Can anyone offer a linguistic explanation for the following phenomenon related to pronoun case and partial determiners:
Theory of programming style incompatibility: it is possible for two or more engineers, each of whom is individually highly skilled, to be utterly incapable of working together productively. In fact, the problem of style incompatibility might actually increase with the skill level of the programmers.
This shouldn't be that surprising: Proust and Hemingway might both be gifted writers capable of producing beautiful novels, but a novel co-authored by the two of them would probably be terrible.
I'm curious about your "system that doesn’t require a strict taxonomy". Is that written up anywhere? Also, does your work have any relevance to how children should be taught grammar in school?
I haven't written it up, though you can see my parser in action here.
One key concept in my system is the Theta Role and the associated rule. A phrase can only have one structure for each role (subject, object, determiner, etc).
I don't have much to say about teaching methods, but I will say that if you're going to teach English grammar, you should know the correct grammatical concepts that actually determine English grammar. My research is an attempt to find the correct concepts. There are some things that I'm confident about and some areas where the system needs work.
One very important aspect of English grammar is argument structure. Different verbs characteristically can and cannot take various types and combinations of arguments, such as direct objects, indirect objects, infinitive complements, and sentential complements. For example, the word "persuade" takes a sentential (that-) complement, but only when also combined with a direct object ("I will persuade [him] that the world is flat" is incorrect without the direct object). In contrast, the verb "know" can take either a direct object or a that-complement, but not both. To speak English fluently, you need to memorize all these combinations, but before you memorize them, you need to know that the concept exists.
Against Phrasal Taxonomy Grammar, an essay about how any approach to grammar theory based on categorizing every phrase in terms of a discrete set of categories is doomed to fail.
TL;DR - A man is searching for a rival to grow together.
Hello everyone!
This comment was inspired by Anti-Lone Wolf and Stronger Together posts.
What I got from these posts is:
1. Anti-Lone Wolf: Trying to go alone, you may miss an important part of motivation.
2. Stronger Together: There is some kind of evidence that group improvement works.
What I got from my research of doing more is:
1. After a myriad of methods and tips tried during 4 years, I remained on the same level - doing things mostly under Panic Monster pressure. I desperately want to change this.
Having a group of people who have their views almost aligned is good, but what if one could add some sort of competition to this?
My current theory is that if two persons have the same goal and similar strategies of pursuing this goal, their competition can benefit each of them.
For example, I heard that while sprinters train on track, they mostly run at least in pairs while going for a record. (I haven't found written proofs of this). This implies, I suppose, that it's easier to get better results when you compete with someone.
The other example - It is recommended to organize startups not alone, but with a co-founder. I assume that in this case, among other benefits, there is a benefit from support while one of founders is lacking motivation.
Based on this, here I am, searching for a person who has the same goal and is on the same stage of reaching this goal, with similar strategy. My characteristics:
Goal: Survive.
Subgoal: Help in solving AI Safety problems.
Strategy: MS in CS/(perhaps ML) in Germany(winter 2018) -> PhD in ML/(perhaps CS) in USA -> work in AIS industry.
Current state: Finished BS in Applied Math, preparing for an application.
Additional info: 21 year, Russian, male, don't smoke/drink.
Afterword:
I apologize if this is the wrong place for such posts. In this case, it would be nice if one gave information about where it's appropriate to post this.
I also apologize if something from this post is naive or too vague. I'm open to any questions and suggestions.
EDIT (4:30, Jul 25 UTC) - It seems that I was wrong about focusing on competition. In games it's easy to tell who is stronger because usually it's the winner. However, there is no strict rules and definitions about winners and losers in real life. Some minor thing later can play a huge role and nobody knows whether it will happen or not.
So instead of "rivals with a bit of partnership" the focus shifts to "partners with a bit of competition". It seems that this idea is very similar to Stronger Together post, just they have a broader goal.
In terms of strategy, I recommend you to think about going to work at the Montreal Institute for Learning Algorithms. They recently received a grant from OpenPhil to do AI Safety Research. I can personally recommend the two professors at McGill (Joelle Pineau and Doina Precup). Since you are Russian, you should be able to handle the cold :-)
Continuing with Adams' theme of congratulating himself on making correct predictions, I'll point out that I correctly predicted both that Adams did in fact want Trump to win a year ago, and also planned to capitalize on the prediction if it came true, by writing a book:
My guess is that Adams is hoping that Trump wins the election, because he will then write a book about persuasion and how Trump's persuasion skills helped him win. He already has a lot of this material on his blog. In that scenario he can capitalize on his correct prediction, which seemed radical at the time, to generate a lot of publicity for the book.
Both of these claims seem to be confirmed by the podcast. Maybe I should write a book!
Does anyone have good or bad impressions of Calico Labs, Human Longevity, or other hi-tech anti-aging companies? Are they good places to work, are they making progress, etc?
This is a mean vs median or Mediocristan vs Extremistan issue. Most people cannot do lone wolf, but if you can do lone wolf, you will probably be much more successful than the average person.
I cannot disagree with this more strongly. I am serial entrepreneur, and a somewhat successful one. Still chasing the big exit, but I've built successful companies that are still private. Besides myself I've met many other people in this industry which you'd be excused for thinking are lone wolfs. But the truth is the lone wolf's don't make it as they build things that fail to have product/market fit, fail to listen to feedback if and when it is even made available to them (since they don't seek it), and usually fail to raise or maintain funding from lack of communication and organizational skill.
The successful entrepreneurs, hedge funders, etc. are not afraid of thinking that conventional wisdom is wrong. The success they have is not from trailblazing a new path -- that just goes with doing something new -- but from having the tenacity to ask "but why is that so?" of conventional wisdom. Every now and then you find something that just shouldn't be so -- it has no good justification except historical accident -- and then you execute. And a very important part of execution is building a team that can work together to avoid the heuristics and biases that follow lone wolfs around.
Don't be a lone wolf. Be a social rationalist willing to question everything and go where that takes you. It's not the same thing.
I agree with you in the context of entrepreneurship, but the OP was talking about self improvement. The best strategy for learning or self-improving may be very different from the best strategy for building a company.
This is a mean vs median or Mediocristan vs Extremistan issue. Most people cannot do lone wolf, but if you can do lone wolf, you will probably be much more successful than the average person.
Think of it like this. Say you wanted to become a great writer. You could go to university and plod through a major in English literature. That will reliably give you a middling good skill at writing. Or you could drop out and spend all your time reading sci-fi novels, watching anime, and writing fan fiction. Now most people who do that will end up terrible writers. But when someone like Eliezer does it, the results are spectacular.
Furthermore, because of the Power Law and the "Average is Over" idea, most of the impact will come from the standout successes.
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Has anyone studied the Red Black Tree algorithms recently? I've been trying to implement them using my Finite State technique that enables automatic generation of flow diagrams. This has been working well for several other algorithms.
But the Red Black tree rebalancing algorithms seem ridiculously complicated. Here is an image of the deletion process (extracted from this Java code) - it's far more complicated than an algorithm like MergeSort or HeapSort, and that only shows the deletion procedure!
I'm weighing two hypotheses:
I'm leaning toward the latter theory. It seems to me that most of the other "elementary" algorithms of computer science are comparatively simple, so the weird overcomplexity of the tool we use for binary tree balancing is some kind of oversight. Here is the Wiki page on RB trees - notice how the description of the algorithm is extremely hard to understand.