acmtariat   236

« earlier    

Surveil things, not people – The sideways view
Technology may reach a point where free use of one person’s share of humanity’s resources is enough to easily destroy the world. I think society needs to make significant changes to cope with that scenario.

Mass surveillance is a natural response, and sometimes people think of it as the only response. I find mass surveillance pretty unappealing, but I think we can capture almost all of the value by surveilling things rather than surveilling people. This approach avoids some of the worst problems of mass surveillance; while it still has unattractive features it’s my favorite option so far.

...

The idea
We’ll choose a set of artifacts to surveil and restrict. I’ll call these heavy technology and everything else light technology. Our goal is to restrict as few things as possible, but we want to make sure that someone can’t cause unacceptable destruction with only light technology. By default something is light technology if it can be easily acquired by an individual or small group in 2017, and heavy technology otherwise (though we may need to make some exceptions, e.g. certain biological materials or equipment).

Heavy technology is subject to two rules:

1. You can’t use heavy technology in a way that is unacceptably destructive.
2. You can’t use heavy technology to undermine the machinery that enforces these two rules.

To enforce these rules, all heavy technology is under surveillance, and is situated such that it cannot be unilaterally used by any individual or small group. That is, individuals can own heavy technology, but they cannot have unmonitored physical access to that technology.

...

This proposal does give states a de facto monopoly on heavy technology, and would eventually make armed resistance totally impossible. But it’s already the case that states have a massive advantage in armed conflict, and it seems almost inevitable that progress in AI will make this advantage larger (and enable states to do much more with it). Realistically I’m not convinced this proposal makes things much worse than the default.

This proposal definitely expands regulators’ nominal authority and seems prone to abuses. But amongst candidates for handling a future with cheap and destructive dual-use technology, I feel this is the best of many bad options with respect to the potential for abuse.
ratty  acmtariat  clever-rats  risk  existence  futurism  technology  policy  alt-inst  proposal  government  intel  authoritarianism  orwellian  tricks  leviathan  security  civilization  ai  ai-control  arms  defense  cybernetics  institutions  law  unintended-consequences  civil-liberty  volo-avolo  power  constraint-satisfaction  alignment 
april 2018 by nhaliday
Sequence Modeling with CTC
A visual guide to Connectionist Temporal Classification, an algorithm used to train deep neural networks in speech recognition, handwriting recognition and other sequence problems.
acmtariat  techtariat  org:bleg  nibble  better-explained  machine-learning  deep-learning  visual-understanding  visualization  analysis  let-me-see  research  sequential  audio  classification  model-class  exposition  language  acm  approximation  comparison  markov  iteration-recursion  concept  atoms  distribution  orders  DP  heuristic  optimization  trees  greedy  matching  gradient-descent 
december 2017 by nhaliday
[1709.06560] Deep Reinforcement Learning that Matters
https://twitter.com/WAWilsonIV/status/912505885565452288
I’ve been experimenting w/ various kinds of value function approaches to RL lately, and its striking how primitive and bad things seem to be
At first I thought it was just that my code sucks, but then I played with the OpenAI baselines and nope, it’s the children that are wrong.
And now, what comes across my desk but this fantastic paper: (link: https://arxiv.org/abs/1709.06560) arxiv.org/abs/1709.06560 How long until the replication crisis hits AI?

https://twitter.com/WAWilsonIV/status/911318326504153088
Seriously I’m not blown away by the PhDs’ records over the last 30 years. I bet you’d get better payoff funding eccentrics and amateurs.
There are essentially zero fundamentally new ideas in AI, the papers are all grotesquely hyperparameter tuned, nobody knows why it works.

Deep Reinforcement Learning Doesn't Work Yet: https://www.alexirpan.com/2018/02/14/rl-hard.html
Once, on Facebook, I made the following claim.

Whenever someone asks me if reinforcement learning can solve their problem, I tell them it can’t. I think this is right at least 70% of the time.
papers  preprint  machine-learning  acm  frontier  speedometer  deep-learning  realness  replication  state-of-art  survey  reinforcement  multi  twitter  social  discussion  techtariat  ai  nibble  org:mat  unaffiliated  ratty  acmtariat  liner-notes  critique  sample-complexity  cost-benefit  todo 
september 2017 by nhaliday

« earlier    

related tags

abstraction  academia  accretion  acm  adversarial  advice  aging  ai-control  ai  akrasia  algorithms  alignment  allodium  alt-inst  altruism  analogy  analysis  analytical-holistic  anthropic  applicability-prereqs  approximation  arbitrage  archive  arms  article  atoms  attention  audio  authoritarianism  auto-learning  automata  automation  average-case  backpropagation  bandits  bare-hands  bayesian  ben-recht  benchmarks  best-practices  better-explained  bias-variance  biases  big-picture  bio  bits  blog  boltzmann  bonferroni  bret-victor  brunn-minkowski  caching  caltech  causation  charity  checking  checklists  circuits  civil-liberty  civilization  clarity  classic  classification  clever-rats  cmu  coalitions  coarse-fine  coding-theory  cog-psych  combo-optimization  commentary  communication  community  comparison  complement-substitute  composition-decomposition  compressed-sensing  computer-vision  concentration-of-measure  concept  conceptual-vocab  concurrency  conference  confidence  confounding  confusion  constraint-satisfaction  context  contracts  contrarianism  convergence  convexity-curvature  cooperate-defect  coordination  cost-benefit  counterexample  counterfactual  courage  critique  crux  curiosity  curvature  cybernetics  cycles  data-science  data  dataset  dataviz  debate  debt  debugging  decision-making  decision-theory  deep-learning  deepgoog  deeplearning  defense  definition  descriptive  detail-architecture  differential-privacy  dimensionality  direction  discovery  discussion  distribution  dp  duality  dumb-ml  duplication  dynamic  dynamical  economics  effective-altruism  efficiency  egt  elections  elegance  embedded-cognition  embeddings  empirical  ems  endo-exo  engineering  enhancement  ensembles  entropy-like  epistemic  ergodic  error  essay  estimate  ethical-algorithms  ethics  events  evolution  examples  existence  expansionism  expectancy  expert-experience  expert  explanans  explanation  exploratory  exposition  extrema  facebook  fall-2016  features  fermi  fiction  fixed-point  flexibility  formal-values  forum  fourier  frequentist  frontier  fungibility-liquidity  futurism  games  gedanken  gelman  generalization  generative  geometry  giants  google  gotchas  government  gradient-descent  graphs  gray-econ  greedy  ground-up  growth-econ  guide  habit  hard-core  hci  heterodox  heuristic  hi-order-bits  history  hmm  hn  homepage  howto  hsu  human-ml  hypothesis-testing  icml  ideas  ieee  impact  info-dynamics  information-theory  inhibition  init  innovation  insight  institutions  intel  intelligence  interdisciplinary  internet  interpretability  intersection-connectedness  intersection  intricacy  intuition  invariance  isotropy  iteration-recursion  iterative-methods  jargon  kernels  language  latent-variables  law  learning-theory  learning  lectures  lens  lesswrong  let-me-see  levers  leviathan  libraries  linear-algebra  linear-models  linearity  liner-notes  links  list  local-global  logic  long-short-run  low-hanging  lower-bounds  machine-learning  magnitude  map-territory  markov  matching  math.co  math.ds  math.mg  math  matrix-factorization  measure  measurement  media  meta:math  meta:prediction  meta:reading  meta:research  meta:rhetoric  meta:science  metabuch  metameta  methodology  metrics  michael-jordan  michael-nielsen  mixing  ml-map-e  ml  model-class  models  moments  monte-carlo  morality  mrtz  multi  multiplicative  near-far  network-structure  neuro  neurons  nibble  nips  nitty-gritty  nlp  no-go  norms  numerics  occam  off-convex  online-learning  open-closed  openai  optimization  orders  org:bleg  org:inst  org:mat  org:med  org:nat  orwellian  oscillation  overflow  p:*  p:whenever  pac  papers  parsimony  pdf  peace-violence  people  performance  perturbation  philosophy  physics  pic  plots  policy  politics  polynomials  popsci  potential  power-law  power  pragmatic  prediction  prepping  preprint  presentation  princeton  priors-posteriors  pro-rata  probabilistic-method  probability  problem-solving  prof  programming  progression  project  proposal  psychology  publishing  python  q-n-a  questions  quixotic  quotes  random  ranking  rant  rat-pack  rationality  ratty  realness  reason  reddit  reduction  reflection  regression  regularity  regularization  regularizer  reinforcement  relativity  replication  repo  research-program  research  retention  rhetoric  rigidity  rigor  risk  roadmap  robust  roots  rounding  s:**  s:*  sample-complexity  sampling  sanjeev-arora  scale  scholar  sci-comp  science  scifi-fantasy  scitariat  search  sebastien-bubeck  security  sensitivity  sequential  siggraph  signal-noise  signaling  similarity  simulation  singularity  skeleton  sleuthin  smoothness  social-psych  social-science  social  society  software  space  sparsity  spatial  speculation  speed  speedometer  spock  stackex  state-of-art  statistics  stats  stochastic-processes  stories  strategy  stream  street-fighting  structure  success  summary  survey  survival  symmetry  synthesis  systematic-ad-hoc  tails  tainter  talks  tcs  tcstariat  teaching  tech  technical-writing  technology  techtariat  tensors  terrorism  tetlock  the-trenches  theory-practice  thermo  thick-thin  things  thinking  threat-modeling  thurston  tidbits  tightness  time-complexity  time-preference  time-use  todo  toolkit  tools  top-n  trade  tradeoffs  transitions  trees  trends  tricki  tricks  tutorial  twitter  unaffiliated  unintended-consequences  unit  universalism-particularism  unsupervised  values  vc-dimension  video  visual-understanding  visualization  volo-avolo  von-neumann  water  wild-ideas  wire-guided  within-without  workflow  workshop  worrydream  writing  xenobio  yoga  zero-positive-sum  zooming  🎓  🔬  🖥  🤖 

Copy this bookmark:



description:


tags: