I stumbled on this project during my research: food4me.org

The complete mapping of the human genome sequence in 2000 introduced the possibility of individualised medicine, including personalised nutrition.  During this time the field of “nutrigenomics” emerged, which examines the relationship between food and gene expression.  Many were hopeful about the ability to plan diet recommendations based on an individual’s genetic profile.

However, the promise of personalised nutrition has failed to develop as a commercial service, and matching dietary advice to genetic profiles has proven difficult.  Some companies offer genetic mapping and health reports, but these services are often based on inaccurate information.

There is a need to comprehensively analyse the opportunities and challenges in the field of personalised nutrition.  In addition, the fundamental question remains, “how can we best use our current understanding of food, genes, and physical traits to design healthier diets tailored for each individual?”

To address these concerns, Food4Me has gathered an international group of experts to survey the current knowledge of personalised nutrition, and to explore the application of individualised nutrition advice.  The Food4Me project will also investigate consumer attitudes and produce new scientific tools for implementation.

So, transferable skills: skills that, upon improvement, increase your ability in other areas (and also improve other, higher-level skills).

A basic example would be reading/writing. Knowing how to read and write allows one to access a huge amount of other skills and resources which are otherwise unavailable. A less obvious example would be clear speech (enunciation). Ability to speak clearly improves one's prospects in a lot of different areas (e.g. professional advancement, dating, etc.).

I'm looking for additional examples. Which skills did you find to be most transferable? Did you become proficient in X, and then found this helped you in many other areas of your life? Please share.

(I tried to find whether this was discussed before, and failed; if it was, I would appreciate the link.)

What does an memetic infection look like? Well, you would encounter something (probably on the internet) that seems very compelling. You think intensely about it for a while, and it spurs you to do something - probably to post something related on the internet. After a while, the meme may not seem that compelling to you anymore, and you wonder why you invested that time and energy. The meme has reproduced itself. For example, Bruce Sterling's response to the 'New Aesthetic' is a paradigmatic example of memetic infection: he encountered it, he found it compelling, he wrote about it, I read about it and now I know about it. (Note that the word 'infection' has a stigma to it, but I don't mean it to be necessarily a bad thing. I will use 'disease' to mean 'infection with bad consequences'.)

Now, let me jump to an apparently unrelated concept - Viral Eukaryogenesis. If I understand correctly, Viral Eukaryogenesis is the theory that eukaryotes (including you and me) are inheritors of a bargain between two kinds of life - metabolic life and viral life, something like the way lichens are a bargain between fungi and algae. The nucleus that characterizes eukaryotes is supposed to be descended from a virus protein shell, and the membrane-fusion proteins that we use for gamete fusion (crucial for sex) are supposed to be descended from viral infection proteins. I am not a biologist, but my understanding of the state of biology is that it is an interesting hypothesis, as yet neither proven nor disproven. However, I'm going to talk as if it were true, because I'm actually trying to make an analogy with memes.

(If I do anything wrong here, please tell me. I don't know what I'm doing and would benefit from being told what I've got wrong, if anything. I've never made a top-level post here before.)

So, it seems like most people here are really smart. And a lot of us, I'm betting, will have been identified as smart when we were children, and gotten complimented on it a lot. And it's pretty common for that to really mess you up, and then you don't end up reaching your full potential. Admittedly, maybe only people who've gotten past all that read Less Wrong. Maybe I'm the exception. But somehow I doubt that very much.

So here's the only thing I can think of to say if this is your situation: ask stupid questions.

Seriously, even if it shows that you have no clue what was just said. (Especially if it shows that. You don't want to continue not understanding.) You can optimize for being smart, you can optimize for seeming smart, but sometimes you need to pick which one to optimize for. It may make you uncomfortable to admit to not knowing something. It may make you feel like the people around you will stop thinking you're all-knowing. But if you don't know how to ask stupid questions, and you just keep pretending to understand, you'll fall behind and eventually be outed as being really, really stupid, instead of just pretty normal. Which sounds worse?

Here, let me demonstrate: so, what tags go on this post and how would I know?

So, anyone else know of any similar things to do, to get back to optimizing for being smart instead of for seeming smart?

Eliezer Yudkowsky once wrote that

[...] when you look at what Sherlock Holmes does - you can't go out and do it at home.  Sherlock Holmes is not really operating by any sort of reproducible method.  He is operating by magically finding the right clues and carrying out magically correct complicated chains of deduction.  Maybe it's just me, but it seems to me that reading Sherlock Holmes does not inspire you to go and do likewise.  Holmes is a mutant superhero.  And even if you did try to imitate him, it would never work in real life.

A few days ago I was at an acquaintance's house after watching the Sherlock miniseries on Netflix. My mind whirling with the abilities displayed by the titular character and I wandered around the house while others were making small talk. I stopped by a large oil painting on one wall that was decent but had obvious problems with perspective. Additionally, it was missing a signature in the lower-right corner.

ANALYSIS:

Sub-par paintings don't generally get put on the market.

If the hostess thought it was worth putting on the wall, it was most likely because she had an emotional attachment to the piece.

Painters place their signatures in the corner of the painting to identify themselves as the creator. If the painter didn't bother leaving their mark, it was because they were confident that they didn't need to.

The conclusion I drew from this was that the painter was either the hostess herself or somebody very close to her. As it turns out, it was the hostess.

Now, this anecdote hardly proves anything.  Still, I think it's a fun little thing and the ability to show off like that, even a small percentage of the time, is too good to pass up.  So I present my analysis of How to Become a Regular Sherlock Holmes.

1) Pay attention to details. Look around you at your environment.  A scratch on a wall, a limp in somebody's walk, a smudge on somebody's cheek.  At this point it's probably hard to tell what details are important, so pay attention to everything.

2) Answer these two questions:

"What am I looking at?" and

"What could it mean (if anything)?"

3) Check your guesses.

This is an important step. It's easy to make any sort of judgments about the details and what they mean, but if you accept your own conclusions without checking the facts, you're likely to create false assumptions and associations that you take as fact.  That's the opposite of what we're trying to do here.

Fortunately, checking your guesses is very easy to do in most situations with another person. Just state what you've noticed and ask for information on the context.  For example, "I've noticed a large scratch on your end-table. Do you know how it happened?"

A follow-up question might be "why haven't you changed it out for another one?", but only if you think getting the information is more important than the possibility of being seen as rude and the potential consequences thereof.

In Summary:

Pay attention to details

"What am I looking at?"

"What could it mean?"

Check your guesses

Oh, and the painting I mentioned at the beginning? I actually didn't figure it out until she told me. I just about kicked myself when I realized I could have figured it out myself and pulled off a really cool Sherlock Summation if I hadn't asked first. C'est la vie.

What's the best way to get rid of a wart?

How many universes "branch off" from a "quantum event", and in how many of them is the cat dead vs alive, and what about non-50/50 scenarios, and please answer so that a physics dummy can maybe kind of understand?

(Is it just 1 with the live cat and 1 with the dead one?)

Suppose we had a model M that we thought described cannons and cannon balls. M consists of a set of mathematical assertions about cannons, and the hypothesis is that these fully describe cannons in the sense that any question about cannons ("what trajectory do cannon balls follow for certain firing angles?", "Which angle should we pick to hit a certain target?") can be answered by deriving statements from M. Suppose further that M is specified in a certain mathematical system called A, consisting of axioms A1...An.

Now there is much to be said about good ways to find out whether M is true of cannons or not, but consider just this particular (strange) outcome: Suppose we discover that a crucial question about cannons - e.g. Q="Do cannon balls always land on the ground, for all firing angles?" - turned out to be not just un-answerable by our model M but formally independent of the mathematical system A in the sense that the addition of some axiom A0 implies Q, while the addition of its negation, ~A0, implies ~Q.

What would this say about our model for cannons? Let's suppose that we can take Q as a prima facie substantive question with a definitive yes or no answer regardless of any model or axiomatization. At the very least it seems that M must be an incomplete model of cannons if the system in which it is specified is insufficient to answer the various questions of interest. It seems to me that

If a question about reality turns out to be logically independent of a model M, then M is not a complete model of reality.

Now we have an axiomatization of mathematics -- let's say it's ZFC for now -- and we have a model of computation in reality, which is M="The unvierse can contain machines that (efficiently) compute F iff there exists a Turing machine that (efficiently) computes F" with appropriate definitions of what exactly a Turing machine is in terms of ZFC. Suppose we want to answer a question like Q="Can the universe contain machines that efficiently solve SAT?"

Under the premise that M is true, the question Q becomes the pure logical question R="Are there Turing machines that efficiently solve SAT?", i.e. the P versus NP problem.

Now suppose that R was shown to be formally independent of ZFC in the sense that for some axiom A0, ZFC+A0 implies P=NP and ZFC+~A implies P!=NP. This would resolve the mathematical question of P versus NP but the question Q seems like a prima facie concrete question with a definitive yes or no answer that does not rely for its substance on M or ZFC or any other epistemic construct. It would seem that we must have missed something in our description of reality, M.

Perhaps more controversially, I claim: Under the correct model M' it seems that it's impossible for a substantive question (such as Q) to be unanswerable.

All this adds up to: The P versus NP problem (and questions like it that can be phrased as definitive questions about reality) must have an answer unless our model of reality is incomplete.

This is a TED talk about open science. It starts with a description of a new math problem which is offered on a blog, and which eventually attracts enough mathematicians working on it to solve, not just the original problem, but a more difficult version of it. It was enough easier than the usual way of doing math that it was described as being like driving a car instead of pushing it.

Then the speaker talks about more ambitious projects-- like a wiki about quantum computing-- which get started, but no one is actually willing to do the work, so that the wiki lies all but vacant.

He suggests that public science isn't what scientists get paid for nor what builds their careers, and has some ideas for pushing the standards of science to change. There's been at least one success involving publishing genomes.

Perhaps the reason the math project succeeded was because the problem was small enough that success was both well-defined and possible, not to mention that working on it was probably more fun than figuring out how to do tolerable and sensibly-linked wiki articles.

There may be a way to get publicly funded science to be open source. We're already got proof of concept for solving math problems if they're interesting enough, so I suggest going public if you've got a math problem people might like to work on.