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IIRC grapefruit juice also inhibits metabolizing many other compounds; some medications have warnings against consuming grapefruit juice so you don’t build up dangerous levels of the medication in your body. Check for interactions before you try this.
I've been able to buy from the CVS website several times in the past couple months, and even though they're sold out online now, they have some (sparse) in-store availability listed. Worth checking there, Walgreens, etc. periodically.
As a pro Hearthstone player and effective altruist, nicely done! If your son is interested in a free lesson I'd be happy to help him improve his game as a reward for his generosity (though I haven't played arena in a while).
Coursera just started a course called Experimentation for Improvement. Is anyone interested in taking it together?
I buy a lot of berries, and I've heard conflicting opinions on the health risks of organic vs regular berries (and produce in general). My brief Google research seems to indicate that there's little additional risk if any from non-organic prodce, but if anyone knows more about the subject, I'd appreciate some evidence.
This was the first Coursera course I took! Highly recommended, if anyone's still on the fence.
A career question, asked with EA aims in mind, that will hopefully be relevant to many other LW members.
I am considering CS research as a career path, probably in one of AI/ML/distributed systems. I'm currently working as a software developer and I have done extensive MOOC work to pick up a CS background in terms of coursework, but my undergraduate degree is in math and I have no published research.
If I decide that getting a PhD was worthwhile and wanted to apply to good programs, where would I start building my resume and skills? Independent research project? Sufficiently impressive projects within my current company? Should I just get a master's and see how that goes?
Alternately, is it possible to get involved with industry research without a PhD? What would such a career path look like?
Thoughts on any or all of the above questions, suggestions for people to talk to, etc. would be much appreciated.
I'm currently making progress through Information Theory (http://videolectures.net/course_information_theory_pattern_recognition/) and I'm considering trying the upcoming Coursera course on Discrete Optimization (https://www.coursera.org/course/optimization) or the one on scientific computing (https://www.coursera.org/course/scicomp), though I'd prefer the latter. I'm open to studying just about any quantitative topic, though - name a MOOC or subject and ask me if I'm interested.
I am looking into noise reduction options for sleeping - I'm a side sleeper, and the foam insert earplugs I've been using so far are extremely uncomfortable to sleep on. It is surprisingly hard to find a comprehensive guide for this that's not trying to sell you something. Do any of the sleep hackers around here have suggestions?
(If this is more appropriate for the stupid questions thread, let me know.)
That sounds great. I haven't finished the first week's material yet, but I'm planning to tackle it tomorrow, and I assume the difficulty/commitment is comparable to Game Theory 1. I'll message you both with contact info.
I'm still on the fence regarding Network Analysis (though I haven't started the work yet, so that may not longer be an option) and Discrete Optimization - I'd be curious to hear your thoughts on both. I'm currently finishing up Bioinformatics Algorithms I, which also had an extremely high workload, so I'm inclined to lean towards fewer total classes unless I've underestimated how relevant or engaging those particular courses are.
I had the same issue with the Coursera class, but thought it might be tolerable with a partner - this looks much better, though. I'll message you to discuss details.
I'm active on Coursera - currently taking Game Theory II. Other courses that just started but look interesting include Cryptography, Computational Molecular Evolution, and Information Theory. I'm up to try one of those or any other quantitative course that looks interesting with a study partner.
Also, I have a decent background in data science/machine learning through Coursera courses but not much practical experience. If anyone wants to partner for either a competition (something like Kaggle) or to analyze a real data set, I'd be happy to work on that.
I've been using a similar tactic lately. When an ugh field is blocking some important task, I'll explicitly ask myself "if I actually wanted to solve this problem, what would I do?" That seems to immediately generate enough emotional distance that I can come up with a more granular plan like the one you described.
Do you use any quantitative self tools for this? If so, could you elaborate on your data tracking/analysis processes?
Could you talk about your graduate work in AI? Also, out of curiosity, did you weight possible contribution towards a positive singularity heavily in choosing your subfield/projects?
(I am trying to figure out whether it would be productive for me to become familiar with AI in mainstream academia and/or apply for PhD programs eventually.)