I don't think the Hamming advice is so great. It's akin to asking, "What are the highest salary professions? Why aren't you entering them?".

Academia is a market-place. Everyone wants high research impact, for a given expenditure of time. Some opportunities are higher-value than others, but as those opportunities appear, other researchers are going to identify them too.

So in academia, as in the economy, it's better to identify your comparative advantage --- both short-term, and long-term. You usually need to publish something quickly, so you need to know what you can do right away. But you also want to plan for the medium and long-term, too. It's a difficult trade-off.

I've had 6 years of formal spanish classes. When I speak spanish, I need to think of the phrase in english, and then translate each word to spanish, and it's all very awkward with no real fluency or soul. My accent is good, but I think that's just because the Spanish phenomes which are not present in English are present in Hindi.

I've had sporadic contact with Hindi via family members and movies. My Hindi is just as bad as my Spanish in terms of raw communicative power...but the nature of my knowledge is different. I can spontaneously and naturally say entire phrases with all the proper communicative cues (changes in pitch, expression) without any English in my mind. And I can directly understand the meaning of Hindi speech, whereas with Spanish I need to map it to English before grasping meaning.

So, if I said one sentence in Spanish, a Spanish speaker can immediately tell I'm not a native speaker. If I say one sentence in Hindu, for that one sentence I'm reported to sound exactly like a native speaker (but there is very little I can actually say, so I essentially sound like a child who has been speaking sentences for about 6 months. (People find it hilarious)).

So while I can communicate roughly equally poorly in both languages in a pinch, I can do more "natural" stuff like create/appreciate humor in Hindi, which I can never pull off in Spanish.

Given that experience, here are my suggestions:

Immersion substitution: Take a movie which you have seen the English version many times, and watch it in Hebrew. When an unfamiliar phrase appears, pause the movie, say the phrase, and try to figure out what it means (using the dictionary as a last resort). Once you get to the point where you can completely understand one movie in Hebrew, move on to another movie. (Side effects may include: Use of overly dramatic or poetic language in daily talk. This goes double from phrases which you learned from musical pieces). Unless you're totally at a loss, I'd suggest leaving any English subtitles off.

Repeat the phrases aloud. Don't be afraid to babble unfamiliar syllables like a baby. Whenever I go to India, I get a powerful instinctive urge to start babbling, saying random phrases, and repeating what people around me say. This draws weird looks, so I do it under my breathe, but I think it really helps/

Do not mentally translate from one language to another. Try to grab the meaning directly from the words, without going en-route to English. That is, as you think of the phrase, try to not activate the equivalent word in a language you already know, and instead try to strongly activate a non-verbal representation of the concept.

For example, if הַשְּׁקִיעָה means "sunset"...but literally means "the setting", then mentally envision a far-away object going downwards over the horizon. The english word "Sunset" most strongly brings to mind a warm orange glow because of the word sun, but "the setting" may well have a very different connotation to a Hebrew speaker, and might emphasize different aspects (the downward motion, the fact that it's now time to go inside and relax, etc). These small differences will become apparent from taking into consideration the literal translation, the figurative translation, and the context. Actively not translating will help these come clearer, because instead of just memorizing "sunset" you would focus on how close the word is to "שקיעה" (to sink), which you would have previously associated with downwards motions.

To the extent possible, try to do the same when speaking (it's harder because it can be a bit difficult to think in a communicative way without the aid of a language, but it will sound more natural in the end.)

Talk to yourself try to have an internal monologue in the target language, except move your mouth along with it. Movie-immersion is only listening...you need to simulate speaking immersion too, or you'll end up being able to understand but not speak (this has happened to me to some extent with Hindi).

I can't read Hindi, but I felt that reading written Spanish aloud made for a decent "immersion" substitute (in terms of how much I subjectively felt myself learning). You might be able to do that with hebrew if you've got the graphy-phenome mapping down. Writing spanish was much less helpful for me...the slower pace of the writing process had me instinctively using the time to apply the "rules" I had learned rather than doing it instinctively.

(Remember the fact that I can't speak Spanish or Hindi well enough to survive on my own in an immersed environment, when weighing my opinion)

I have been tossing around the idea of not-high-IQ rationalist fiction. Problem is, it's really hard to write. If they act rationally, people stop identifying the person as unintelligent. You get intelligence creep or an unsatisfying story.

The best route I can see is to make them well-substandard in intelligence. Rationalist!Forrest Gump, say.

ETA: Another problem is that adventures are usually sub-optimal. No one writes about the Amundsen expedition or equivalents (*) - they write about Scott expeditions.

*(except for Le Guin, who managed it because she's amazing)

He also likes arguing with Jeff Kaufman about effective altruism.

I'm not sure that he doesn't have "natural" skill or talent. I find the link now but I remember reading that he's extremely high IQ. (or something something eidetic memory something something?)

Motifs in his standup comedy routines are about how much smarter he is than everyone else, etc etc (anecdata)

Something that's always bugged me about being an academic is, we're terrible at communicating to people outside our field. This means that whenever I see a post using an NLP tool, they're using a crap tool.

Why is that, do you think? This doesn't seem to be the case in the ML community as far as I can judge (though I'm not an expert). What's special about NLP? What prevents the nltk people from doing what you did?

I'm currently a post-doc doing language technology/NLP type stuff. I'm considering quitting soon to work full time on a start-up. I'm working on three things at the moment.

• The start-up is a language learning web app: http://www.cloze.it . What sets it apart from other language-learning software is my knowledge of linguistics, proficiency with text processing, and willingness to code detailed language-specific features. Most tools want to be as language neutral as possible, which limits their scope a lot. So they tend to all have the same set of features, centred around learning basic vocab.

• Something that's always bugged me about being an academic is, we're terrible at communicating to people outside our field. This means that whenever I see a post using an NLP tool, they're using a crap tool. So I wrote a blog post explaining a simple POS tagger that was better than the stuff in e.g. nltk (nltk is crap): http://honnibal.wordpress.com/2013/09/11/a-good-part-of-speechpos-tagger-in-about-200-lines-of-python/ The POS tagger post has gotten over 15k views (mostly from reddit), so I'm writing a follow up about a concise parser implementation. The parser is 500 lines, including the tagger, and faster and more accurate than the Stanford parser (the Stanford parser is also crap).

• I'm doing minor revisions for a journal article on parsing conversational speech transcripts, and detecting disfluent words. The system gets good results when run on text transcripts. The goal is to allow speech recognition systems to produce better transcripts, with punctuation added, and stutters etc removed. I'm also working on a follow up paper to that one, with further experiments.

Overall the research is going well, and I find it very engaging. But I'm at the point where I have to start writing grant applications, and selling software seems like a much better expected-value bet.

Yes I agree, there is only a rough isomorphism between the mathematics of binary logic and the real world; binary logic seems to describe a limit that reality approaches but never reaches.

We should consider that the mathematics of binary logic are the limiting case of probability theory; it is probability theory where the probabilities may only take the values of 0 or 1. Probability theory can do everything that logic can but it can also handle those real world cases where the probability of knowing something is something other than 0 or 1, as is the usual case with scientific knowledge.

Interesting discussion but I suspect an important distinction may be required between logic and probability theory. Logic is a special case of probability theory where values are restricted to only 0 and 1, that is to 0% and 100% probability. Within logic you may arrive at certain conclusions but generally within probability theory conclusions are not certain but rather assigned a degree of plausibility.

If logic provides, in some contexts, a valid method of reasoning then conclusions arrived at will be either 0% or 100% true. Denying that 100% confidence is ever rational seems to be equivalent to denying that logic ever applies to anything.

It is certainly true that many phenomena are better described by probability than by logic but can we deny logic any validity. I understand mathematical proofs as being within the realm of logic where things may often be determined as being either true or false. For instance Euclid is credited with first proving that there is no largest prime. I believe most mathematicians accept this as a true statement and that most would agree that 53 is easily proven to be prime.