01 Jan 2022
This is a meta-post to review what happened in 2021.
This year I set out to learn about machine learning for speech recognition. My first milestone was to understand the use of hidden Markov models for speech recognition but I soon realized during the process that my background on signal processing is very lacking, so I spent most of the year learning that.
Still related to my goal, I wanted to start getting familiar with MacOS APIs because that’s the OS I use most day-to-day, so I did a simple project: A Simple Key Logger for MacOS.
I got excited about programming challenges again, especially during the beginning of the year, and ended up learning (or improving my understanding of) some fun problems: Max Area Under a Histogram, Boyer–Moore Majority Vote Algorithm, Maximum Non-Empty Intersection of Constraints.
At work, I had the opportunity to work with process jailing, so I took some time to understand the space a bit: Linux Filesystems Overview, Chroot Jailing, Namespace Jailing. I also worked more with Python and wrote Revisiting Python: Modules to improve my knowledge in it.
Finally I improved the process of managing posts during the draft phase, documented in Writing Posts.
I kept the resolution to have at least one post a month on average, by writing 22 posts. The blog completed 9 years with 144 posts (some of which were ported and translated from my old blog in Portuguese).
The post Linear Predictive Coding in Python received the most unique visits, 893. Overall the blog had a total of 5k visitors.
I didn’t learn nearly enough about machine learning for speech recognition, being focused mostly on signal processing, so I’ll keep this as the main resolution for next year.
As side goals, I want to read a textbook on topology and learn Lean, the proof assistant.
The end of the year is a good time to look back and remember all the things I’ve done besides work and the technical blog. This year was one of temporary hopes with the vaccine rollout but then the realization that the pandemic is not over, as waning immunity and new variants can attest.
The year started with road trips around California, up north in the Redwoods National Park and south in the Joshua Tree National Park and San Gabriel mountains.
For a while after getting vaccinated, I thought things would go back to normal. We felt confident about flying to Colorado and doing a road trip in the southern part of the state.
Closer to year end, more California road trips, this time in the Central Coast.
I read really good books this year, especially in history and physics. I’m thinking of perhaps focusing on those two genres at the expense of other non-fictions for the next year.
This year I also started taking more detailed notes while reading the books, so I can “recall” more things now and hence the summaries below are longer than in previous years.
|Wild Swans: Three Daughters of China by Jung Chang. This is a family-biography relating events that three generations of Chinese women went through in their lives. It starts with the grandmother who lived through the Japanese annexation of Manchuria and the civil war between the Kuomintang and the Chinese Communist Party. The mother and the author lived through the communist regime, including the Cultural revolution.|
The Making of Asian America by Erika Lee. This book tells the history of Asian immigrants and Asian Americans. It covers them more or less chronologically, based on when significant migration first happened: Chinese, Japanese, Koreans, South Asians, Filipinos during the late 19th century and then more recently Vietnamese and Hmong.
A common theme has always been antagonism towards immigrants from these countries, to a much bigger extent than other European immigrants. This manifested in exclusion acts, internment camps and even persecution by mobs.
|London: a novel by Edward Rutherford. I got recommended this book because of another historical fiction I liked, Tolstoy's War and Peace. I learned many tidbits about London, especially its buildings. It’s pretty long but well worth the time and I wish I had read it before visiting London!|
|American Nations by Colin Woodard. This book makes a case that there are 11 distinct cultures in North America, which transcend state borders and even countries (Canada and Mexico).
I know it’s possible to cherry pick historical facts to fit a theory but it was super interesting to revisit American history through this point of view. For example, it's pointed out that some states in the midwest are divided into opposing cultures which makes them swing states in elections.
|The Machinery of Life by David S. Goodsell. This is a short book and contains lots of beautiful and detailed illustrations of parts of the cell. I had only been exposed to abstract depictions in school so it was wonderful to see a more realistic depiction.
Random things learned:
The Pleasure of Finding Things Out by Richard Feynman. This is a mix of Feynman's biography, the philosophy of science and some bits of physics. I'm not a big fan of Feynman's personal life but his account of the atomic bomb development at Los Alamos was very interesting.
I also liked his interview on nano-physics and the effect his dad's conversations had on him, especially on being scientifically minded in life.
The Selfish Gene by Richard Dawkins. I made a point to re-read a book every year. This was my 2021 choice. I re-read Sapiens last year but didn't enjoy it as much. For this book it was the opposite, which means this book is really one of my favorites.
At a high level, the selfish gene theory says that the natural selection process happens at the gene level rather than at the organism or species level.
General Relativity from A to B by Robert Geroch. I saw John Baez recommend this book as a good introduction to General Relativity. It was indeed a good one: the author starts with a simple model (called Aristotelian), then find issues with it and try to fix them with a more elaborate model (called Galilean), which is also not perfect which then leads to the introduction of the Space-time model. The examples with black holes were particularly interesting.
There's almost no math in the book, and at points I found myself trying to "translate" the layman terms into math concepts I know. I believed at some point he was trying to explain vector spaces, for example. I want to find a book that uses some basic math (linear algebra and calculus) but skims though more advanced ones like differential geometry/topology. It did get me really interested in learning these topics!
Our Mathematical Universe by Max Tegmark. I was primarily interested in this book after reading Permutation Cities by Egan, which speculates the wild idea that computation can be carried over without a machine to run it on. Pair that with the idea that we could be living in a simulation and the next logical step is that our universe could just be such a simulation, or more abstractly, that we are a mathematical (which include any simulation program) object. This feels like such a crackpot idea so I was delighted to find a non-fiction book on this.
For the first part of the book I was overwhelmed with information. I knew very little about cosmology and pretty much everything was news to me. For the second part, I had a better prior layman knowledge of quantum mechanics but the possibility that quantum randomness is an illusion and could be explained via multiverse was mind blowing.
Most of the book is dedicated to laying down the current understanding of our universe and that the more we dig, the less "real" it seems and the more "abstract/mathematical" it feels. It then makes the case for the "universe as a mathematical object" at the very end. I think the book adds a lot of substance and rigour to the idea I was hoping to learn more from it.
As in the General Relativity book, I was left wanting to understand the mathematics of physics better. I hope one day to make through Penrose's The Road to Reality which I heard is a difficult read. This is definitely my favorite read of the year.
A Computer Scientist's Guide to Cell Biology by William W. Cohen. This is a short book (100 pages) that covers aspects of cell biology, including definitions, mechanisms like protein production and experiments commonly performed to understand the cell better.
I was personally disappointed by the book, mainly because I was (unjustifiably so) expecting this book to be more of an intersection between Computer Science and Biology and the fact it was quite pricey. There's little Computer Science in it besides some loose analogies with programming. This book is a good introduction to cell biology, perhaps with a selection of topics more likely to be needed to make sense of problems in bio-informatics.
I actually wrote about Cell Biology before (post) with some forceful analogies with programming, but I'm still hoping to read about a more detailed discussion on "computability" performed by biological organisms.
|The Subtle Art of Not Giving a F*ck by Mark Manson. The central idea is to find the balance between not caring too much about things and not being apathetic. It discusses topics like finding the right set of values, learning to reject and be rejected and to live life having with the perspective that it is finite. I like the anecdotes, where the author starts a chapter with the history of a person to illustrate the idea - reminds me of Gladwell's style.|
|Factfulness by Anna Rosling Rönnlund, Hans Rosling, and Ola Rosling. I recall Hans Hosling's energetic TED talk where he shows an animated bubble chart to highlight the fact the world has been getting better. This book is an extended written form of the same idea. I enjoyed the quizzes to test the reader's pre-conceptions and the data driven approach.
Random things learned:
|Permutation City by Greg Egan. This science-fiction explores the simulation hypothesis in great detail. The main character simulates himself in different setups, including with non-continuous time and the simulation cannot tell the difference. It's an amazing thought experiment. It concludes with the idea that simulations can go on without computers to run them which at first made no sense to me but I eventually internalized it and it was revealing.
While the first half of the book has a lot of science/philosophy, the second half is more fiction and it has a lot less plausible events, so I didn't enjoy as much.