Links

AI:

• Mat­ters Of Scale:

  • The Bit­ter Les­son: “Accu­racy and Per­for­mance Com­par­i­son of Video Action Recog­ni­tion Approaches”, Hutchin­son et al 2020 (sim­ple large 2D CNNs per­formed best when com­pared under con­trolled con­di­tion­s); “A Met­ric Learn­ing Real­ity Check”, Mus­grave et al 2020 (the dou­bling of met­ric learn­ing per­for­mance since 2006 appears almost entirely due to larger neural nets + more com­pute used in train­ing, not fancy loss functions/theory)
  • “Self­-su­per­vised learn­ing through the eyes of a child”, Orhan et al 2020 (dataset; it’d be fun to see this used for rats or dogs)
  • “The remark­able, yet not extra­or­di­nary, human brain as a scaled-up pri­mate brain and its asso­ci­ated cost”, Her­cu­lano-Houzel 2012
  • “The Node Is Non­sense: There are bet­ter ways to mea­sure progress than the old Moore’s law met­ric”, Moore 2020
  • “Mea­sur­ing hard­ware over­hang”, hippke (“with today’s algo­rithms, com­put­ers would have beat the world chess cham­pion already in 1994 on a con­tem­po­rary desk com­puter”)

Genet­ics:

• Every­thing Is Her­i­ta­ble:

  • “Sib­ling val­i­da­tion of poly­genic risk scores and com­plex trait pre­dic­tion”, Lello et al 2020
  • “Poly­genic Scores for Cog­ni­tive Abil­i­ties and their Asso­ci­a­tion with Differ­ent Aspects of Gen­eral Intel­li­gence—a Deep Phe­no­typ­ing Approach”, Genç et al 2020
  • “Genetic test­ing of dogs pre­dicts prob­lem behav­iors in clin­i­cal and non­clin­i­cal sam­ples”, Zap­ata et al 2020 (pre­vi­ous­ly: MacLean et al 2019)

Statistics/meta-science/mathematics:

• “Object­ing to exper­i­ments even while approv­ing of the poli­cies or treat­ments they com­pare”, Heck et al 2020

Psychology/biology:

• “Epi­ge­netic clocks: A review”, José Luis 2020; “TRIIM: Rever­sal of epi­ge­netic aging and immunose­nes­cent trends in humans”, Fahy et al 2019; “Rever­sal of Epi­ge­netic Age with Diet and Lifestyle in a Pilot Ran­dom­ized Clin­i­cal Trial”, Fitzger­ald et al 2020

• “The quest to slow age­ing through drug dis­cov­ery”, Par­tridge et al 2020

• “Atrib­ac­te­ria repro­duc­ing over mil­lions of years in the Atlantic abyssal sub­seafloor”, Vuillemin et al 2020

• “Explor­ing the per­some: The power of the item in under­stand­ing per­son­al­ity struc­ture”, Rev­elle et al 2020 (“every­thing is cor­re­lated”)

• How Com­pe­tent Are Humans?

  • “Bet­ter All the Time: How the “per­for­mance rev­o­lu­tion” came to ath­let­ic­s—and beyond"; “Per­sonal Best: Top ath­letes and singers have coach­es. Should you?”
  • “Does Man­age­ment Mat­ter? Evi­dence from India”, Bloom et al 2012; “The Impact of Con­sult­ing Ser­vices on Small and Medium Enter­pris­es: Evi­dence from a Ran­dom­ized Trial in Mex­ico”, Bruhn et al 2018
  • “95%-ile isn’t that good”, Dan Luu (per­sis­tent incom­pe­tence in Over­watch play­ers)
  • “Worker Rush: Descent to Bronze”, Gheed 2011 (and in Star­craft play­ers)
  • “Play­ing to Win”, Sir­lin 2006

• “The Scent of the Nile: Jean-Claude Ellena cre­ates a new per­fume”, Chan­dler Burr 2005

Tech­nol­o­gy:

• Your Com­puter Is Really Fast:

  • “There’s plenty of room at the Top: What will drive com­puter per­for­mance after Moore’s law?”, Leis­er­son et al 2020 (gains from end-to-end sys­tems design; AI scal­ing can con­tinue even if semi­con­duc­tors do not, par­tic­u­larly with self­-op­ti­miz­ing stacks; John Car­mack notes, apro­pos of Sey­mour Cray, that “Hyper­scale data cen­ters and even national super­com­put­ers are loosely cou­pled things today, but if chal­lenges demanded it, there is a world with a zetta[flops] scale, tightly inte­grat­ed, low latency matrix dis­si­pat­ing a gigawatt in a swim­ming pool of cir­cu­lat­ing flu­o­rinert.”)
  • “Scal­a­bil­i­ty! But at what COST?”, McSh­erry et al 2015 (when lap­tops > clus­ters: the impor­tance of good base­li­nes)
  • “You’re Doing It Wrong: Think you’ve mas­tered the art of server per­for­mance? Think again.”, Poul-Hen­ning Kamp 2010 (on using cache-obliv­i­ous B-heaps to opti­mize Var­nish per­for­mance 10×)
  • “Sam­ple Fac­to­ry: Ego­cen­tric 3D Con­trol from Pix­els at 100,000 FPS with Asyn­chro­nous Rein­force­ment Learn­ing”, Petrenko et al 2020
  • “What Every Pro­gram­mer Should Know About Mem­ory”, Drep­per 2007
  • “What it takes to run Stack Over­flow”, Nick Craver
  • see pre­vi­ously on latency/UI: “It’s the Laten­cy, Stu­pid.”/“Com­puter laten­cy: 1977–2017”/“Key­board Latency”/“Ter­mi­nal Latency”/“Local-first soft­ware: You own your data, in spite of the cloud”/Klepp­mann et al 2019/“Web Bloat”

• “Fälschungser­schw­erende Schrift (forgery-im­ped­ing type­face)”

• “Inuk­shuk: Cari­bou Drive Lanes on South­ern Vic­to­ria Island, Nunavut, Canada”, Brink 2005

• “The case of the bar­na­cled crys­tal”, Kohman 1950 (on dis­ap­pear­ing poly­morphs)

Eco­nom­ics:

• “Mov­ing off the Map: How Knowl­edge of Orga­ni­za­tional Oper­a­tions Empow­ers and Alien­ates”, Huis­ing 2019 (“The CEO, after being walked through the map, sat down, put his head on the table, and said, ‘This is even more fucked up than I imag­ined.’”)
• “The Age of Rea­son: Finan­cial Deci­sions over the Life-Cy­cle with Impli­ca­tions for Reg­u­la­tion”, Agar­wal et al 2009

Fic­tion:

• “An Auto­bi­o­graph­i­cal Essay”, Jorge Luis Borges 1971
• “Sin­gu­lar: Pos­si­ble futures of the sin­gu­lar­ity”, James Yu & GPT-3

Misc:

• List of games the Bud­dha would not play

Music

Touhou:

• “Moon­bow” (Kirin feat. Chata; Sprout Inten­tion {C88}) [trance]
• “Har­vester’s Dance” (Ganemes; Sis­ter’s 3 {TK12}) [folk]