Links

Genetics:

• Everything Is Heritable:

  • “Genome-wide study identifies 611 loci associated with risk tolerance and risky behaviors”⁠, Linner et al 2018

  • “DeepGS: Predicting phenotypes from genotypes using Deep Learning”⁠, Ma et al 2017 (rrBLUP is one of the best generic methods if you’re working with relatively small n/p GWAS⁠ data, and this is not a setup or design that favors CNNs⁠: single trait w/no auxiliary data, tiny n/p, shallow CNN, no hyperparameter or architecture optimization or data augmentation—but the crippled CNN still beats rr-BLUP. What would happen if one did a full-strength CNN GWAS across the UKBB⁠? The memory and computation requirements would be exorbitant, but one can dream.)

  • “2017 was the year consumer DNA testing blew up”⁠ (“More people took genetic ancestry tests last year than in all previous years, combined. The number of people who have had their DNA analyzed with direct-to-consumer genetic genealogy tests more than doubled during 2017 and now exceeds 12 million, according to industry estimates.”)

  • ⁠“Whose poop is that on the lawn? DNA testing is cracking down on doggie-doo offenders” (unexpected consequences of exponential decreases in DNA testing costs)

• Recent Evolution:

  • “Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection”⁠, Pardiñas et al 2018 (‘Background selection’⁠ as the mechanism driving all the human mutation load⁠ in common schizophrenia variants? Could this also explain other traits like intelligence?)

• Engineering:

  • “Metaphase II oocytes from human unilaminar follicles grown in a multi-step culture system”⁠, McLaughlin et al 2018 (⁠media⁠; steps towards massive embryo selection & IES)

AI:

• “DAML: One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning”⁠, Yu et al 2018 (⁠video⁠)

• “Unicorn: Continual Learning with a Universal, Off-policy Agent”⁠, Mankowitz et al 2018; “IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures”⁠, Espeholt et al 2018 (⁠blog⁠; Real transfer learning, and even more wallclock speedups/parallel scaling, on ALE)

• “Learning and Querying Fast Generative Models for Reinforcement Learning”⁠, Buesing et al 2018 (Learning deep environment models for planning)

• ⁠“Deep Reinforcement Learning Doesn’t Work Yet”⁠, Alex Irpan

• “Machine Theory of Mind”⁠, Rabinowitz et al 2018

• “ENAS: Efficient Neural Architecture Search via Parameter Sharing”⁠, Pham et al 2018

• “One Big Net for Everything”⁠, Schmidhuber2018 (An update on ⁠NNAISENSE⁠? Or still just proposals like Schmidhuber2015⁠?)

• ⁠Holden Karnofsky & Robert Wiblin podcast discussing Open Philanthropy’s approach to AI safety (transcript)⁠

Statistics/Meta-Science:

• “Statistical power of clinical trials has increased whilst effect size remained stable: an empirical analysis of 137,032 clinical trials between 1975^–₄₂2017”⁠, Lamberink et al 2017 (Medical experiments are still usually grossly underpowered but things seem to be getting a little bit better.)

Politics/religion:

• ⁠“The Impact of Media Censorship: Evidence from a Randomized Field Experiment in China”⁠, Chen & Yang2018

• ⁠“What Really Happened At The School Where Every Graduate Got Into College”⁠ (The Stainless Steel Law of Evaluation⁠: “The better designed the impact assessment of a social program, the more likely is the resulting estimate of net impact to be zero.”)

Psychology/biology:

• “Deep image reconstruction from human brain activity”⁠, Shen et al 2018a; “End-to-end deep image reconstruction from human brain activity”⁠, Shen et al 2018b

• ⁠“Investigating the right tail of wealth: Education, cognitive ability, giving, network power, gender, ethnicity, leadership, and other characteristics”⁠, Wai & Lincoln2018

• “Adversarial Examples that Fool both Human and Computer Vision”⁠, Elsayed et al 2018 (it’s a start)

• “It’s a Dog’s World, Especially in the Lab. Where Are the Cats?”⁠ (particularly in my catnip⁠ research, I’ve noticed a lamentable lack of cat research.)

Technology:

• “Augur: a Decentralized Oracle and Prediction Market Platform”⁠, Peterson et al 2018 (If you last read the original Augur/Truthcoin whitepapers back in ~2014, the mechanism design has changed radically so may be worth reading the latest whitepaper.)

• The Alinea Project (I’m awed by the depth of this guy’s foray into doing “modernist cuisine”⁠ at home and replicating every single Alinea⁠ recipe published in Alinea, with impeccable photographic documentation.)

Economics:

• ⁠“Effects Of Copyrights On Science—Evidence From The US Book Republication Program”⁠, Biasi & Moser2018 (Estimating the large deadweight⁠ losses of copyright using the natural experiment⁠ of US expropriation of German copyrights in WWII)

• “The Robots Are Coming for Garment Workers”⁠ (Automation comes to the last few steps in the clothes-making process. Reminds me of Hanson’s model⁠ of how automation/tech/capital initially serves as a complement to labor, making labor ever better off, but then at a sufficient point of development, flips over to being a substitute for labor.)

• “Inside North Korea’s Hacker Army”⁠

• “Are We Running Out of Trademarks? An Empirical Study of Trademark Depletion and Congestion”, Beebe & Frommer2018

Books

Nonfiction:

• ⁠The Operations Evaluation Group: A History of Naval Operations Analysis⁠, Tidman1984 (⁠review⁠)

Film/TV

Live-action:

• AlphaGo⁠ (⁠review⁠)

Music

Touhou:

• ⁠“A LA MODE”⁠ (Attrielectrock feat. こばきょん; du Cafe’ tre {C83}) [jazz/vocal]

• ⁠“your heart, your smile”⁠ (Attrielectrock; du Cafe’ tre {C83}) [jazz/instrumental rock]

• ⁠“LES TOILES”⁠ (Attrielectrock; du Cafe’ tre {C83}) [jazz]

• ⁠“DU SOLEIL”⁠ (Attrielectrock; du Cafe’ tre {C83}) [jazz]

Doujin:

• ⁠“凍る花”⁠ (bermei.inazawa feat. YURiCa; ERiCa {2016}) [vocal]

Vocaloid:

• ⁠“alta mugs”⁠ (FukukawaP; Miku; alta mugs E.P. {VM15}) [trance]

• ⁠“Open Your Lights”⁠ (BIGHEAD; Miku; RELOVE [Deluxe Edition] {C91}) [trance]