Links

Genetics:

• Recent Evolution:

  • dysgenics: “Genome-wide analysis identifies 12 loci influencing human reproductive behavior”, Barban et al 2016 (supplement; genetic correlations with fewer later offspring: r_g = -0.236 and 0.712 respectively. Cross-sectional confirmation of Conley et al 2016’s discovery of longitudinal dysgenics.)
  • “A time transect of exomes from a Native American population before and after European contact”, Lindo et al 2016 (Rapid soft selection sweeps on immune-system genes post-colonization. Presumably ancient genomes would show even more dramatic population collapses & selection in South/Central America.)
  • “Kinship, Fractionalization and Corruption”, Akbari et al 2019
  • “CRISPR gene-editing tested in a person for the first time”

• Everything Is Heritable

  • “Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders”, Weiner et al 2016
  • “Genome-Wide Association Study Reveals First Locus for Anorexia Nervosa and Metabolic Correlations”, Duncan et al 2016 (see also “The Thin Gene”)
  • “Lung cancer, genetic predisposition and smoking: the Nordic Twin Study of Cancer”, Hjelmborg et al 2016 (R.A. Fisher would be pleased to see that someone’s finally checked.)

AI:

• “Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes”, Rae et al 2016

• “Neural architecture search with reinforcement learning”, Zoph & Le 2016 (800 GPUs!)

• “Designing Neural Network Architectures using Reinforcement Learning”, Baker et al 2016

• “Learning to reinforcement learn”, Wang et al 2016

• human-level lipreading (human-level lipreading + MSR’s transcription + Google’s WaveNet could have major implications for the deaf & hard-of-hearing and the role of sign language):

  • “Lip Reading Sentences in the Wild”, Chung et al 2016 (vide)
  • “LipNet: Sentence-level Lipreading”, Assael et al 2016 (video)

• “Tracking the World State with Recurrent Entity Networks”, Henaff et al 2016

• “DeepCoder: Learning to Write Programs”, Balog et al 2016; “Learning to superoptimize programs”, Bunel et al 2016; DeepMath/“HolStep: A Machine Learning Dataset for Higher-order Logic Theorem Proving”, Kaliszyk et al 2016 (continuing the AlphaGo theme of tree search+NN heuristics; see also “Deep Learning for Real-Time Atari Game Play Using Offline Monte Carlo Tree Search [MCTS] Planning”, Guo et al 2014)

• “Reinforcement Learning with Unsupervised Auxiliary Tasks”, Jaderberg et al 2016

• “Outrageously large neural networks: the sparsely-gated mixture-of-experts layer”, Shazeer et al 2016 (This is cool. The main net is a little NN which chooses a couple out of a few thousand other NNs to do the real computation. Because only a couple subnets are activated at any time and the others are silent, they are effectively small specialized NNs—which accordingly fit in the GPU and are very fast forwards/backwards. Instead of the complications of learning to use an external memory, huge datasets can effectively be sharded & memorized by individual specialized sub NNs.)

• “Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation”, Johnson et al 2016; “Found in translation: More accurate, fluent sentences in Google Translate” (the long-awaited high quality translation RNNs finally get rolled out to the masses)

• “Image-to-Image Translation with Conditional Adversarial Nets”, Isola et al 2016 (as has often been noted, mapping images to images is a very common type of operation, and there’s no real reason to have a whole menagerie of DCGANs for upscaling and colorizing and inpainting and…)

• “DeepMind and Blizzard to release StarCraft II as an AI research environment”

• “Decoding The Thought Vector”

• “miles-deep: Deep Learning Porn Video Classifier/Editor with Caffe”

Statistics/meta-science/mathematics:

• “Why a pro/con list is 75% as good as your fancy machine learning algorithm”

Politics/religion:

• “History is Written by the Losers”

Psychology/biology:

• “Neural correlates of specific musical anhedonia”, Martínez-Molina et al 2016

Technology:

• “‘It smelled like death’: An oral history of the Double Dare obstacle course”

Fiction:

• “Design”, Robert Frost

Film/TV

Live-action:

• Doctor Strange (Marvel action movie featuring Benedict Cumberbatch. Cumberbatch is always great fun to watch be superior to other people. Much of the plot is fairly perfunctory like the standard kung-fu-training-in-Tibet + Hollywood Buddhism trope, and the real fun is not the awkward martial arts but the space-warping mechanic employed in most of the fighting: it is a fascinating special effect, used much more extensively than the ‘city warping’ in Inception, and I really enjoyed watching those scenes. The finale offers an equally memorable use of a time-rewinding effect and a nice if somewhat simple resolution using time loops. Oddly, Arrival also relies on time loops for its resolution, so both movies I watched in November used that plot device. Doctor Strange doesn’t take time manipulation to nearly the heights of Braid or Primer, and only stands out in memory for the cityscape warping, but I was able to enjoy the movie for what it was.)
• _Five Element Ninjas (good stupid fun; each fight is more ridiculous than the last)
• Arrival (see my review of Stories of Your Life and Others)

Music

Touhou:

• “二人のエンドレス秘封活動” (MasamiT; ゴツまさ倶楽部 {C79}) [folk]

Doujin:

• “美しくも醜いのなら” (君の音。; 少女の海から {M3-2016}) [classical]
• “DEEP FOREST” (Kirin feat.Sarii Yoshida; Altar Fragments {C90}) [electronic]
• “INFINITY” (Kokuchou feat. Misa Kikouden; Altar Fragments {C90}) [electronic]