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Complexity no Bar to AI - Gwern.net
Critics of AI risk suggest diminishing returns to computing (formalized asymptotically) means AI will be weak; this argument relies on a large number of questionable premises and ignoring additional resources, constant factors, and nonlinear returns to small intelligence advantages, and is highly unlikely. (computer science, transhumanism, AI, R)
created: 1 June 2014; modified: 01 Feb 2018; status: finished; confidence: likely; importance: 10
ratty  gwern  analysis  faq  ai  risk  speedometer  intelligence  futurism  cs  computation  complexity  tcs  linear-algebra  nonlinearity  convexity-curvature  average-case  adversarial  article  time-complexity  singularity  iteration-recursion  magnitude  multiplicative  lower-bounds  no-go  performance  hardware  humanity  psychology  cog-psych  psychometrics  iq  distribution  moments  complement-substitute  hanson  ems  enhancement  parable  detail-architecture  universalism-particularism  neuro  ai-control  environment  climate-change  threat-modeling  security  theory-practice  hacker  academia  realness  crypto  rigorous-crypto  usa  government 
april 2018 by nhaliday
Open Thread, 11/26/2017 – Gene Expression
A few days ago there was a Twitter thing about top five books that have influenced you. It’s hard for me to name five, but I put three books down for three different reasons:

- Principles of Population Genetics, because it gives you a model for how to analyze and understand evolutionary processes. There are other books out there besides Principles of Population Genetics. But if you buy this book you don’t need to buy another (at SMBE this year I confused Andy Clark with Mike Lynch for a second when introducing myself. #awkward)
- The Fall of Rome. A lot of historical writing can be tendentious. I’ve also noticed an unfortunate tendency of historians dropping into contemporary arguments and pretty much lying through omission or elision to support their political side (it usually goes “actually, I’m a specialist in this topic and my side is 100% correct because of obscure-stuff where I’m shading the facts”). The Fall of Rome illustrates the solidity that an archaeological and materialist take can give the field. This sort of materialism isn’t the final word, but it needs to be the start of the conversation.
- From Dawn to Decadence: 1500 to the Present: 500 Years of Western Cultural Life. To know things is important in and of itself. My own personal experience is that the returns to knowing things in a particular domain or area do not exhibit a linear return. Rather, it exhibits a logistic curve. Initially, it’s hard to make sense of anything from the facts, but at some point comprehension and insight increase rapidly, until you reach the plateau of diminishing marginal returns.

If you haven’t, I recommend you subscribe to Patrick Wyman’s Tides of History podcast. I pretty much wait now for every new episode.
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november 2017 by nhaliday
Subgradients - S. Boyd and L. Vandenberghe
If f is convex and x ∈ int dom f, then ∂f(x) is nonempty and bounded. To establish that ∂f(x) ≠ ∅, we apply the supporting hyperplane theorem to the convex set epi f at the boundary point (x, f(x)), ...
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august 2017 by nhaliday
Stages of Diversification
This paper studies the evolution of sectoral concentration in relation to the level of per capita income. We show that various measures of sectoral concentration follow a U-shaped pattern across a wide variety of data sources: countries first diversify, in the sense that economic activity is spread more equally across sectors, but there exists, relatively late in the development process, a point at which they start specializing again. We discuss this finding in light of existing theories of trade and growth, which generally predict a monotonic relationship between income and diversification. (JEL F43, F15, O40)

seems unhealthy to me (complacency)
pdf  study  economics  growth-econ  stylized-facts  correlation  curvature  wealth  wealth-of-nations  distribution  trade  heavy-industry  🎩  group-level  regional-scatter-plots  longitudinal  the-world-is-just-atoms  econ-metrics  econometrics  broad-econ  diversity  entropy-like  nonlinearity  convexity-curvature 
june 2017 by nhaliday
There Is No Such Thing as Decreasing Returns to Scale — Confessions of a Supply-Side Liberal
Besides pedagogical inertia—enforced to some extent by textbook publishers—I am not quite sure what motivates the devotion in so many economics curricula to U-shaped average cost curves. Let me make one guess: there is a desire to explain why firms are the size they are rather than larger or smaller. To my mind, such an explanation should proceed in one of three ways, appropriate to three different situations.
econotariat  economics  micro  plots  scale  marginal  industrial-org  business  econ-productivity  efficiency  cost-benefit  explanation  critique  clarity  intricacy  curvature  convexity-curvature  nonlinearity  input-output 
may 2017 by nhaliday
Estimating the number of unseen variants in the human genome
To find all common variants (frequency at least 1%) the number of individuals that need to be sequenced is small (∼350) and does not differ much among the different populations; our data show that, subject to sequence accuracy, the 1000 Genomes Project is likely to find most of these common variants and a high proportion of the rarer ones (frequency between 0.1 and 1%). The data reveal a rule of diminishing returns: a small number of individuals (∼150) is sufficient to identify 80% of variants with a frequency of at least 0.1%, while a much larger number (> 3,000 individuals) is necessary to find all of those variants.

A map of human genome variation from population-scale sequencing: http://www.internationalgenome.org/sites/1000genomes.org/files/docs/nature09534.pdf

Scientists using data from the 1000 Genomes Project, which sequenced one thousand individuals from 26 human populations, found that "a typical [individual] genome differs from the reference human genome at 4.1 million to 5.0 million sites … affecting 20 million bases of sequence."[11] Nearly all (>99.9%) of these sites are small differences, either single nucleotide polymorphisms or brief insertion-deletions in the genetic sequence, but structural variations account for a greater number of base-pairs than the SNPs and indels.[11]

Human genetic variation: https://en.wikipedia.org/wiki/Human_genetic_variation

Singleton Variants Dominate the Genetic Architecture of Human Gene Expression: https://www.biorxiv.org/content/early/2017/12/15/219238
study  sapiens  genetics  genomics  population-genetics  bioinformatics  data  prediction  cost-benefit  scale  scaling-up  org:nat  QTL  methodology  multi  pdf  curvature  convexity-curvature  nonlinearity  measurement  magnitude  🌞  distribution  missing-heritability  pop-structure  genetic-load  mutation  wiki  reference  article  structure  bio  preprint  biodet  variance-components  nibble  chart 
may 2017 by nhaliday
Concentration and Growth | Dietrich Vollrath
Ultimately, and this is my impression, not some kind of established fact, concentration likely lowers innovative activity. Put it this way, the null hypothesis should probably be that concentration lowers innovation. An individual industry needs to provide evidence they are on the “right side of the curve” in the first AAH figure to believe concentration would be good for productivity growth in the long run.
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may 2017 by nhaliday

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