300 karma · joined July 25, 2018
It made me think: is there a better way to read the classics?
The result: a iMessage interface that presents The Republic in a fresh way.
p5 was a core dependency for Art Blocks, a popular Ethereum art platform that gained popularity due to its asset class of entirely generative artworks.
The reason that GDP growth is so important is because it raises the standard of living for those who aren’t yet born. If you accept the premise that lives in the future matter just as much as those today, then the vast majority of human lives are yet to be born and therefore deserve consideration about what to do __today__.
Even small changes in GDP growth (e.g. 1-2% per year) has dramatic compounding effects over a multi decade timeframe.
For a great book on this, I recommend Tyler Cowen’s Stubborn Attachments which discusses the ethics of economic growth: https://press.stripe.com/stubborn-attachments
- Kevin Kelly: kk.org
- Patrick Collison: patrickcollison.com
- Patrick McKenzie: kalzumeus.com
- David Perell: perell.com
- Berthub.eu
- Alexey Guzey: https://guzey.com/
- https://astralcodexten.substack.com/
- Paul Graham: paulgraham.com
- Laura Deming: https://www.ldeming.com/
- Sam Altman: https://blog.samaltman.com/
- Casey Handmer: https://caseyhandmer.wordpress.com/
disclaimer: his work is widely cited as pseudoscience. it's a good read if you're looking for entertainment value, but try not to take it too seriously :)
> It led to the 20th century’s most successful game console: the Game Boy. One day, a gaming engineer named Gunpei Yokoi was commuting home on the train when he saw a man playing with an LCD calculator next to him. Unfortunately, Nintendo didn’t have the budget to push the technological frontier at the time, so they used old technology to innovate. So long as the gameplay was engaging, Yokoi believed that players didn’t care about technical details like colors or screen resolutions. Compared to its contemporaries, the Game Boy was durable and affordable, which removed barriers to entry for users and developers. People would play for hours because it used AA batteries that were cheap and easy to find. Today, the Game Boy has sold more than 118 million units.
Modern language models (eg GPT-3 et al) offer the capability to take a natural language input, match it against the context of the sentence, then propose a query that is understandable to the layperson. This abstraction allows us to understand the problem better, rather than just analyzing the way the problem manifests itself in code. Having a programming language that mirrors our everyday communication is an important step forward in making the innovations from software broadly available.
The next wave of programmers will need to understand how human language can be used to efficiently guide models to solve problems that can’t be solved by human-written code. This is a big challenge, and we’re just at the very beginning of it, but I think it will open up new and undiscovered ways to create value in the world.
I have quite a few additional thoughts on the topic which I’ve captured here: https://sundayscaries.substack.com/p/whos-the-real-expert
tl;dr: combine ideas from different domains, talk with friends who have interesting ideas, work on things that interest you
The email standard(s) are great. Powerful, decentralized, and damn near universal. It's just that we live in a world where a Duopoly has taken over most of what we consider to be email.
If this comment resonated with you, I am working on something you might be interested in. Feel free to DM me for details.
I wrote this post to help others who are considering how to spend their last few weeks at a company. There will be many demands for your attention -- this attempts to help you prioritize what is important to spend time doing.
Eric, a question if I may:
Is there room for a modern PhD that values breadth over depth?
The goal of completing a Ph.D. program is to become the most knowledgable person in the world about a specific topic. While this is a valuable goal for disciplines that reward specialization, it does not provide enough flexibility for autodidacts with a range of interests.
A P.h.D. typically takes between 3 and 6 years of self-directed study. If candidates spend between 35 to 70 hours per week, this amounts to 5,250 hours on the low-end and 21,000 hours at the extreme end.
Of course, not all of this time is spent on research. In fact, modern P.h.D. students spend more time than necessary dealing with administrative functions like teaching, grading, and paperwork for the university.
What would you recommend to someone planning their own "personal PhD"? That is, four to six years of self-directed research on a specific topic.
This is something I think about often. Many citizen scientists like Franklin, Edison, and Darwin were not the result of PhD programs but instead curious professionals who conducted independent research.
Other specific questions:
- What is a suitable replacement for the role of advisor? Is there a representative person outside of academia who would provide the same type of advice?
- What type of fields are best suited to personal PhDs? Low capital investment (ie, no expensive lab equipment) seems like a constraint?
Like I said, I think about this often and have written more on the topic here: https://sundayscaries.substack.com/p/the-lifetime-curriculum...
It’s easy to focus on the next promotion or the completion of a big project that will elevate your career.
By succumbing to the natural instinct of mimicry, we rarely ask ourselves the question: are we climbing the right hill?
In this analogy, the hills represent any long-term goal: career, fulfillment, financial security. Our natural instinct is to walk upward, chasing the next promotion or job opportunity. However, we lose the virtue of randomness by doing this. If your only benchmark is the hill you’ve always known, you have no way to gauge its relative steepness. It’s a good way to reach a local maxima, but not necessarily the best long-term option.
Instead, I allow myself to explore other options, even if it seems “downhill”. For naturally ambitious people, it can seem downright impossible to avoid this instinct. It’s hard, and often feels unnatural. However, the perspective gained from these excursions improves my mental map and I’m able to learn what lies on other hills. Taking this mindset means letting go of the mimetic behavior that leads to jealousy or comparison.
After all, why should it matter if someone else is higher? Your peak is somewhere else entirely.
https://sundayscaries.substack.com/p/climbing-the-right-hill...
I was curious about this, so I made a dataset to understand U.S. Legislative Education. This dataset contains complete education details for members of the 116th United States Congress, including universities, degrees, and political affiliations. I hope that this dataset is helpful for anyone who may wish to further investigate the correlation of education and academic credentials with policy decisions made by members of our government.
This dataset can be used to answer questions like:
- Is political affiliation correlated with education?
- What is the most common degree type for U.S. Senators?
- What percentage of U.S. Congressmen dropped out of college?
- Which college has the most representation in the House of Representatives?
- What percentage of Congressmen are scientists?
With some creative co-mingling, this dataset can be used to supplement research questions like:
- Are policy decisions correlated with education?
- Are there relationships associated with college affiliations and voting in Congress?
- Can we find a relationship between hot button topics and education?
- How is public sentiment influenced by education level?
"The Fermi paradox is the conflict between an expectation of a high {\em ex ante} probability of intelligent life elsewhere in the universe and the apparently lifeless universe we in fact observe. The expectation that the universe should be teeming with intelligent life is linked to models like the Drake equation, which suggest that even if the probability of intelligent life developing at a given site is small, the sheer multitude of possible sites should nonetheless yield a large number of potentially observable civilizations. We show that this conflict arises from the use of Drake-like equations, which implicitly assume certainty regarding highly uncertain parameters. We examine these parameters, incorporating models of chemical and genetic transitions on paths to the origin of life, and show that extant scientific knowledge corresponds to uncertainties that span multiple orders of magnitude. This makes a stark difference. When the model is recast to represent realistic distributions of uncertainty, we find a substantial {\em ex ante} probability of there being no other intelligent life in our observable universe, and thus that there should be little surprise when we fail to detect any signs of it. This result dissolves the Fermi paradox, and in doing so removes any need to invoke speculative mechanisms by which civilizations would inevitably fail to have observable effects upon the universe."
roamresearch.com
Scott is one of the best teachers on the topic, and makes complex models simple and intuitive to understand.
It is a long course, but well worth it. Cannot recommend it enough.
No snark intended. His letters intended for investors are the best use of your time rather than a book someone wrote for vanity.