programming.
 

2021 looks to be off with an exciting year for technology markets. Bitcoin is at an all time high. Tesla stock prices have been imitating the trajectory of SpaceX rockets - making Elon Musk the wealthiest man in the world. At the same time, London and even countries who have managed to be more effective in dealing with COVID-19 are being hit by a mutant and more viral strain.  
 

We previously covered Bitcoin and Tesla last year with a bullish prediction. This week’s issue will dive into some of the biggest predictions, hits and fails.

A Week In Summary: Brewing Socio-Tech Cauldron

Jake Angeli, dressed as a ‘Viking shaman’ in the protest intrusion of the U.S. Capitol.

  • Trump has finally conceded. Not before however a Pro-Trump protest stormed the U.S. Capitol and Mr Trump getting a suspension on his Twitter and Facebook accounts. This was later followed by a permanent Twitter ban with Reddit also following suit with the banning of subreddit group “r/DonaldTrump”. People remain divided on Twitter’s censorship given that others like Iranian Ayatollah Ali Khamenei remain untouched on the platform.

    The incoming Biden administration looks to ‘release’ nearly all of  the available COVID-19 vaccine and to make changes with environmental policy. Trump said he won’t be attending the Biden inauguration.

     

  • Bitcoin has hit all new time highs, doubling its price in a month. Bitcoin ‘whales’ (addresses with over 100 Bitcoins) have accumulated more than 47,500 Bitcoins during the December rally. Earlier this week, some anonymous users began to make some large transfers of over 4,000 BTC (~$196USD mil).
     

  • The UK is seeing record numbers of positive coronavirus cases with the new strain. London has seen the highest increase in hospital admissions and Mayor Sadiq Khan has declared it as a “major incident”. The strain has seen many countries reduce their flights and close travel corridors with the UK.
     

  • OpenAI (the creators of GPT-3) have debuted DALL-E which creates images from text. Using a 12-billion parameter version of GPT-3, it uses a transformer language model to process image and text.
     

  • The MetaVerse grows with Roblox looking to do a direct listing at a valuation of $30 Billion USD instead of an IPO at $8 Billion USD. More than 960,000 developers have been earning Robux (virtual cash that can be converted into real money). When users exchange Robux for money, Roblox takes a 30% share of the transaction.

The predictions for what the world will look like

 

Predictions and prophecies of the future are as old as time itself. 

 

According to the ever reliable Wikipedia, Michel de Nostredame (aka Nostradamus) is said to have made 6,338 predictions in his almanacs. Of those predictions, a number have been proven to be ‘correct’. A quick search on YouTube will often show that The Simpsons is equally good at predicting the future. For example, a video essay by ScreenRant shows that a lot of what has been shown on The Simpsons have ‘come to pass in 2020.

 

How accurate are people’s predictive faculties?

 

One of the most famous studies on prediction was done by political scientist, Philip Tetlock in his 2006 book Expert Political Judgment. In his research, Tetlock asked a group of pundits and foreign affairs specialists to predict geopolitical events. Overall, the “experts” struggled to perform better than “dart-throwing chimps”. They were also consistently less accurate than simple statistical decision making models. This was regardless of creed or credentials.

 

Another experiment which seems to indicate that expert humans aren’t as great as their ego thinks on their predictive ability is by economist, Burton Malkiel in his book A Random Walk Down Wall Street. Testing the random walk hypothesis with his students flipping coins, Malkiel concluded that the future direction of the stock market could not be predicted by its past. That “a blindfolded monkey throwing darts at the stock listings could select a portfolio that would do just as well as one selected by the experts”.

Setu Mazamdar recreated Malkiel’s experiment by coin toss and compared the chart to that of the actual Dow Jones Industrial Average.
 

Prices seem random in fluctuations unless you are Tesla 😉
 

🛠 The Tools To Predict
 

Whether it be the hedge fund managers or Movie Studio Execs trying to predict and make a bet on a film’s likely success, data seems to suggest that ‘experts’ aren’t generally very good at predictions. In most attempts of predicting what will happen, with streaks of successes, the human guesses are not too different to statistical estimates of a stochastic process.

 

A larger amount of data and a new array of techniques plus technology may make us better at prediction. Cliodynamics and applying machine learning to large datasets (similar to DeepMind’s success with AlphaFold in protein folding) may of course change this.

 

We will cover in more depth next week, on certain techniques and tools that can be used for more data predictive models.

 

🎯 Predictive Hits & Misses.

 

With Tesla’s soaring stock prices and investors following the thesis of Tesla being more of a tech company than car company, we can look back into past predictions. The cheery GM Motorama Exhibit of 1956, shows the Firebird ‘self driving’ (“safe, cool and comfortable”) car as being coordinated with control towers (like airport terminal) and running on magnetic car strip roads. 

 

The GM ad reflected the fascination of the 1900s with aviation and automation. Cars were influenced by turbines. It was imagined that in the 2000s, automobiles would be replaced by flying contraptions.


One leading German chocolate company, Hildebrands, made a series of commemorative postcodes and speculated that people would take to the skies. They predicted that people would travel by personal airships and gliders, that buildings would be movable (aka Howl’s moving castle) through trains, and that cities would be encased in glass to be protected from the weather elements.

In the 1920s, people were fascinated with skyscrapers and the term ‘robot’ was conceived. The dream was of a future of convenience and luxury. 


The 1960s and 70s saw an even more futuristic prediction. With the US and USSR competing in a space race, people dreamt of humans as space colonisers. NASA’s founding in 1958 propelled the U.S. into being the first nation to land a person on the moon in 1969. The period saw the emergence of Googie building design in the U.S. and Hollywood imagined what an intergalactic species would look like through gripping films like Star Trek (1966) and Star Wars (1977).

In the 1980s and 1990s, computers became more prevalent and people predicted a digital and physical reality. Hollywood hits like Terminator (1984) and Back To The Future (1985) conveyed potentially existential technology risks to society. Capitalising on the hype for immersive digital experiences, Nintendo launched the Virtual Boy headset in 1995, an attempt to offer gamers a 3D experience. It was a flop - selling only 770,000 units and remains Nintendo’s biggest fail.  

 

✅ One of the best predictive bets

 

Whilst there have been some very good predictions and bets such as Masayoshi Son’s $20M investment in Alibaba which has returned SoftBank about 5000x (~$100B) There have also been a number of flops (by the same guy) and others.

 

❌ Some of the worst predictive fails

 

Microsoft’s former CEO Steve Baller in 2007 thought that the iPhone:
"[Apple's iPhone] is the most expensive phone in the world, and it doesn't appeal to business customers because it doesn't have a keyboard, which makes it not a very good email machine…"

 

John McAfee betting to eat his ‘d*ck’ in 2017 on what the price of Bitcoin will be in 2020:

Five Luminary Lines

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Creator: Jessica Zhou the SocioTechnical 👩‍🎤

A Phrase Worth Remembering

“Because, most of all, our tomorrow is the child of our today. Through thought and deed, we exert a great deal of influence over this child, even though we can’t control it absolutely. Best to think about it, though. Best to try to shape it into something good. Best to do that for any child.”
- Octavia Butler, "A Few Rules for Predicting the Future”

A Concept Worth Understanding

Sinofuturism! I've learned so much from anything/everything written/spoken by Xiaowei Wang, who recently published "Blockchain Chicken Farm," and wrote a piece in 2018 that reframed my view of innovation as I was entering the tech industry as a baby software engineer. As someone who wants to better understand the Chinese and Asian American diaspora as a means to better understand who precedes me, I take a lot of comfort in learning about the past through exploring these futurisms.

An Activity Worth Trying

Taking a dance class with a teacher who talks about embodiment and body awareness is worth doing at least once -- it's rare in our daily lives that there's space made for us to explore motion!

My favorite classes have been ones that allowed for playfulness and experimentation in movement, and explored form/function, encouraging us to perceive how movements felt in lieu of focusing on the appearance in the mirror.

A Habit Worth Having

Keeping a thorough journal for personal records - it is a gift to be able see growth and change over the years, to see dreams fulfilled and new ones sprout! All that fun stuff :) It is also of course super awesome for processing life day by day -- there is magic in the mundane!

A Creator Worth Viewing

Danielle Baskin is so darn cool.

Brain Gems

The Strange Story of Satoshi Nakamoto’s Spelling Choices
(by Michael Kapilkov)

Who is Satoshi Nakamoto? The anonymous creator/s of Bitcoin is estimated to have around 1,000,000 Bitcoins. At current prices, that is around $30.2 Billion USD. Kapilov conducts some statistical analysis of Satoshi’s writings and finds inconsistencies in Satoshi’s preferred English communication language choices. Is Satoshi a team or a purposeful operations security writing technique? 

 

Kolgomorov Complexity - A Primer
(by Jeremy Kun)

Is it possible to generate truly random numbers using a computer program? The Kolgomorov Complexity theorem (Definition: The Kolmogorov complexity of a string w, denoted K(w) is the length of the shortest program which outputs w given no input), helps to think about the complexity of a program (the algorithmic content required) in calculating a string. Kun explores this. Depending on whether one thinks the universe is deterministic, it is interesting to think with this theorem on the entropy and perhaps eventual negentropy of cryptocurrencies. 

 

Mapping the Passions
(by Alan Cowen, Disa Sauter, Jessica Tracy and Dacher Keltner)

What would a comprehensive atlas of human emotions include? Using empirical findings, the authors suggest an alternative concept to the six emotions framework (the “basic six”: anger, disgust, fear, sadness, surprise, and happiness) and propose a more inductive methodology in identifying emotions. They suggest there are 25 states. You can explore a mapping of 24 emotions as conveyed by brief human vocalisation here. I had so much fun with it… the soundboard is quite a symphony of sounds!



Your valuable opinions needed!

 

I work hard to send you less. If you don't want to check 100 sources each week, read my newsletter. 

 

If you have any thoughts, feedback on this newsletter or how we can help you, please do let me know through replying to this email or on Twitter

 

Looking forward to your thoughts!

 

- Daniel

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