Give more context on your drawing of parallels between the European Reformation and what is happening today

While the European Reformation's ire was directed at the errors, abuses, and discrepancies of the Catholic Church, the current Reformation is upending nation-state governments and the downstream structures of power that benefit from their existence - namely media and large corporations.

While the timeline for the European Reformation was centuries, we believe the compounding effects of technology, a much steeper climate curve, and an unprecedented shift in demographic scale will compress the Modern Reformation to be years, not centuries.

References by topic

A lot of AI is about two things:

  • Building stuff to turn squishy reality into something digital and structured - that's the point of a lot of computer vision. - gives humans superpowers of computers.

  • Building stuff to reason about the resulting digitized representation of reality (e.g, massive generative models that can be prompted, like CLIP or GPT3).

  • Like the internet, deep learning is relevant for every industry, not just for the computing industry. Deep learning software is a core differentiator for retail, automotive, health care, agriculture, defense, and many other industries.

  • Like the internet, deep learning endows computers with previously unimaginable capabilities. The internet made it possible to search for information, communicate via social media, and shop online. Deep learning enables computers to understand photos, translate language, diagnose diseases, forecast crops, and drive cars.

  • Like the internet, deep learning is an open technology that anyone can use to build new applications. While deep learning used to rely on computer scientists and specialized hardware, it now can be done using a laptop and a few lines of Python code.

  • Like the internet, deep learning should be highly disruptive, perhaps far more disruptive than the internet. The internet has been disruptive to media, advertising, retail, and enterprise software. Deep learning could change the manufacturing, automotive, health care, and finance industries dramatically. Interesting to note, those industries have been sheltered to some extent from technological disruption to date.


  • The cost to sequence a genome, once a nine-figure nation-state-worthy project, has dropped into the hundreds of dollars.1

  • Editing DNA is becoming an antidote to pervasive, chronic disease.

  • For the first time, living therapies are likely to cure certain diseases with just one dose.

  • Bioinformatics is tying DNA sequencing data and therapeutic initiatives to patient outcomes,providing scientists, corporations, and clinicians with an unprecedented understanding of how the human genome can break down and how it might be mended.

    Big Ideas: Technological Breakthroughs Investors Shouldn’t Miss in 2019

    Unit costs to program cells is declining by 50% every year

Risks and counter-arguments

Regulatory Risk.

All four technologies that we are focused on have caught the eye of legislative bodies. If there are onerous laws passed to prevent these technologies from being adopted, that may inhibit growth in companies we invest in.

I may not know what I'm talking about.

The broad and deep ambitions of this fund require strong grasps of domains that are very technical. Additionally, my assessment of the intersections between these domains and the larger macro trends may have a fundamental flaw that I am unable to see.

I may be wrong about timelines for change.

The time compression I speak to may not happen, and we could see these changes play out in a longer time period, 15-30 years. If that is the case, many of the companies we invest in would be too early.

Illustrated here
Population growth