fsavard
https://news.ycombinator.com/item?id=16230668
I only post when I think I can somehow add value to the discussion, at least value for some people who might read the comment. Obviously some people with in-depth knowledge of the paper and field in general will probably already be aware of the link I posted (for example), but others might find it an interesting avenue to explore. I know I often come to HN comments for this reason: a topic seems interesting, I want to learn of related stuff and/or get opinions from people with deeper expertise.
So even if it's only for "future reference", it might actually bring value _for some_. At least that's what I tell myself :)
Their figure 1, which appears to describe fundamental design tradeoffs, makes me think of CAP theorem "maps", like this:
https://www.researchgate.net/figure/CAP-Theorem_fig4_2214620...
But the whole idea of figuring out first principles and "fundamental" design choices is quite appealing. They have a section saying that a big goal here would be automatic design of optimal data structures. They talk of machine learning techniques (they mention Bayesian optimization and reinforcement learning).
That seems a very interesting research direction. In the same vein there's this talk by Jeff Dean about how they use ML at Google to replace all sorts of heuristics in data structure design (bloom filters etc.) with machine learning to optimize performance, though from what I recall it doesn't automatically change the algorithm itself:
http://learningsys.org/nips17/assets/slides/dean-nips17.pdf
(discussed on HN previously https://news.ycombinator.com/item?id=15892956)
EDIT: I think they cite a paper by Dean and others which was part of that talk
Avatar Digitization From a Single Image For Real-Time Rendering
http://www.hao-li.com/publications/papers/siggraphAsia2017AD...
(from the people at Pinscreen)
There's a lot of work being done on using deep learning for computer graphics in general as well.
- https://eng.uber.com/ - https://code.fb.com/
and many more. Google also publishes papers on various engineering practices obviously, some ML-related, but I can't find a blog where they focus on that specifically.
Also it's not "to keep up to date", but there's a great paper (from Google) that's often cited:
Machine Learning: The High Interest Credit Card of Technical Debt https://ai.google/research/pubs/pub43146
It talks about issues you face over the long run (I've experienced some of those). It also provides interesting pointers for further reading, e.g. about "pipeline jungles".
If others have pointers, I'm curious to hear about them as well.
The trick I've found (I don't remember where) and used ever since is to map the "kj" sequence to <Esc>, since it's otherwise unlikely in normal text. It's just a simple instruction in the vim config:
:imap kj <Esc>
That foot pedal is a cute project though.
In my case it's just discomfort but I'm curious as to why constraints around the waist don't get discussed more in articles about posture. For me it's one of those things that annoy all day long, hovering slightly below awareness level.
Some companies make "dress sweatpants", e.g.
https://www.betabrand.com/collections/dress-pant-sweatpants/
but I never bought any because even in promotional pictures they still tend to look too much like sweatpants.
I stand up for routine tasks (email etc.) and sit down for deeper work. I find standing unconsciously restricts breathing (core muscles contract) so makes me exhausted more rapidly. I rarely work standing for more than an hour.
Reading comments here it seems a very common experience.
I think no matter how many studies on the subject there will be, personal experience dictates how we'll do it. Like you I'm just glad the option now is now socially acceptable to be a bit more mobile when doing desk work.
However I still think that the "short-lived" nature of discussions here is a relatively independent problem. I think integrating a way to "subscribe to a story" with email alerts on HN itself (rather than independent apps like hnreplies.com), and _displaying_ the number of people who did subscribe, would pave the way for longer-lived discussions. By seeing the number of people who did "subscribe to the story" you'd know whether or not it's still worth posting a comment even though it's been a day or two.
Maybe that's the reason forums have longer-lived discussions. You can easily get alerts when there are new posts in a discussion where you've posted.
More often then not, when that threshold is crossed, I realize I'm too late and my post will just sit there, unread.
Aren't there others who think it'd be great to have a "sticky" or "follow" button, in essence signalling "I'm going to follow this discussion for a few days / weeks, because I'm genuinely interested"?
Also if there was a way to easily "suscribe" to a thread (email alerts) that'd help. (Someone mentioned hnreplies.com in a sibling comment, never tried it, but I'll check it out)
I just wish a bunch of well-known publishers would get together and agree on _one_ solution that they'd all add to their site.
It's just a matter of adding a widget on their article pages. They already have large readership. It could kick things off and maybe get over that network effect cold-start issue.
They could add a nice bounty like "make a first payment and don't see ads on our site for a month". Or similar.
A solution like this could be a good candidate because it's neutral. With Flattr or similar you're encouraging that particular middleman. However I think to inspire confidence in publishers they'd need to prove that this solution will have strong support for years to come (which is always unsure with open source projects).
EDIT: To be clear I'm mostly thinking of micropayments to news sites. The strategy is less clear when talking about electronic commerce in general.
http://affaires.lapresse.ca/economie/201611/10/01-5039742-le...
which states that Montreal startups (by their definition) employ around 10,000 people. Of course those behind that study - local "startup scene" people and governmental instances - would have some incentive to inflate the numbers, but still, it seems larger than what you assume (1% of 66000 ~= 600 - 700 jobs). It's not Bombardier, but it's not negligible either.
I'm not sure what to say about your larger point, because I'm not sure if you're advocating something in particular. Are you saying it would be better if Facebook, Google etc. didn't open labs here, e.g. to avoid competition for local AI specialists? Or maybe you're just drawing attention to that drawback. In any case, I'd just say I'd hope it's not a zero-sum game. With better opportunities, the pool enlarges because 1) people come from abroad and 2) it makes sense for local people to specialize (e.g. pursue a PhD) in that direction.
It's a bit early to conclude concerning the long-term "impact on the local economy" as you mention, but I guess it can't hurt to shine internationally in one more respect.
EDIT: I'd add also that there are quite a few AI-centered startups, where AI is the forefront and not just a component, e.g. look at this:
https://medium.com/@shivon/the-current-state-of-machine-inte...
and startups certainly contribute to the local economy. A local ecosystem around AI could foster such startups, I guess, so again not hurting.
Anyway it's pretty funny in light of an intro I remembered from one of his old papers:
"It would be truly wonderful if randomly connected neural networks could turn themselves into useful computing devices by using some simple rule to modify the strength of synapses. This was the hope that lay behind the original Hebb learning rule and it is the vision that has driven neural network modelers for half a century. Initially, researchers tried simulating various rules to see what would happen. After a decade or two of messing around, researchers realized that there was a much better way to explore the space of possible learning rules: First write down an objective function [...] and then use elementary calculus to derive a learning rule that will improve the objective function." [1]
ie. backprop
So actually backprop was the solution to all that initial "messing around" with unsupervised rules. Though of course to be fair (if I understand correctly) those rules had very little to do with modern "unsupervised learning" methods (e.g. autoencoders, which still rely on backprop or similar optimization).
[1] http://www.cs.toronto.edu/~fritz/absps/hebbdot.pdf published in 2003
I have another setup with an Ergotron Workfit (can be lifted up and down) but I find that the position is more adjustable with my mirror-screen version. With the Ergotron the position of the hands relative to screen is fixed so eye-screen distance can't be adjusted as well as I'd like. Also screen height doesn't go as high as I'd like.
http://www.fsavard.com/flow/2012/12/diff-revision/
Basically you take notes like you normally would and the "diffs" of your notes become the elements you will review using spaced-repetition style intervals.
Drawbacks:
- It's not exactly user friendly in its current implementation.
- There isn't any way to give yourself a grade based on how well you remembered a piece of information.
- You must take care to write notes in small blurbs before running the "diff" command, otherwise I end up with large chunks of text to revise and I won't review properly.
- The lack of question-answer mechanism pretty much bypasses the whole "active recall" principle, or whatever that was called.
(Edit: spacing.)
Do you know what the Google monthly fees are? Is the bandwidth consumed a concern?
5 minutes after drop-off is quite enough to uncover where you meant to _really_ go if you gave a close-by address, in these scenarios.
That's pretty much what the OP meant with "So your secret rendezvous may not be so secret" but it's particularly poignant in a TV show.
Here's the thread I saw:
http://www.engadget.com/2013/06/17/geak-ring-nfc-finger/
The "unlock your smartphone" use case is underlined here, too.
Manufacturer's site (Chinese, can't read it myself): http://www.igeak.com/Ring
But for the reader there's a definite advantage: you know exactly what has changed, and whether a site is updated regularly. I have a small blog, and on some entries I maintain changelogs manually. I suppose the best would be for Wordpress and the like to offer the ability to link to cleanly-formatted diffs (ala revisions in google docs).
(and just a heads up: I think your link should point to http://converspace.github.com/specification/... your link gives me a 404)
I like WikidPad because it's _fast_ in Edit mode (on-the-fly text formatting, like code highlighting), and it turns out to be a killer feature for me: without this speed I probably wouldn't be using it as much. With almost all other wikis I know, you need to switch back and forth between edit mode and preview mode, or they have a WYSIWYG editor mode (and I avoid that as much as possible -- just a programmer's obsession... I like to deal with the source).
I haven't used TiddlyWiki much, but I loved the concept when I first heard of it (self-modifying single file). It sure is a good way to get started fast.
My wiki has about 1,500 pages (a few MBs of text) and it's still very manageable. I use it for just about all notetaking purposes (you mention taking note about documentaries, it's one use case of mine; but the biggest is by far replacing bookmarks with free form text -- see link below).
The biggest advantage I see over text files is the graph structure you create by linking entries. I'll have a bunch of links at the top of each entry, and I'll add links whenever I feel it'll help me next time I try to find some piece of information.
About managing programming-related info: I have a bunch of code snippets in there too, along with more reference-like notes on concepts.
I've thought about using mind maps in the past, but I find it too limiting (I'd have to have a mind map + text notes in another system, and anyway I prefer something more text-y). But of course it's way better for visualization of the overall structure.
It's been a while, but a few years back I blogged about all this personal wikis idea (and wrote a post or two on using them for programming-related stuff), so if it may be useful: http://www.fsavard.com/flow/tag/wiki/