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iraphael

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i would focus on just taking notes on related topics, without much structure for a bit. try to link them together if they are on related ideas a bit. once you have a network of notes that feels a little less manageable (~100), i create a "map of content" where i link to all notes related to that concept, and in it i essentially tell a higher level story about how those notes relate to each other.

+1 to this point.

I also find it easier to read certain philosophers than others because they themselves seem to be empathetic in the way they write their thinking. Almost as if they know that they could be wrong about the conclusions they're coming to, and that the truths they uncover aren't necessarily absolutes but instead, at least to a certain degree, subjective and personal.

Reading phenomenology for instance doesn't get me feeling like the author is self-indulgent. I find it easier to empathize with the philosopher because the philosopher is trying to empathize with me.

I don't actually remember. I used to set all my settings to US/American ones because some apps were only in the US app store, so there's a good chance I was looking at the US$1 price. Not sure what my friends saw in the Brazilian app store.

The power of mass usage comes into play here. IIRC, when WhatsApp launched, I was one of the early adopters. As it grew (and it became hugely popular in Brazil, where I lived) they switched to the $1/year model. Current users were auto-enrolled in a "free-for-life" plan. My friends who didn't have WhatApp would still sign up because everyone else was using it and, besides "$1/year? it's almost nothing".

I received an email from a website I don't remember signing up for, and have no clue what they do. After a few attempts I am able to log in. I go through menu after menu looking for the "permanently delete all my data" button only to find an FAQ that says

"Q: How do I delete my account?"

"A: Please get in touch with our Customer Services team if you have any worries or concerns. If something at {website} has troubled you, we'll be happy to help sort it out."

To their credit, the support chat person was very efficient in complying with my request.

I was actually wondering what the data considers "immigration". This shows no African countries light up until around the 90s but that's somewhat incorrectly categorizing influx of people into the US as it ignores "forced immigration" (kidnapping for slavery).

I’m not talking about being stuck in traffic, which is often a issue with poor planning and lack of infrastructure investment rather than an issue with cars themselves

I disagree with this statement. I believe that cars are not a transportation solution that scales like public transportation, for instance, does.

For these same reasons I believe Musk's Boring Company's plans are exactly the wrong kind of urban planning ideas that will just create a "fast lane" for those who can pay, instead of a solution that works for all.

Maybe cars could come with this romanticized "freedom" and "pleasure" when they're not prevalent enough to cause the issues that make driving undesirable. But I think the last time that happened was when cars were luxury items, reserved for the rich suburban white America and I don't want the future to involve making transportation more under-democratized.

there is pushing a country into forbidding every kind of energy generation available

which is not what is happening in Brazil. There are enormous opportunities for energy generation far away from the Amazon. In fact, a lot of foreigners don't know but the vast majority of Brazilian population lives nowhere near the Amazon. Creating an energy grid in the forest is a great way to waste energy due to traveling long distances in transition cables.

There's a lot of things to do in TensorFlow that involve a lot of work (and could even be its own project). Namely support for dynamic computation graphs (a-lá PyTorch). TF as it is is great for production, and even for research, but a lot of people in the latter are starting to look at PyTorch more and more for prototyping.

[dead] 9 years ago

[FLAGGED] This very misguided article seems to be a complete misunderstanding of two papers: https://arxiv.org/abs/1706.05125 and https://arxiv.org/abs/1611.04558

None of the dramatic claims have any basis in real science, or real world events (e.g.: "it prompted concerns we could lose control of AI"? I'm 100% certain this came from the author's imagination).

This kind of AI apocalyptic alarmism with no real basis is the same kind that created the first AI winter, and the complete misinterpretation of research in popular culture.

Unless there's a very deep layer of irony I'm not seeing, this article is not worth your click.

* Densely Connected Convolutional Networks [0] by Gao Huang, Zhuang Liu, Laurens van der Maaten, & Kilian Q. Weinberger.

* Learning from Simulated and Unsupervised Images through Adversarial Training [1] by Ashish Shrivastava, Tomas Pfister, Oncel Tuzel, Joshua Susskind, Wenda Wang, & Russell Webb

CVPR 2017 Best Paper Honorable Mention Awards

* Annotating Object Instances with a Polygon-RNN [2] by Lluís Castrejón, Kaustav Kundu, Raquel Urtasun, & Sanja Fidler * YOLO9000: Better, Faster, Stronger [3] by Joseph Redmon & Ali Farhadi

CVPR 2017 Best Student Paper Award

* Computational Imaging on the Electric Grid [4] by Mark Sheinin, Yoav Y. Schechner, & Kiriakos N. Kutulakos

CVPR 2017 Longuet-Higgins Prize (for cvpr 2007 papers that stood the test of time)

* Object Retrieval with Large Vocabularies and Fast Spatial Matching [5] by James Philbin, Ondrej Chum, Michael Isard, Josef Sivic & Andrew Zisserman

CVPR 2017 PAMI Young Researcher Award

* Ross Girshick & Julien Mairal

[0] https://arxiv.org/abs/1608.06993

[1] https://arxiv.org/abs/1612.07828

[2] https://arxiv.org/abs/1704.05548

[3] https://arxiv.org/abs/1612.08242

[4] http://openaccess.thecvf.com/content_cvpr_2017/papers/Sheini...

[5] http://ieeexplore.ieee.org/document/4270197/

I have to respectfully disagree. From the video (the only source of information we have about the company's plans), it focuses on automobile-centric high speed transportation (as opposed to, say, efficient public transportation).

If there's anything we learned in the last ~30 years of urban planning is that building cities at car scales isn't the best way to promote healthy city life and community. There are many reasons for this. There's probably books that focus on just this, but if you want a better idea of how city design has affected community living in general, I recommend The Great Good Place [0].

I read somewhere else in this thread that The Boring Company is obviously something intended for Mars. I am more ok with that idea, since it might be impossible to do anything other than underground individual transportation in a place where the environment is hostile.

[0] https://en.wikipedia.org/wiki/The_Great_Good_Place_(Oldenbur...

Does anyone have more information about the finding itself? This article seems to be mostly a story about how "there was this mystery, and this scientist solved it with math".