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, Tidman 1984_40ya (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]