jeremynixon

Mechanics and Insights from Extreme Productivity Experiments

This blog post is flawed. "Life insurers can predict when you'll die with about 98% accuracy." Is not even properly framed and is found nowhere in the cited report.

Predictions of when you will die need a range in order to be attached to a number like accuracy. The attached report is not about this but about population-level mortality trends.

This blog post is flawed.

"Life insurers can predict when you'll die with about 98% accuracy." Is not even properly framed and is found nowhere in the cited report.

Predictions of when you will die need a range in order to be attached to a number like accuracy. The attached report is not about this but about population-level mortality trends.

There is article shows no evidence of fabrication, fraud or misinformation, while making accusations of all of them. All it shows is that ChatGPT was used, which is wildly escalated into "evidence manipulation" (ironically without evidence).

Much more work is needed to show that this means anything.

Search through youtube via embedding search over frames of video, in a click-to-semantic-search interface. (Right click to play video)

For now, the researcher using our tool needs to check.

or perhaps, free scientists to focus on genuine insight, ending publish or perish forever

OP here: We have data source powered research papers in the making, that reports on experiments executed with codegen - really hopeful that the papers can be informative at a minimum.

It's clear that superhuman citation depth & breadth is already imminent. Hopefully we can push hallucinations to near-zero with the next generation of models.

What libraries do you see as being SOTA? Fitz? Tika?

My hope is that computer vision + OCR will solve this once and for all in near future.

Why is the state of the art in PDF parsing SO BAD? This is an incredibly common and important problem. Tika and fitz have very poor results. What is the reason that this is still so backwards?

Genuinely curious. Why is apple search still so bad after poaching all of these Google people?

Are these fines close to the business value gained from getting this legislation passed over the last 5 years? Seems unlikely. Nobody is going to jail. So where is the disincentive?

Instead of ensuring that health care benefits are independent of corporate attachments, Marty Walsh continues to destroy useful distinctions in a system that congress refuses to appropriately reform. Sad.

Please Contribute: https://docs.google.com/spreadsheets/d/1l0QMTpYkBgFxEbfCeal2...

Growth Mr. Money Moustache [http://www.mrmoneymustache.com/] Study Hacks, Cal Newport [http://calnewport.com/blog/] Tim Ferriss [https://tim.blog/] Oliver Emberton [oliveremberton.com]

Intellectual Farnam Street, Shane Parrish [farnamstreetblog.com/blog] Less Wrong [http://lesswrong.com/] [lesserwrong.com] Raw Thought, Aaron Swartz [aaronsw.com/weblog] Slate Star Codex [slatestarcodex.com] Edge [http://edge.org/] Melting Asphalt, Kevin Simler [http://www.meltingasphalt.com/] Essays, Paul Graham [paulgraham.com/articles.html] Minding Our Way, Nate Soares [http://mindingourway.com/] Ribbonfarm, Venkatesh Rao [ribbonfarm.com] Overcoming Bias, Robin Hanson [overcomingbias.com] Shtetl-Optimized, Scott Aaronson [http://www.scottaaronson.com/blog/] Raikoth, Scott Alexander [http://web.archive.org/web/20140220082152/http://raikoth.net...] Heterodox Academy [https://heterodoxacademy.org/]

Technology Hacker News [https://news.ycombinator.com/] Worrydream, Bret Victor [http://worrydream.com/] Naval Ravikant [https://startupboy.com/] Unenumerated, Nick Szabo [http://unenumerated.blogspot.com/] Stratchery [http://stratchery.com/]

Statistics DataTau [http://www.datatau.com/] FiveThirtyEight [fivethirtyeight.com] Simply Statistics [https://simplystatistics.org/] Chris Olah [colah.github.io]

Economics Marginal Revolution [marginalrevolution.com] Project Syndicate [project-syndicate.org]

Companies to landlords, but yes.

This is a deep violation that makes every user of 2fa _unsafe_. A mere $250 million? This needs to be the kind of violation that endangers the company. It's not a mistake or honest error when 2fa phone numbers are used for advertising. This is malicious. Should be scaled to 100X the amount the company gained in advertising for the violation.

Peter Thiel’s view on progress and stagnation in his own words, sourced from a number of his interviews and articles. This document consists only of direct quotes from Thiel, lightly edited for clarity (except for headings and where marked otherwise). Key quotes are in the summary. Compiled by Richard Ngo (@richardmcngo) and Jeremy Nixon (@jvnixon).

From FB:

"We’re taking down these Pages, Groups and accounts based on their behavior, not the content they posted."

https://newsroom.fb.com/news/2019/08/removing-cib-china/

Didn't this book come out in 2012?

Important and and missing:

"[Uber] said it had suspended testing of its self-driving cars in Tempe, Pittsburgh, San Francisco and Toronto"[1]

1: https://www.nytimes.com/2018/03/19/technology/uber-driverles...

The question is actually about the counterfactual impact of Facebook's addiction machine.

In the absence of social media, do people simply replace their wasted time there with leisure like video games, television, texting, and the like? If yes, the net impact of Facebook is small.

Or, have the addictivity wizards actually managed to increase the amount of time spent in leisure, taking away from familial connection and deep friendships?

With Facebook in particular, there's a generated sense of belonging that comes along with the quantified social proof which makes the hits of dopamine much more personal and meaningful. I see this as trading off against getting that sense of connection in reality.

But much of the other 'damage' from Facebook is fungible, and people would turn to other sources of leisure and addiction soon after losing it. Perhaps one day these addictive engines will be powerful enough to make this untrue, but we're not there quite yet.

According to the nextflix prize leaderborad at http://www.netflixprize.com/leaderboard.html, this result wouldn't even be in the top 1000. More than that, due to the absence of compositional structure in the data I wouldn't expect this approach to work well. Would love to hear more insights, I'm digging into the paper now.

All that said, open code for running this on arbitrary data is great to have! A thanks to Oleksii Kuchaiev.

That's not implied by the title. Neural Networks is a member of Machine Learning, which is a member of AI. PyTorch, Caffe 2 and CNTK are Deep Learning Frameworks. All Deep Learning Frameworks are AI frameworks, but not all AI frameworks are neural network / deep learning frameworks.

Automatic productionizability of PyTorch models through Caffe 2 will speed the transition from research to production dramatically - this gives the environment a chance to compete with Tensorflow / Tensorflow Serving.

Frameworks (say, DL4J) have been using Keras as a loose way to share models between frameworks. It'll be fascinating to see if Theano / Tensorflow / DL4J / MXNet walk this path as well.

The mysticism around ‘Emergence’ is just a modeling error where people only abstract in one way (say, down to cells) and don’t include something important like the interaction between cells in their reductionist model of the system. It’s like creating a graph without the edges. And so when those effects have manifest consequences at a higher level, it feels like they appeared as if by magic.

It's not just Shervin Pishevar that wants Benchmark off the board. Ron Burkle (Yucaipa Cos) and Adam Leber (Maverick) also penned the letter requesting that they divest.

Would love to use this, how and where do I set the bookmarklet?

Legendary. Huge thanks to all of the engineers behind segwit.

Pass the paywall: https://t.co/fU9VRQUpiw