Limitarianism: academics is fascinating

This will be a short one, because I decided to pick up a topic that I can’t really say that I understand much, just to talk about something that makes me happy. I was reading a Washington Post opinion piece, Is it time to limit personal health? and that led me to looking into a research project at Utrecht University in the Netherlands, Fair Limits, which is focused on studying the question of whether it makes sense to talk about it.

What I want to talk about is not really about “limitarianism”, which personally I don’t think is that easy to apply meaningfully, or the tax rate discussion raised in the Post article, but really the idea that people have enough resources to actually launch a philosophical “program” to just think and write articles about this topic to get to the bottom of whether it’s really worth pursuing.

I love this type of academics!

Maybe it’s because it reminds me of some types of good fiction where the author will come up with a concept and just try to build a world around this concept to see if what comes out of the story is something that makes sense.

Maybe it’s because it reminds me of my own Ph.D. where I spent a while just pushing for what you could do if you represented everything as graphs and try to come up with structural patterns instead of numeric patterns. On my Ph.D side, I have to admit that I probably could have another few years to get to the end of it, and I didn’t because I moved to industry. Oh, well…

Anyway, thank you researchers out there for giving their best try at ideas!

People’s aversion to OOP is odd

From time to time I read an “opinion article” (just like this one) of why people think that OOP is very bad for the world and everybody should embrace Functional Programming (e.g. Why is OOP Such a Waste?).

I think people make good points about the issue with OOP, mostly centered around statefulness and what could be called an “un-natural relationship between logic containers in the code”. That leads to bugs and learning complexity.

My opinion is a little bit less extreme. While I can’t say that I’ve worked on a lot of “production” functional code, I’ve tried to read enough of it that it is pretty clear to me that there is a non-trivial challenge on how to actually document and structure functional code. I think there are two key pieces around this:

  1. The “dynamic compositional nature” of the code, where code can more easily be used across multiple use cases leads to a more “abstract” approach to coding, which is harder to clearly put into words.
  2. Some activities are much harder to represent without state, leading to developers to do hard-to-read tricks with the code in order to achieve this statelessness required by the approach. It doesn’t necessarily make the code less efficient, just harder to read.

Granted, I’m a big fan of FP. I also agree that makes code safer by default and leads to designs that end up being simpler and more decomposed.

What I don’t agree is to being stuck in this idea that OOP is just terrible, and the abstractions that it enforces are “pure evil”. I think there is value to the types of entities that it generates, the ability that people have to better relate to them, and sometimes the alignment with business relationships (which are often stateful themselves). So I feel like focusing on the bad things is almost like throwing out the baby with the bath water. There are good things about OOP and we should value them.

Probably one day I should revisit this topic with specific examples to share. For now I’ll leave it in this abstract-ish state.

The pandemic and virtual concerts

The COVID-19 pandemic was rough on a lot of different dimensions. But one that I want to highlight is the performing arts. Actually, more specifically than that, I want to focus on some organizations that decided to turn their concerts into virtual concerts.

I really like going to concerts, especially orchestral music, ballet, and opera. But since having kids, I don’t really have time to do it. It’s a big commitment, both in time and monetary. My kids were just never consistent enough in their needs for me to be comfortable buying tickets for something. That was a little sad.

Now enter COVID-19 and all concert places close. But some decide to figure out how to take it to the internet. On those, there were three kinds:

  1. Live concerts – you have a specific time that it starts and ends
  2. On-demand, but time-limited concerts – you have a few days to watch, but you can watch whenever you want
  3. Fully recorded – the concert is available to watch whenever you want and will be available forever (or at least for a very long time).

I think due to licensing costs, most professional performing arts organizations are doing options 1 & 2. Now, especially with option 2, I can watch it again! Which has been pretty amazing when I can. The best one this last few months has been the Pacific Northwest Ballet (PNB). I have to admit that out of those 3 types of performances that I talked above, ballet is the one that I understand the least. But being able to just sit at home, on my living room, and watch an “almost kind of live” concert has been pretty cool.

I hope when we come out of this, the virtual concerts will continue. Right now that’s what the next season seems to suggest, but it’s still a pretty “hybrid” state for the pandemic. So I can’t really tell yet if it will be something that is here to stay or not.

I can’t end this post without being saddened by the arts organizations that were not able to survive this pandemic. Switching gears and being able to figure out the technology and way to interact with the audience during this period was not for everybody. My hope is that things will come back. Just like many restaurants closed during this pandemic will likely be replaced by other restaurants, most (hopefully) of those organizations that closed will either reopen or be replaced by another organization to fill in the gap. We will get through with the pandemic.

Note taking

I spent a lot of time over the last few years thinking and trying out note taking strategies and applications. From Evernote, OneNote, Notion, Roam Research, Obsidian and today I played around a little with logseq (and I’m probably forgetting some others that I’ve tried – not to count Google Docs, Apple Notes, or to go into the to-do tracking tooling).

What am I using today? Roam Research

Do I like it? I’d say, yes. I think better than all the other note taking apps that I’ve tried before. Is it perfect? No. Part of its approach is really not to be perfect and to try to be simple and let you just write. But I’m getting ahead of myself.

Let me maybe start with what I use it for. I’ve been trying to do is two things:

  1. Archive learnings that can then be retrieved later
  2. Planning for things to do, things to write

I feel like Roam is pretty good somewhere in between the two. The main thing that it’s aimed for is for research, where you want to look at a lot of ideas and thoughts, and then try to find the connections between them to build on top of past things. It works well when things are “actively” used because they keep showing up when you try to reference something. So if all you want to use it for is something more like an archive that you want to retrieve specifically later (and not by accident while tying to reference something else), then it can become a little noisy pretty quickly.

On the planning side, there has been a lot of “hacks” that have been added into how to do to-do lists, schedule things in the future, track and manage goals. And I think those can work, but they all need effort. You have to populate something, jump between pages, or create templates with embedded pages to try to reduce this effort. But the unstructured nature of the tool, it ends up being work.

If I think it’s not a great match for what I’m looking for, why did I stick with it for now?

  1. I really like how quickly I can just add information and not have to worry about structure. I was a pretty heavy user of Evernote before and fine tuning documents, document tags, notebooks, and references to documents was very time-consuming.
  2. There is a component to what I do that is nice that I can start connecting dots by using the right tags and seeing what is there. I love the idea that I can do something like [[John Doe]] #FollowUp in the middle of notes and then build a query on “John Doe”‘s page that just shows all the things that I have to follow up with him.
  3. Very fast synchronization between multiple windows. At home I find myself sometimes switching between my work computer and personal computer a lot at night and it’s nice that whatever I write on Roam on one automatically appears on the other.

What I don’t like about it?

  1. Price – it is on the expensive side. I think it’s the most expensive of all tools.
  2. No useful mobile app – there are times where I mostly just want to query my graph on my phone and it’s not easy (I open the web app, but it’s not really meant for mobile). This is not that important today because I am mostly at home all the time, but I can see that being very annoying once I start taking the bus again and wanting to take notes about things then.
  3. Feels slow on feature improvement – a lot of the “modern clones”, like logseq and Obsidian (logseq is very Roam-like, Obsidian has a slightly different approach for some things) have a lot of good features, like templates with variables. Roam seems to me to spend a lot of its time on community building and not as much on externally facing feature development.

Some people are concerned about privacy and I agree that it makes sense to be concerned about it. Just not really something that today prevents me from using it.

Maybe one day I’ll post here all the pieces that I’ve added to my Roam to make my workflow faster. For now, I’ll stick with it and see what it will take me.

Reading to learn

I’ve read a lot of different books and articles that highlight the importance of reading all the time to increase your knowledge and the most successful people are the ones that are constantly learning.

I’m going to agree that learning is important. But I think I have a slightly different take on what learning really is and how to do it. Actually, it’s not really novel, just something that I feel like a lot of these articles forget to emphasize.

The key concept that I believe is that we need to learn by doing. Just reading something and not putting it into use does not give you actual learning and I don’t think it is really that useful. Or else, considering the hours that the world spends reading Facebook, Twitter, WhatsApp, etc. we would be a very enlightened society. I don’t think we are quite there.

One consequence of doing it is that we can’t learn by just discussing the quantity of books that you read a day/week/month. More books can actually be the opposite as I’m going to claim (and I’ll weaken this claim a little below) that you are probably wasting a good amount of your time skimming through important information that you will just end up forgetting and never taking advantage of.

There are a couple of exceptions to this statement that come to mind:

  1. Reading for empathy sake: there is a good amount of research that supports the reading fiction is good for improving your empathy, your ability to put yourself in she shoes of somebody else (because that’s what you are doing reading those books). For that use, actually reading is all you need to do.
  2. Reading for building connections: there are some cases where you don’t really have a way to put something to practice directly, but you may do it by using that reading to then nudge your brain to connect concepts that you didn’t connect before. So you may be able to work on the concepts of book A and by reading book B and continuing to work through book A’s ideas, you will find yourself actually being able to connect A to ideas in yet another book C, because B provided you that mental bridge.

I think the most important thing to think about is really to spend time doing things.

Even if what you read is fiction only, spend time with it. Think about how the author develops the story or the relationships, and consider how that could help you develop relationships around you. Maybe take some time and rewrite a chapter of the book in a way that you think it could have gone. I’ve also seen people spending time actually trying to draw or build things that happen on the book, or cook the food on the book, taking you even deeper into the empathy that you get from it.

Yes, that will most certainly take time out of the time you’d be reading. My thesis here is that this is a good thing. Quality beats quantity.

Another side from it is that it will keep making the world better in aggregate. If most of us are just sinks for knowledge, or just filters of knowledge, then knowledge is not being built as quickly as it could be if we were all producing our own dimension to it, adding a little bit of insight and connection to the world.

Background music playlist-making frustrations

From time to time I decide that I want to listen to music while working. It’s not that often because my calendar is usually filled with meetings, so the best I often can do is to listen to music at the beginning of the day.

But today I had a big block without meetings so I decided to go for it and build new playlists of things to listen to. And that, for me means classical music. So I went to Spotify and did some research on what to listen to. When I don’t have an actual idea in mind, I often open their “new releases” playlist and then select a couple of albums from there to listen to.

Maybe let me step back and explain something that annoys me deeply about some (many) classical music playlists, especially the ones that are created by algorithms: they usually don’t include whole pieces, but just a movement of a piece, and then another movement of a different piece. That’s now how I listen to classical music, and I think that’s not how anybody should listen to classical music.

So back to my method: I’ll then go to each song that seem interesting and open the album to get the whole piece (and sometimes the whole album). So far so good, right? Well, not really. Thank you Spotify! Here are some examples:

I select an entry from the playlist…
I get a single?
Another example…

I had a lot of examples I could place here. I don’t know who it to blame for this, but some process is setting up tracks from actual albums as singles, so even if I wanted to listen to the whole piece I can’t!

I was frustrated about things like this (and auto-generated playlists) before and did try some classical music-focused services in the past and I’m not sure I was excited enough about those to stick with them. They were more expensive and considering that I don’t listen that often to them and they don’t offer as many integrations as Spotify (and Amazon Music), I ended up giving up on it.

So, well, today I’m ending my day still frustrated.

A new website

So I have a new website… You may be wondering why I did that considering that I rarely update this website? Well, basically I decided I didn’t want to get rid of this website and, at the same time, I didn’t want to pay Squarespace prices to maintain it. So I moved to the slightly cheaper WordPress and let’s see how it works.

Don’t get me wrong, I really like Squarespace. It was easy to use, had way more intuitive navigation and formatting, and it did make my website look better without a lot of effort. So I do feel a little bad that I left, but I couldn’t convince myself to pay almost $200 a year to keep a website that I’m not using.

So, do I have plans for this website? I’ll get back to you on that. I do want to write more and share my ideas more often, but right now I’m not convinced I have the time to do it. Maybe 2020…

Classical Music Streaming

It has been observed by many people that “traditional” streaming services are terrible at classical music.

PCmag: Primephonic Wants to Save Classical Music, 1 Stream at a Time

Forbes: Meet Primephonic, The Streaming Company On A Mission To Save Classical Music

LifeHacker: The Best Classical Music Streaming Service Is Idagio

TechAcute: IDAGIO: The Streaming Service For Classical Music Fans

And they are pretty terrible. Classical music is complicated… There are lots of dimensions in which you can slice and dice the music, because the stronger dissociation of composer and performer, and the greater diversity of well-defined genres. I’m not saying that popular music doesn’t have as much diversity (although it might be true that it doesn’t), just that the taxonomy is not as well developed. Another dimension of complexity is the fact that a piece of classical music often needs to be taken as a complete unit, even though it might be split into multiple tracks (but not always, and not for everybody).

So enter the latest contenders, Primephonic and Idagio. How do they stack?

TL;DR: they are certainly better at handling classical music than the “standard” streaming tools. But they are far from perfect. And their “imperfection” is inconsistent. IDAGIO has a big defect (at least on the iOS client) of not supporting today gapless playback, so between tracks you get this short gap which is very annoying. This makes Primephonic the winner in my opinion, but not by much.

I started a trial on each and decided to do some comparisons for how I would use it. Here are the use cases that I tested:

  1. Query for a standard piece with an expected high number of recordings

  2. Query for a standard piece with less recordings

  3. Query for a series of pieces with low number of recordings

  4. Query for ensemble

I also discussed a couple of features related on how it is to listen to long pieces, make playlists and discovery.

I did not go into sound quality. That requires a fair amount of time investment in an environment where I could listen to the quality, so I just accepted what they advertise (Primephonic 24bit FLAC and IDAGIO 16bit FLAC) and that probably if you want to pay extra for it (for both you pay extra for lossless), you will get reasonably equivalent quality which will be more limited by the source recording than the streaming format.

1. Query for standard piece

beethoven string quartet 14

beethoven string quartet 131

(refers to Ludwig van Beethoven’s String Quartet No. 14 in C# minor op. 131)

IDAGIO:

“131” returns two works

  • String Quartet No. 14 in C sharp minor op. 131 (arr. for Piano) – single recording

  • String Quartet No. 14 in C sharp minor op. 131 – 53 recordings

Oddly, when I was typing it and was at “beethoven string quartet 13” it showed another work

  • String Quartet No. 14 in C sharp minor op. 131 (Arr. for String Orchestra) – 5 recordings

“14” returns:

  • String Quartet No. 14 in C sharp minor op. 131 (arr. for Piano) – single recording

  • Sonata for Piano No. 9 in E major op. 14/1 (Version for String Quartet)

This inconsistency made me ready for what was coming next for the next searches.

Primephonic

“131” returns 0 works! But quite a few albums. That’s what made me decide to also try “14”.

“14” returns 1 work:

  • String Quartet No.14 in C-sharp minor – 93 recordings, but when you click on it it only shows 82 recordings mixed orchestral and quartet. It had a lot of duplicates, but seems to have more recordings than IDAGIO.

2. Query for a standard piece with less recordings

“part festina lente”

for Arvo Pärt Festina Lente

IDAGIO

Not marked as “works” but returns “Festina Lente, for Harp and String Orchestra (1986, rev. 1990) – 5 recordings

Primephonic

“Festina lente” – 8 recordings

Interestingly the recordings have very little overlap.

3. Query for a series of pieces with low number of recordings

“bachianas”

Heitor Villa-Lobos “Bachianas Brasileiras No. 1-9”

IDAGIO

  • Shows (out of order) Bachianas Brasileiras 1-8 with dates

  • In the bottom has repeated 1 & 5 (twice)

Primephonic

  • Shows (out of order) Bachanas brasileiras 1-9 but missing 6

  • Repeated 4 & 5

4. Query for ensemble

“roomful of teeth”

IDAGIO

  • Only had one match for Berio: Sinfonia

Primephonic

  • 3 albums

  • Does have the Berio above, but doesn’t show in the search results (although it is in the metadata)

Other use flows

Recordings

They both have a concept of recordings which is a pair of work+recording, which allows you to add to playlist all movements for a single piece easily. That does create sometimes a little bit of a confusing point of what you are looking at when navigating. Moreover, on IDAGIO they have a concept of a “collection” and you can add “tracks”, “recordings” and “albums” to the collection. Some albums contain a single work, so sometimes you may think that you are adding a “recording”, but it ends up in the “album” because you were actually at the album view.

I think it’s a necessary concept, I just don’t think they cracked the UI component of it.

Playlists

I have this odd use case of creating a “today” playlist, where I accumulate the pieces that I want to listen to today. “Today” doesn’t mean that I’ll be able to listen to all those pieces in a single day and that’s where I have an unsolved issue: I’d love to know the last piece that I listened to on my playlist. Spotify (before my account started being shared with other people in my household) was pretty good at giving me where I was when I left, so, unless I switched to another playlist/album, I could just continue where I left off. Neither IDAGIO or Primephonic seem to do that. Often when I open their app, I start from scratch and I have to figure out where I was. I have a similar note below on playback.

Beyond that, playlists work as expected. You can add tracks, albums or recordings to them. But if you are on an album and you want to add a recording from that album (i.e. multiple tracks at once for the same work), you have to first navigate to the “recording” view for those tracks and then add them to your playlist.

Playback

This is probably one of the weakest points on IDAGIO, which made me decide that today (when I tested it) they are not the winner: it doesn’t support gapless playback. And that’s a big sin especially for classical music where you have a lot of works that have multiple movements that sometimes, by design by the composer, don’t have a break between them. Now on playback IDAGIO adds a break.

Beyond that, I also felt that IDAGIO took a little longer to start playing than Primephonic.

Finally, related to the “starting from scratch” that I mentioned on playlists, I also can never get it to autoplay when I start a new bluetooth connection. For example, my car connects to my phone on bluetooth and then I can play music through the car sound system, like most cars today. Let’s say that I select something on IDAGIO or Primephonic to play. Then I park the car, go get something and then when I get back to the car, I expect the bluetooth to connect again and trigger play on where I was, but that never worked on my tests for any of those two services. Kind of like the “start from scratch”, they just don’t know what to play. I have to go to the app and play from there.

Other Notes

For sure IDAGIO has the most number of features from the two:

  • Music by mood

  • Good music by musical instrument with a very large selection of instruments

  • More selection on pre-built playlists

But I don’t think that’s really enough to make it the winner, but, in technical terms, I believe the gapless playback is probably a smaller missing feature than the features above, so it might not take very long for IDAGIO to be my recommendation.

Ph.D. flashback of the day: scale-free networks

I was reading an article today from Quanta Magazine: Scant Evidence of Power Laws Found in Real-World Networks which refers to a posted article in arXiv: Scale-free Networks are Rare by Anna D. Broido and Aaron Clauset. And that gave me flashbacks of my Ph.D…

While, scale-free/power-law distributed networks weren’t really the main focus on my research, it did influence what I was doing, as it related to graph-structured databases, where a lot of that structure exists and affects scalability of your analysis. But, more importantly, it influenced a collaboration that I had with another researcher on the same department, Steve Morris. His actual interest was really on power-law distributed networks and his belief was that there was signal to be observed from when a network deviated from being power-law distributed.

During one Summer, we sat together and decided that the way researchers were claiming that everything was power-law distributed was by plotting it in a log-log scale and drawing a line through the points. We hypothesized that it was not a very good way to show that it followed the right distribution and we should have an actual statistical test. My proposal was to use bootstrapping and the Kolmogorov–Smirnov test. So we co-wrote a paper on it: Problems with Fitting to the Power-Law Distribution.

We didn’t have as much data to play with as the paper that I mentioned above, but we also did conclude that almost nothing was actually power-law distributed. And, until this date it’s the paper that I wrote with the most number of citations (622, according to Google Scholar).

We were onto something back then… Oh, well…

AI stigma

The other day I was noticing how many things out there tout to be using AI to solve things today and that’s a great thing. That gave me flashbacks of when I started at Amazon, in 2004. Back then I was just finishing my Ph.D. in a machine learning area, dealing with feature extraction on graph-structured databases, keeping a “fond” eye for the future of the web, the Semantic Web, where computers would be able to interact with the web as well as humans and that would be the turning point for what we’ve imagined as AI back then.

But we didn’t call it AI. AI wasn’t seen as a very good term. We talked about expert systems, or sometimes we did mention machine learning. But AI evoked two negative reactions:

  1. From the general population, AI was like 2001’s HAL 9000 or the Terminator, a robot/computer that was going to kill us all.
  2. For the research, and especially professional population, AI was that dream that people had in the past that just didn’t work. But “expert systems” were showing some great results (i.e. very bounded applications for algorithms initially developed, or inspired by algorithms developed for this “AI” field).

That even caused some awkward relationships at work. My manager then was a former IBM guy that was working on the AI team at IBM. A lot of people around me disregarded some of the work that we were doing because it was based on the ideas of this “AI guy”, so it wasn’t going to work.

Fast-forward to today and AI is everywhere. And now things have changed in perspective:

  1. From the general population, the biggest fear is not that it will kill us all, but that it will get rid of all jobs. A way more sensible fear based on things that go beyond Hollywood.
  2. In the research field, there is still some reluctance to call AI, as we are not at the “AI” imaged in the 80s and 90s, the one that failed miserably. We are just on a little bit less specific “expert systems” (or really “expert systems” that can learn from different applications too, but still applied to specific applications).
  3. On the professional field, people want to say that they do AI to say that they are at the edge of R&D and they are not going to be one of those companies that are going to be replaced by other company’s AIs. Yes, just like humans are afraid that they are going to be replaced by AIs, companies are afraid of the same risk.

So I think we are at a more sensible place. I personally don’t like that people are calling now any machine learning system as AI, but maybe that just softens the expectation of where we are going, making us forget a little bit that goal of this human-like machine that can out-think us. I can live with that!