Such a great rip with @RealOilRspctr and @SeedOilDsrspctr - it's becoming increasingly clear that seed oils are (1) in damn near everything we eat, and (2) detrimental to human health.

Give them a follow and take the seed oil pill:

https://twitter.com/Orangepilladdix/status/1509196634143424512?s=20&t=QyJWY6cN-5oh9QYenDFYzg

In my personal experience, disrespecting seed oils has led to:

- much higher and more stable energy levels
- significantly fewer "down" days
- far fewer cravings
- almost never feeling "hangry"

Modern society is the result of short-term decision making that tries to treat symptoms as quickly as possible rather than address the underlying issue.

Once you see this, you can't unsee it. - Pharmaceuticals / Healthcare (here take a pill)
- The absolute behemoth federal government (TSA, IRS, etc.)
- The entire tax industry (people working 80+ hours / week to help a client comply with some law passed by a geriatric senator to appease his donors 20 years ago)

The single most underrated feature of #Bitcoin is that it ties money to the global energy supply.

Today, money printing incentivizes humans to do one thing: consume.

Consumption requires energy - consider all that goes into getting a fidget spinner delivered to your doorstep. Manufacturing the fidget spinner, transporting it across the ocean, storing it in a warehouse, and getting it shipped across the country with 2 day Prime shipping - all of this consumes energy.

I've been doing a deep dive into money - what it is, how it works, history, etc.

Money is taken for granted by most, but it's really the first principle of the economy (and society). Money is the base layer, and everything else is built on top. The base layer / first principle of a complex system is profoundly important and should not be meddled with, because the second, third, and nth order consequences are not predictable.

Well-intentioned changes to the base layer can unexpectedly wreck the entire system.

Some highlights / takeaways / thoughts / comments from #RWRI 14, Day 10:

1. If your metric is not useful during times of crisis, then your metric is simply not useful. Many metrics are some variation of reward divided by risk, where 'risk' can be further broken down as: measured risk divided by hidden risk.

If you increase your hidden risks, it artificially increases your reward to risk ratio.

Some highlights / takeaways / thoughts / comments from #RWRI 14, Day 9:

1. It took us decades to figure out that trans fats were harmful. GMOs can have the same problem.

Just because we don't have evidence of a problem does not mean that there is no problem. 2. When implementing a tail risk hedge strategy (whether in finance or other domains), your goal is to be at a point where you are okay with your worst case scenario.

Some highlights / takeaways / thoughts / comments from #RWRI 14, Day 8:

1. To deal with bad actors in a system, ensure damages to the system will also damage the bad actor.

This is difficult to do in practice, but Bitcoin accomplishes it. The value of Bitcoin is largely based on trust of the system. So if bad actors are able to break the trust of the system, the value of Bitcoin could crater, making the bad actors' heist of Bitcoin lose its value.

Some highlights / takeaways / thoughts / comments from #RWRI 14, Day 7:

1. Just because x is normally distributed does not mean that f(x) is normally distributed. In other words, just because you can predict a specific variable / input for a model does NOT mean that the model itself should be used to forecast.

Some highlights / takeaways / thoughts / comments from #RWRI 14, Day 6:

1. Chaotic systems occur when tiny differences in initial conditions result in wildly different results (e.g. changing a variable from 10 to 10.0001 gives a completely different result). To predict a system like this, you would need infinite precision, which you don't have. These systems are "unpredictable but characterizable," as you can predict the possible states but not where it will be at any given point.

Some highlights / takeaways / thoughts / comments from #RWRI 14, Day 5:

1. Optionality provides you with convexity: you can throw out the bad option and choose a better option. Optionality is worth something, so the whole idea is to avoid paying too much for it. Many times, it isn't priced in at all (e.g. a restaurant reservation that you can cancel for free if you find a better one).

Some highlights / takeaways / thoughts / comments from #RWRI 14, Day 4 (probably my favorite day thus far):

1. If the payout is convex, you don't care about the average; you care about the second order effects. 2. The more optimized a system, the more fragile it is. The tradeoff for more optimization is less redundancy. So when hyper-optimized organizations meet a large stressor, they don't have enough safety margin to survive.

Some highlights / takeaways / thoughts / comments from #RWRI 14, Day 3:

1. Biggest takeaway overall through three days is: "Science isn't about naive evidence, it's about understanding properties." It's pretty easy to run a linear regression on two variables, or develop an algorithm, and call it science. It's very difficult (and sometimes impossible) to deeply understand the properties of the parts of a system and how they interact with each other.

Some highlights / takeaways / thoughts / comments from #RWRI 14, Day 2:

1. There are two major types of distributions: Mediocristan (e.g. height) and Extremistan (e.g. wealth). In Mediocristan, the average of a small sample (n=100 or even n=10) will be reasonably close to the average of the entire population. If you take the average height of 100 people, you won't be too far off the average height of everyone in the world.

Some highlights / takeaways / thoughts / comments from #RWRI14, Day 1:

1. The best indicator of high blowup risk is stability (low volatility). I believe this is because volatility provides us with information. So by reducing volatility, you are missing out on information, and thus accumulating hidden risks that will one day blowup.