anon1253

"The fall" and "The stranger" from Albert Camus, arguably the most accessible cornerstones of Existential philosophy, and they really make you think about your position in this world and as a person. The play "no exit" by Sartre is also very interesting, and works well as the audio version by Partially Examined Life (a philosophy podcast).

Very interesting. Way back my old university was also involved in historical document processing https://www.rug.nl/research/portal/files/40224455/Chapter_7.... they also looked at things like writer identification and trying to automatically date the documents using a wide array of hand crafted features. Curious what would happen with some of the newer deep learning models, but the project has been dead for a while http://application02.target.rug.nl/cgi-bin/monkweb?db=All&cm... … as these things go

Yes, but I was being naive and thought the Vega/Epyc/ThreadRipper stuff with the Intel Specter/Meltdown and crypto craze would help them more. I know my next machine will be an AMD one, if only just for wishful thinking

I got in at ~$12 two years ago, was down 26% for most of that (I'm long, and don't care much for intra-day volatility). I hope it will crawl back up, but I'm increasingly bearish on this one.

Without investors pouring money in it, the R&D will stall and that's not something they can sustain. One of the few reasons they haven't been bought yet is because that will invalidate their license sharing with Intel. So I guess the other strategy is to simply bleed them dry. I mean just think about it. They build GPUs, just like NVidia. They build CPUs, just like Intel. They have their own fabrication process, logistics, research, the whole thing. Their chips don't perform much worse, even better in the mid-range tier. Yet AMD is valued at 9, instead of like 5x or even 10x as much. The people with the money are holding a grudge or something, and I can't see them keeping it up for much longer.

It doesn’t work on the 2018 model. No reliable deep sleep state, no trackpad or track point on the model with NFC. Lenovo refuses to acknowledge both, so it will probably not get fixed. Also, the sound and webcam are aweful (think tin can and potato) … not something I expected from a 2750$ machine; but Netflix and conference calls will be painful at best. I also tried the Carbon X1 in 2015 I think (the one with the touch bar) but back then it only got 1,5 hours of battery, and I ended up returning it. This time it’s collecting dust in a drawer, probably indefinitely.

Long ago I wrote a blog post as an introduction with an identical title: https://joelkuiper.eu/semantic-web

At our company we still use Semantic Web (or rather, RDF) for inference and annotation with medical ontologies (UMLS, Gene Ontology, Human Phenotype Ontology, etc). The ease of use of triples + SPARQL (basically a PROLOG-ish unification scheme) is really powerful (and quite performant when using Jena/Fuseki with Lucene as a text index). But it's a far cry from the "dream" of semantic web like federated queries and OpenAnnotations (now just W3C Annotations). Still, every time someone implements an EAV scheme without even considering an RDF triple store I cringe a bit.

I recently wondered the same thing to replace my 15" 2014 Macbook Pro Retina. I went with the 2018 Lenovo Carbon X1 (16GB, WQHD, i7) and ... it's awful. Linux doesn't work due to a bug in the trackpad drivers, for which there is no reliable fix yet. And, I personally just can't stand Windows (that's a whole different rant). Hardware wise: the sound quality is so horrendous that even watching youtube is a no-go (think dollar store earbuds). That's on low volume, on medium-high volume, in addition to the audio quality, the whole case resonates making it very uncomfortable to even type. And, even though the battery life is rated at "15 hours", with just normal browsing and text edit I get 4 tops. Also it gets really really hot, for no reason (CPU < 10% utilization) which makes using it on my lap a no go. Some of this might be forgiven if it was actually faster, but it isn't. In day to day use it feels /slower/ than my 2014 machine, by quite a big margin (opening files/apps, input latency, jittery animations, even things like running an IO intensive task locks the whole machine, etc) ... that's probably just Windows though. I'm too late to return it, and if I were to sell it on craigslist or something I would probably not recover the costs reasonably. So for me the answer is "no". Nevermind the atrocious support Lenovo gives here in Europe. I ordered it end of February, I got it 30th of March. I ordered the extended warranty, but they want you to register the serial number within 30 days. Which was impossible since I didn't have the machine, the phone number was unresponsive, and the email replies took several days and got back with broken English and non-solutions to the problem. So that was 300 euro for extended warranty down the drain right off the bat. Mind you this was ordered from their official website (which also, incidentally, doesn't work in Firefox with uBlock Origin and uses the /worst/ payment gateway I've ever seen).

I'm probably going to try to get the latest 2016 (I think?) Retina model if my 2014 machine breaks, and see how long that lasts.

I know the barrier to entry is enormous, and there are fundamental problems with doing it better than Dell etc (patents), but a hardware startup that builds better laptops would be great. It feels so silly, but it's a solid reminder for me that consumer hardware progress has definitely stalled; a 2014 machine performs equally, if not better, than a 2018 one in the same price range.

I /just/ got mine in the mail (i7, 16GB, WQHD non-touch, non-IR webcam, 1TB SSD). My comparison is a 15" Macbook Pro Retina (2014). Some initial impressions: Build quality is good, it feels solid yet light. Minor nitpick is that the screen doesn't retain its position well if you hold it in your hand. I'm not known to be gentle with my equipment, and it gets thrown in bags, used in the freezing cold, etc; it's a consumer device with limited life span, I know that going in. The trackpad is one of the best I've seen on a Windows laptop, but still no match for the Macbook (although could be my muscle memory). Also I love the aesthetics of the thing, it looks and feels professional and doesn't have any of the frills "gaming" stuff usually has. There was only one Intel sticker, which I managed to peel off without residue (what's up with those stickers...). The white backlit keyboard is a nice touch, which is overall amazing to type on. I still can't deal with Windows though (it just feels so sloooow), but I'm reluctant to install Linux right now because of a bug in the trackpad drivers (it becomes unresponsive) if you have the NFC option (which I do). I'll wait a couple more months for that to get sorted out. Right now I'm running Linux (Ubuntu 17.10) in VMWare Workstation 14, but that's also very slow (noticeable input lag when typing or dragging windows). But that's all software, I'm sure that will become better over time. The bad though: the audio quality is awful, I mean a 2014 Macbook Pro is bad ... but this is a whole new level. The case even vibrates/resonates with the volume turned up a little bit, and the whole thing sounds like a tin can. Also it gets REALLY hot, as in uncomfortable to use on my lap. The fan curves probably could also use some tuning, it goes on and off often, which I dislike over a continuous sound and would probably help the thermals too. Although, I haven't done any benchmarks yet to check for throttling. I was hoping it would replace my aging Macbook, but it'll probably end up in a drawer until I squeeze the last bit of life out of a 2014 machine, which is in my opinion still the best laptop ever build. The new Macbooks are not really an option (even if I could justify the ridiculous costs) due to lack of USB type A/B ports (which I need for astrophotography), and the annoying sound of the keyboard.

Again with the offensiveness. I'm not sure why you're like this because you have not given any argument to your strong reactions, and are apparently judging me on a myriad of things (even equating me to a dog ffs) without even a shred of explanation. Fyi I live a happy life and am successful at what I do. I'm seriously beginning to doubt that for you; if so I do really hope you'll find happier times. That's what empathy is.

I'm sorry I hurt your feelings. I do feel "Nothing worth learning will be finished learning before you run out of joy for it." is terrible advice and reinforces a believe that's non-congruent with my life experience. But that's my life, and your life is yours. I am trying to let your knee-jerk offensiveness slide, because you obviously feel strongly about the topic; but out of context it almost reads like a threat which I do not appreciate.

I'm sorry you had such a bad experience learning things. Really, that's probably the worst way to learn a language. Ideally language is acquired, not learned. It's a passive process governed by exposure, rather than repetition. http://www.utesinternationallounge.com/language-acquisition-...

But even with skills that do require solid spaced-repetition (like factoids, and probably only factoids) if you run out of joy: what even is the point. Maximize misery in life?

Some interesting concepts to consider: K-anonymity, ℓ-diversity, t-closeness.

From the paper (https://www.liebertpub.com/doi/full/10.1089/bio.2014.0069) I wrote a while ago:

While the risk of re-identification (of a record or individual participant) might be virtually non-existent with synthetic data, one could predict unknown attributes of a known individual, given an ideal model of synthesis. In other words, an attacker could find unknown attributes of some individual with a certain probability by looking for the closest match in the synthetic data. This is known as attribute disclosure.

There are several methods for quantifying attribute disclosure, most notably t-closeness, which is defined as: An equivalence class is said to have t-closeness if the distance between the distribution of a sensitive attribute in this class and the distribution of the attribute in the whole table is no more than a threshold. A table is said to have t-closeness if all equivalence classes have t-closeness.

In short: the distribution of a particular sensitive value should not be further away than a distance t from the overall distribution.

Using the t-closeness metric circumvents issues associated with k-anonymity and ℓ-diversity. Briefly, k-anonymity states that a certain attribute class should be present in at least k records, which introduces ambiguity in the data set. However, if each of the k equivalence classes are the same, properties could still be resolved simply by elimination. The ℓ-diversity metric circumvents this problem by adding a further requirement: in addition to the class to being seen in k records, these records must have at least ℓ ‘well represented’ values. But if an attacker knows the real-world distribution of values, then attributes could still be disclosed with a certain probability, simply by combining different data sources

It was more or less the basis of my PhD in epidemiology that I dropped out of: https://joelkuiper.eu/academic-publishing (Most academic publishing isn't academic (and how to deal with it))

Agreed. I was not trying to imply watching Netflix or doing heroin is the correct way to go about this. But I sorta implied the context of learning a new skill. Like the sibling-post to this indicated: it's about the reward mechanism. But all too often I see people struggling to do something and not really get any satisfaction out of it. The key to learning anything, for me at least, is that it has to be self-rewarding or at least be self-motivating. Just today I did some SMD soldering to try and fix my SO's old discarded Macbook Air, will it fail: probably. Is it hard? you bet ya. At least for me right now. But, I thought it was fun to learn and fiddle with it. I could just as well have decided to learn to play the Cello, or some other thing. Which would probably have been equally "hard", but not as enjoyable for me. And that's the thing I guess: find some heuristic or compass for things that make you go "hey, that would be fun to be able to do" and then push through it. The reward will be greater, and ultimately the energy spend will feel less. For me personally, I know I have very little energy in me. I get 2-3 hours of good concentration per day. Tops. Then it's back to solid sleep. I don't know how people can do hard things for 8 hours straight, but I know it's not for me. (tangentially I think most people can't, they just lie or goof off, and sleep deprivation/burn-out/depression is I think the biggest culprit in our modern society). So I've become very aware of the things I'd like to put my energy in. Like fiddling with electronics, machine learning, philosophy, or astrophotography. But I bet most people would find those things tedious and annoying. So it's up to you :-)

There is an important heuristic to make it much more pleasant though: do the things you like and celebrate the successes. Looking back at some of the things I learned, yeah it was tedious and downright frustrating sometimes. But doing these things now I also feel the reward. Pick the things you think are fun and enjoyable, there is no greater frustration than learning something that ultimately doesn't pique your interest. In my case, especially in high school, I disliked learning foreign languages (apart from English, of course), but I enjoyed chemistry and philosophy. Obviously I put more time into the latter, and worked through all the hurdles and headaches, but it was fun getting to know that stuff. I still only speak two languages. If figuring out T-shirt math isn't your cup of tea, then just don't.

I often feel that people see hardship as a virtue. You /must/ feel shitty, otherwise you're not worthy. And, I don't think that's even remotely true in the long run.

Really my only advice to anyone who wants to learn a new skill: if you start to feel reluctant; just stop. Really. Only do the things you ultimately enjoy. Why put yourself through tedious things in your adulthood. The world is a big place, I'm sure there is something you like doing. Just do that. Don't beat yourself up over it. I've never learned to play an instrument, and suck at countless things; and that's fine. You'll notice that you will quickly become better at the things you enjoy, compared to the tedious ones.

If ImageMagic isn't your thing and like a GUI but don't like Photoshop or the GIMP I really recommend PixInsight (http://www.pixinsight.com/). It's normally used for astronomical image processing but it's well build with some advanced stuff in there. Unfortunately not free, but people have to pay the bills!

Heh. I wrote a paper about this a while ago https://www.liebertpub.com/doi/full/10.1089/bio.2014.0069

I have no expectation that my online learning will amount to anything other than just plain fun. I learned, to some extend, astrophotography and astronomy, day trading, machine learning, and many other minor skills on just an undergraduate (BSc) degree in AI. I have absolutely no illusion that anybody in their right mind will ever hire me on just the online learning. It's just for fun. I didn't know how to do something, now I do. That's all there is to it I think. The rest is mostly just luck and having a big mouth.

https://www.resilio.com/ (formerly bitorrent-sync)?

so immutable, like datomic? https://www.infoq.com/articles/Datomic-Information-Model

Or more like federated SPARQL on RDF? https://www.w3.org/TR/sparql11-federated-query/

Perhaps more like EDN since it doesn't have a runtime. But yeah, it's s-exps with curly braces. Which in my opinion, look worse than round parentheses … but that's opinion

https://github.com/edn-format/edn https://learnxinyminutes.com/docs/edn/

Hume argues this in “enquiry concerning human understanding” https://plato.stanford.edu/entries/hume/#Cau

TextEdit or org-mode, then forget I made them or even don't save them

The waves come from synchronicity of neurons "firing". When neurons fire there is a flow of ions that causes a potential difference. If a lot of this happens at the same time with some periodicity you can measure this. But it would be like looking at a CPU running some math operations and determining "there is periodic activity in the ALU" (which could be due to memory reads). Now this is a poor analogy because a single neuron doesn't do "one thing" it's massively distributed. My go to argumentation for "how the brain works" (and thus consciousness) has been that it's a massive coincidence detector that tries to encode these coincidences in spike train activity using spike train dependent plasticity. In doing so the brain echoes the coincidences of the neural (sensory) input, and since these encode for some "real" cause-effect you can predict the future: memory is "echoing" in a neural substrate, consciousness is exploiting those "echos" to try to predict the future. I wrote it up in 2011 https://www.dropbox.com/s/huol1vf4j1fs1ll/mind_matters.pdf?d... I've never seen anyone poke holes in this, and even hints at the details of this paper. Guess I chose the wrong career somewhere.

Hugo Boss, Kodak, Volkswagen, Siemens, Ford, IBM, IG Farben/Bayer

All of these are still around and were much more involved than Ingvar Kamprad was at the time.

For those curious about Lack server gear https://wiki.eth0.nl/index.php/LackRack

I was lucky enough to visit a private game reserve in South Africa for a few days. One of the things I saw was a pregnant ex-Zebra being eaten by lions (including the fetus that was dragged to the shade under a bush by other Lions). The guide explained that what likely happened is that the lions tried to separate the pregnant zebra from the herd and make her go down slope. The added weight of the fetus makes maneuvering down slope harder, especially when trying to make tight turns, giving the lion the edge. It was fascinating (although a bit gruesome) to see animal behavior in action that way.

"I'd rather cry in a Ferrari"

Sound could be a red herring