Call For Competitions
12 weeks ago by nhaliday
alotta these have already ended but, eg, Lyft is still going
contest
oly
machine-learning
deep-learning
computer-vision
automation
auto-learning
nips
conference
transportation
bio
bioinformatics
robotics
generative
reinforcement
priors-posteriors
human-ml
data-science
kaggle
links
list
12 weeks ago by nhaliday
Basic Error Rates
may 2019 by nhaliday
This page describes human error rates in a variety of contexts.
Most of the error rates are for mechanical errors. A good general figure for mechanical error rates appears to be about 0.5%.
Of course the denominator differs across studies. However only fairly simple actions are used in the denominator.
The Klemmer and Snyder study shows that much lower error rates are possible--in this case for people whose job consisted almost entirely of data entry.
The error rate for more complex logic errors is about 5%, based primarily on data on other pages, especially the program development page.
org:junk
list
links
objektbuch
data
database
error
accuracy
human-ml
machine-learning
ai
pro-rata
metrics
automation
benchmarks
marginal
nlp
language
density
writing
dataviz
meta:reading
speedometer
Most of the error rates are for mechanical errors. A good general figure for mechanical error rates appears to be about 0.5%.
Of course the denominator differs across studies. However only fairly simple actions are used in the denominator.
The Klemmer and Snyder study shows that much lower error rates are possible--in this case for people whose job consisted almost entirely of data entry.
The error rate for more complex logic errors is about 5%, based primarily on data on other pages, especially the program development page.
may 2019 by nhaliday
Iterated Distillation and Amplification – AI Alignment
nibble org:bleg acmtariat clever-rats ai ai-control alignment iteration-recursion deepgoog games research research-program algorithms explanation exposition summary reinforcement values machine-learning human-ml tradeoffs volo-avolo ratty
april 2018 by nhaliday
nibble org:bleg acmtariat clever-rats ai ai-control alignment iteration-recursion deepgoog games research research-program algorithms explanation exposition summary reinforcement values machine-learning human-ml tradeoffs volo-avolo ratty
april 2018 by nhaliday
Information Processing: US Needs a National AI Strategy: A Sputnik Moment?
february 2018 by nhaliday
FT podcasts on US-China competition and AI: http://infoproc.blogspot.com/2018/05/ft-podcasts-on-us-china-competition-and.html
A new recommended career path for effective altruists: China specialist: https://80000hours.org/articles/china-careers/
Our rough guess is that it would be useful for there to be at least ten people in the community with good knowledge in this area within the next few years.
By “good knowledge” we mean they’ve spent at least 3 years studying these topics and/or living in China.
We chose ten because that would be enough for several people to cover each of the major areas listed (e.g. 4 within AI, 2 within biorisk, 2 within foreign relations, 1 in another area).
AI Policy and Governance Internship: https://www.fhi.ox.ac.uk/ai-policy-governance-internship/
https://www.fhi.ox.ac.uk/deciphering-chinas-ai-dream/
https://www.fhi.ox.ac.uk/wp-content/uploads/Deciphering_Chinas_AI-Dream.pdf
Deciphering China’s AI Dream
The context, components, capabilities, and consequences of
China’s strategy to lead the world in AI
Europe’s AI delusion: https://www.politico.eu/article/opinion-europes-ai-delusion/
Brussels is failing to grasp threats and opportunities of artificial intelligence.
By BRUNO MAÇÃES
When the computer program AlphaGo beat the Chinese professional Go player Ke Jie in a three-part match, it didn’t take long for Beijing to realize the implications.
If algorithms can already surpass the abilities of a master Go player, it can’t be long before they will be similarly supreme in the activity to which the classic board game has always been compared: war.
As I’ve written before, the great conflict of our time is about who can control the next wave of technological development: the widespread application of artificial intelligence in the economic and military spheres.
...
If China’s ambitions sound plausible, that’s because the country’s achievements in deep learning are so impressive already. After Microsoft announced that its speech recognition software surpassed human-level language recognition in October 2016, Andrew Ng, then head of research at Baidu, tweeted: “We had surpassed human-level Chinese recognition in 2015; happy to see Microsoft also get there for English less than a year later.”
...
One obvious advantage China enjoys is access to almost unlimited pools of data. The machine-learning technologies boosting the current wave of AI expansion are as good as the amount of data they can use. That could be the number of people driving cars, photos labeled on the internet or voice samples for translation apps. With 700 or 800 million Chinese internet users and fewer data protection rules, China is as rich in data as the Gulf States are in oil.
How can Europe and the United States compete? They will have to be commensurately better in developing algorithms and computer power. Sadly, Europe is falling behind in these areas as well.
...
Chinese commentators have embraced the idea of a coming singularity: the moment when AI surpasses human ability. At that point a number of interesting things happen. First, future AI development will be conducted by AI itself, creating exponential feedback loops. Second, humans will become useless for waging war. At that point, the human mind will be unable to keep pace with robotized warfare. With advanced image recognition, data analytics, prediction systems, military brain science and unmanned systems, devastating wars might be waged and won in a matter of minutes.
...
The argument in the new strategy is fully defensive. It first considers how AI raises new threats and then goes on to discuss the opportunities. The EU and Chinese strategies follow opposite logics. Already on its second page, the text frets about the legal and ethical problems raised by AI and discusses the “legitimate concerns” the technology generates.
The EU’s strategy is organized around three concerns: the need to boost Europe’s AI capacity, ethical issues and social challenges. Unfortunately, even the first dimension quickly turns out to be about “European values” and the need to place “the human” at the center of AI — forgetting that the first word in AI is not “human” but “artificial.”
https://twitter.com/mr_scientism/status/983057591298351104
https://archive.is/m3Njh
US military: "LOL, China thinks it's going to be a major player in AI, but we've got all the top AI researchers. You guys will help us develop weapons, right?"
US AI researchers: "No."
US military: "But... maybe just a computer vision app."
US AI researchers: "NO."
https://www.theverge.com/2018/4/4/17196818/ai-boycot-killer-robots-kaist-university-hanwha
https://www.nytimes.com/2018/04/04/technology/google-letter-ceo-pentagon-project.html
https://twitter.com/mr_scientism/status/981685030417326080
https://archive.is/3wbHm
AI-risk was a mistake.
hsu
scitariat
commentary
video
presentation
comparison
usa
china
asia
sinosphere
frontier
technology
science
ai
speedometer
innovation
google
barons
deepgoog
stories
white-paper
strategy
migration
iran
human-capital
corporation
creative
alien-character
military
human-ml
nationalism-globalism
security
investing
government
games
deterrence
defense
nuclear
arms
competition
risk
ai-control
musk
optimism
multi
news
org:mag
europe
EU
80000-hours
effective-altruism
proposal
article
realness
offense-defense
war
biotech
altruism
language
foreign-lang
philosophy
the-great-west-whale
enhancement
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anglo
jobs
career
planning
hmm
travel
charity
tech
intel
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tutoring
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india
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class
labor
polisci
society
trust
n-factor
corruption
leviathan
ethics
authoritarianism
individualism-collectivism
revolution
economics
inequality
civic
law
regulation
data
scale
pro-rata
capital
zero-positive-sum
cooperate-defect
distribution
time-series
tre
A new recommended career path for effective altruists: China specialist: https://80000hours.org/articles/china-careers/
Our rough guess is that it would be useful for there to be at least ten people in the community with good knowledge in this area within the next few years.
By “good knowledge” we mean they’ve spent at least 3 years studying these topics and/or living in China.
We chose ten because that would be enough for several people to cover each of the major areas listed (e.g. 4 within AI, 2 within biorisk, 2 within foreign relations, 1 in another area).
AI Policy and Governance Internship: https://www.fhi.ox.ac.uk/ai-policy-governance-internship/
https://www.fhi.ox.ac.uk/deciphering-chinas-ai-dream/
https://www.fhi.ox.ac.uk/wp-content/uploads/Deciphering_Chinas_AI-Dream.pdf
Deciphering China’s AI Dream
The context, components, capabilities, and consequences of
China’s strategy to lead the world in AI
Europe’s AI delusion: https://www.politico.eu/article/opinion-europes-ai-delusion/
Brussels is failing to grasp threats and opportunities of artificial intelligence.
By BRUNO MAÇÃES
When the computer program AlphaGo beat the Chinese professional Go player Ke Jie in a three-part match, it didn’t take long for Beijing to realize the implications.
If algorithms can already surpass the abilities of a master Go player, it can’t be long before they will be similarly supreme in the activity to which the classic board game has always been compared: war.
As I’ve written before, the great conflict of our time is about who can control the next wave of technological development: the widespread application of artificial intelligence in the economic and military spheres.
...
If China’s ambitions sound plausible, that’s because the country’s achievements in deep learning are so impressive already. After Microsoft announced that its speech recognition software surpassed human-level language recognition in October 2016, Andrew Ng, then head of research at Baidu, tweeted: “We had surpassed human-level Chinese recognition in 2015; happy to see Microsoft also get there for English less than a year later.”
...
One obvious advantage China enjoys is access to almost unlimited pools of data. The machine-learning technologies boosting the current wave of AI expansion are as good as the amount of data they can use. That could be the number of people driving cars, photos labeled on the internet or voice samples for translation apps. With 700 or 800 million Chinese internet users and fewer data protection rules, China is as rich in data as the Gulf States are in oil.
How can Europe and the United States compete? They will have to be commensurately better in developing algorithms and computer power. Sadly, Europe is falling behind in these areas as well.
...
Chinese commentators have embraced the idea of a coming singularity: the moment when AI surpasses human ability. At that point a number of interesting things happen. First, future AI development will be conducted by AI itself, creating exponential feedback loops. Second, humans will become useless for waging war. At that point, the human mind will be unable to keep pace with robotized warfare. With advanced image recognition, data analytics, prediction systems, military brain science and unmanned systems, devastating wars might be waged and won in a matter of minutes.
...
The argument in the new strategy is fully defensive. It first considers how AI raises new threats and then goes on to discuss the opportunities. The EU and Chinese strategies follow opposite logics. Already on its second page, the text frets about the legal and ethical problems raised by AI and discusses the “legitimate concerns” the technology generates.
The EU’s strategy is organized around three concerns: the need to boost Europe’s AI capacity, ethical issues and social challenges. Unfortunately, even the first dimension quickly turns out to be about “European values” and the need to place “the human” at the center of AI — forgetting that the first word in AI is not “human” but “artificial.”
https://twitter.com/mr_scientism/status/983057591298351104
https://archive.is/m3Njh
US military: "LOL, China thinks it's going to be a major player in AI, but we've got all the top AI researchers. You guys will help us develop weapons, right?"
US AI researchers: "No."
US military: "But... maybe just a computer vision app."
US AI researchers: "NO."
https://www.theverge.com/2018/4/4/17196818/ai-boycot-killer-robots-kaist-university-hanwha
https://www.nytimes.com/2018/04/04/technology/google-letter-ceo-pentagon-project.html
https://twitter.com/mr_scientism/status/981685030417326080
https://archive.is/3wbHm
AI-risk was a mistake.
february 2018 by nhaliday
What is recommended number of latent factors for the implicit collaborative filtering using ALS? - Quora
q-n-a qra expert machine-learning acm model-class best-practices matrix-factorization ranking matching generalization nibble multi overflow data-science data optimization expert-experience human-ml
august 2017 by nhaliday
q-n-a qra expert machine-learning acm model-class best-practices matrix-factorization ranking matching generalization nibble multi overflow data-science data optimization expert-experience human-ml
august 2017 by nhaliday
How to create recommender system that integrates both collaborative filtering and content features? - Cross Validated
nibble q-n-a overflow data-science machine-learning acm model-class matrix-factorization matching ranking todo project pinboard exocortex exploratory features papers recommendations research human-ml latent-variables
august 2017 by nhaliday
nibble q-n-a overflow data-science machine-learning acm model-class matrix-factorization matching ranking todo project pinboard exocortex exploratory features papers recommendations research human-ml latent-variables
august 2017 by nhaliday
Tutorial bpocf - Collaborative Filtering with Binary, Positive-only Data Tutorial
july 2017 by nhaliday
collaborative filtering where you only have R_ij = 1 or R_ij = ?
would be useful for pinboard tag-recommendation
http://win.ua.ac.be/~adrem/bibrem/pubs/verstrepen15PhDthesis.pdf
many cites: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.192.6482&rep=rep1&type=pdf
Bayesian: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.165.7857&rep=rep1&type=pdf
implemented in Quora library (c++): https://pinboard.in/u:nhaliday/b:5265de8b1c0d
slides
talks
machine-learning
acm
model-class
matching
pinboard
todo
human-ml
nibble
multi
pdf
thesis
papers
exocortex
exploratory
matrix-factorization
bayesian
positivity
homo-hetero
volo-avolo
measurement
ranking
qra
libraries
parametric
project
data-science
signum
would be useful for pinboard tag-recommendation
http://win.ua.ac.be/~adrem/bibrem/pubs/verstrepen15PhDthesis.pdf
many cites: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.192.6482&rep=rep1&type=pdf
Bayesian: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.165.7857&rep=rep1&type=pdf
implemented in Quora library (c++): https://pinboard.in/u:nhaliday/b:5265de8b1c0d
july 2017 by nhaliday
The Bridge: 数字化 – 网络化 – 智能化: China’s Quest for an AI Revolution in Warfare
june 2017 by nhaliday
The PLA’s organizational tendencies could render it more inclined to take full advantage of the disruptive potential of artificial intelligence, without constraints due to concerns about keeping humans ‘in the loop.’ In its command culture, the PLA has tended to consolidate and centralize authorities at higher levels, remaining reluctant to delegate decision-making downward. The introduction of information technology has exacerbated the tendency of PLA commanders to micromanage subordinates through a practice known as “skip-echelon command” (越级指挥) that enables the circumvention of command bureaucracy to influence units and weapons systems at even a tactical level.[xxviii] This practice can be symptomatic of a culture of distrust and bureaucratic immaturity. The PLA has confronted and started to progress in mitigating its underlying human resource challenges, recruiting increasingly educated officers and enlisted personnel, while seeking to modernize and enhance political and ideological work aimed to ensure loyalty to the Chinese Communist Party. However, the employment of artificial intelligence could appeal to the PLA as a way to circumvent and work around those persistent issues. In the long term, the intersection of the PLA’s focus on ‘scientific’ approaches to warfare with the preference to consolidate and centralize decision-making could cause the PLA’s leadership to rely more upon artificial intelligence, rather than human judgment.
news
org:mag
org:foreign
trends
china
asia
sinosphere
war
meta:war
military
defense
strategy
current-events
ai
automation
technology
foreign-policy
realpolitik
expansionism
innovation
individualism-collectivism
values
prediction
deepgoog
games
n-factor
human-ml
alien-character
risk
ai-control
june 2017 by nhaliday
AI Impacts – Guide to pages on AI timeline predictions
may 2017 by nhaliday
http://slatestarcodex.com/2017/06/08/ssc-journal-club-ai-timelines/
http://www.bayesianinvestor.com/blog/index.php/2017/06/01/do-ai-experts-exist/
http://infoproc.blogspot.com/2017/06/rise-of-machines-survey-of-ai.html
https://www.youtube.com/watch?v=WSKi8HfcxEk
https://www.youtube.com/watch?v=7Pq-S557XQU
http://infoproc.blogspot.com/2017/07/robots-taking-our-jobs.html
ratty
ai
ai-control
risk
automation
links
summary
futurism
prediction
poll
expert
technology
definite-planning
miri-cfar
speedometer
flux-stasis
multi
yvain
ssc
commentary
hsu
scitariat
the-bones
stagnation
winner-take-all
inequality
video
labor
presentation
human-ml
acemoglu
chart
expert-experience
singularity
http://www.bayesianinvestor.com/blog/index.php/2017/06/01/do-ai-experts-exist/
http://infoproc.blogspot.com/2017/06/rise-of-machines-survey-of-ai.html
https://www.youtube.com/watch?v=WSKi8HfcxEk
https://www.youtube.com/watch?v=7Pq-S557XQU
http://infoproc.blogspot.com/2017/07/robots-taking-our-jobs.html
may 2017 by nhaliday
Adaptive data analysis
acmtariat acm machine-learning stats research research-program exposition science methodology mrtz meta:science differential-privacy liner-notes hypothesis-testing org:bleg nibble metameta 🔬 info-dynamics generalization iteration-recursion data-science online-learning bayesian gelman scitariat frequentist human-ml robust perturbation sensitivity learning-theory information-theory bits lower-bounds no-go volo-avolo adversarial gradient-descent bonferroni
december 2016 by nhaliday
acmtariat acm machine-learning stats research research-program exposition science methodology mrtz meta:science differential-privacy liner-notes hypothesis-testing org:bleg nibble metameta 🔬 info-dynamics generalization iteration-recursion data-science online-learning bayesian gelman scitariat frequentist human-ml robust perturbation sensitivity learning-theory information-theory bits lower-bounds no-go volo-avolo adversarial gradient-descent bonferroni
december 2016 by nhaliday
Notes Essays—Peter Thiel’s CS183: Startup—Stanford, Spring 2012
business startups strategy course thiel contrarianism barons definite-planning entrepreneurialism lecture-notes skunkworks innovation competition market-power winner-take-all usa anglosphere duplication education higher-ed law ranking success envy stanford princeton harvard elite zero-positive-sum war truth realness capitalism markets darwinian rent-seeking google facebook apple microsoft amazon capital scale network-structure tech business-models twitter social media games frontier time rhythm space musk mobile ai transportation examples recruiting venture metabuch metameta skeleton crooked wisdom gnosis-logos thinking polarization synchrony allodium antidemos democracy things exploratory dimensionality nationalism-globalism trade technology distribution moments personality phalanges stereotypes tails plots visualization creative nietzschean thick-thin psych-architecture wealth class morality ethics status extra-introversion info-dynamics narrative stories fashun myth the-classics literature big-peeps crime
february 2016 by nhaliday
business startups strategy course thiel contrarianism barons definite-planning entrepreneurialism lecture-notes skunkworks innovation competition market-power winner-take-all usa anglosphere duplication education higher-ed law ranking success envy stanford princeton harvard elite zero-positive-sum war truth realness capitalism markets darwinian rent-seeking google facebook apple microsoft amazon capital scale network-structure tech business-models twitter social media games frontier time rhythm space musk mobile ai transportation examples recruiting venture metabuch metameta skeleton crooked wisdom gnosis-logos thinking polarization synchrony allodium antidemos democracy things exploratory dimensionality nationalism-globalism trade technology distribution moments personality phalanges stereotypes tails plots visualization creative nietzschean thick-thin psych-architecture wealth class morality ethics status extra-introversion info-dynamics narrative stories fashun myth the-classics literature big-peeps crime
february 2016 by nhaliday
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