Thanks for visiting! You’ll find a bunch of musings I’ve been writing around these parts since the early 2000’s. Lately, I’ve been reviewing a lot of books. But I also write about code. But really, you’re just here to see pictures of Benson.
In the early 2000’s, one of my favorite punk bands was Tsunami Bomb. I followed them up and down the West Coast, going to a ton of shows and meeting a lot of cool people in the process. They went on hiatus in 2005. In 2009, the had a reunion show up here in the Bay Area, so I went and took a number of photos.
(Interestingly, they reformed again in 2015 with a slightly different lineup… and I sadly haven’t gone to see them live yet).
Anyway, they recently had an Instagram post celebrating their anniversary and posted one of my photos. Nice!
The premise: a baseball fan fondly recalls his childhood memories of obsessively opening and collecting packs of baseball cards.
While watching an A’s game one afternoon at the Coliseum (which he rightly describes as a “post-apocalyptic crater ringed with hot dog stands”), he wonders what the players featured on the cards he collected as a kid were doing with their lives after their baseball careers had ended.
After purchasing a pack of cards on eBay from 1986, (the first year the author remembers having baseball cards), he sets off on a road trip across America to find and hopefully meet the 14 players featured in this 30-year-old card pack.
High jinks, hilarity and even important life lessons ensue.
This was just a great read and I highly recommend it for any baseball fan. Check it out on Goodreads.
I recently wrote a simple hook for React to automatically detect a device’s dark mode preference (as well as any changes to it) and style your web app accordingly, using something like ThemeProvider from styled-components.
It was developed as part of a side project I was hacking around on using my personal React Starter Kit, which is my own React project for quickly getting prototypes and side projects up and running.
In light of current events, I’ve found myself doing it much more than usual. However, I’ve never really been able to explain why I’ve enjoyed it so much but I’ve felt there is something relaxing and even meditative about it.
Adam Hanley randomized two groups of college kids and had half read Thich Nhat Hanh’s instructions for mindful dish-washing while the others read simple, mechanical instructions.
After the students washed the dishes, members of the group that had read mindfulness teachings reported having a better experience, a joyful experience, and had lost track of time.
Hanley’s study was published in 2014. Some notes from the abstract are below:
This study sought to investigate whether washing dishes could be used as an informal contemplative practice, promoting the state of mindfulness along with attendant emotional and attentional phenomena. We hypothesized that, relative to a control condition, participants receiving mindful dishwashing instruction would evidence greater state mindfulness, attentional awareness, and positive affect, as well as reduce negative affect and lead to overestimations of time spent dishwashing. A sample of 51 college students engaged in either a mindful or control dishwashing practice before completing measures of mindfulness, affect, and experiential recall. Mindful dishwashers evidenced greater state mindfulness, increases in elements of positive affect (i.e., inspiration), decreases in elements of negative affect (i.e., nervousness), and overestimations of dishwashing time.
Happy April Fools’ Day. This post is no laughing matter because it deals with IE11. 🙀
Awhile back, we had an issue where visitors to our site would hit our landing page and not see anything if they were using Internet Explorer 11. The skeleton layout would appear on the screen and that was it.
Debugging the issue using IE11 on a Windows box proved to be difficult. Normally, we open up the inspector window, look for an error stack and start working backwards to see what is causing the issue.
However, the moment I opened the inspector, the site would start working normally again. This lead me down a rabbit hole and I eventually found a relevant post on StackOverflow: “Why does my site behave differently when developer tools are open in IE11?”
The suggested solution was to implement a polyfill for console.log, like so:
Interestingly, we didn’t have console.log statements anywhere in our production build, so I figured it must be from some third party library that we were importing. We added this line of code at the top of our web app’s entry point to try and catch any instances of this. For us, that was located at the following path: src/app/client/index.js
After rebuilding the app, things were still broken, so the investigation continued.
We eventually concluded that the issue had to do with how our app was built. Our web app is server side rendered and we use Babel and Webpack to transpile and bundle things up. It turns out, Babel wasn’t transpiling code that was included in third party libraries, so any library that was using console.log for one reason or another would cause our site to break.
(The fact that IE11 treats console.log statements differently when the inspector is open vs. not is an entirely separate issue and is frankly ridiculous.)
Knowing this, we were eventually able to come up with a fix. We added the polyfill I posted above directly into the HTML template we use to generate our app as one of the first things posted in the head block. The patches console.log so that it’s available in any subsequent scripts (both external or not) that use it.
In light of the current COVID-19 pandemic, I’ve been reading “Spillover: Animal Infections and the Next Human Pandemic” by David Quammen, published in 2012 (!!). It takes a look into various zoonotic viruses that make the jump from animal to human. There have been a number of passages that have just jumped out and resonated with me as I’ve been reading.
One further factor, possibly the most crucial, was inherent to the way SARS-CoV affects the human body: Symptoms tend to appear in a person before, rather than after, that person becomes highly infectious. The headache, the fever, and the chills—maybe even the cough—precede the major discharge of virus toward other people. […] That order of events allowed many SARS cases to be recognized, hospitalized, and placed in isolation before they hit their peak of infectivity.
And a few paragraphs later:
“That probably helped account for the scale of worldwide misery and death during the 1918–1919 influenza: high infectivity among cases before they experienced the most obvious and debilitating stages of illness. The bug traveled ahead of the sense of alarm. And that infamous global pandemic, remember, occurred in the era before globalization. Everything nowadays moves around the planet faster, including viruses. If SARS had conformed to the perverse pattern of presymptomatic infectivity, its 2003 emergence wouldn’t be a case history in good luck and effective outbreak response. It would be a much darker story. The much darker story remains to be told, probably not about this virus but about another.”
One section of the book that was especially chilling involved the monkeys that inhabited the sacred monkey temples on Bali. In 2014, Kerry and I took our honeymoon there and I had even posted about the crazy monkeys: “While cute looking, the monkeys here are ridiculously aggressive. It was a bit scary!“
Anyway, the monkeys on the island are all apparently infected with herpes B, which kills nearly everyone.
The monkeys aren’t shy about accepting, even demanding, those handouts. They have lost their wild instincts about personal space. Enterprising local photographers run a brisk trade in photos of tourists posed with macaques. “And here’s me in Bali, with a monkey on my head. Cute little guy, just wanted that Snickers bar. But the cute little guys sometimes bite and scratch.”
Engel, Jones-Engel, and their colleagues gathered two interesting sets of data from this place. They surveyed the monkey population, by way of blood samples; and they surveyed the human workforce at Sangeh, by way of interviews and also blood samples. What they found says a lot about the scope of opportunity for virus spillover between Asian monkeys and people.
The team drew blood from thirty-eight macaques, of which twenty-eight were adults, the rest youngsters. They screened the blood serum for evidence of antibodies to herpes B, the same virus that killed William Brebner and most of the other people ever infected with it. The results of the lab work were chilling: Among adult long-tailed macaques at Sangeh, the prevalence of herpes B antibodies was 100 percent. Every mature animal had been infected.
But, there is good news!
The researchers merely estimated that there must be thousands of monkey-bitten tourists walking away from Sangeh each year—and Sangeh is just one such Balinese monkey temple among a handful. The odds of a human contracting herpes B under these circumstances seem vast.
But it hasn’t happened, so far as anyone knows.
I recommended the book to my dad and he asked if it had a happy ending. I shared this passage toward to end of the book with him.
“These scientists are on alert. They are our sentries. They watch the boundaries across which pathogens spill. And they are productively interconnected with one another. When the next novel virus makes its way from a chimpanzee, a bat, a mouse, a duck, or a macaque into a human, and maybe from that human into another human, and thereupon begins causing a small cluster of lethal illnesses, they will see it—we hope they will, anyway—and raise the alarm.
Whatever happens after that will depend on science, politics, social mores, public opinion, public will, and other forms of human behavior. It will depend on how we citizens respond.”
He replied simply, “so much for the happy ending.”
—
I ended up rating this book 5 stars on Goodreads. I probably wouldn’t have discovered it if not for the current global pandemic, but it is something I think I’d have enjoyed before everything changed. David Quammen looks at a number of zoonotic diseases (SARS, Lyme, and AIDS among them) and their fascinating histories.
I’ll admit, it’s been awhile since I’ve seen the International Space Station pass overhead (it’s something I loved to do in the past).
While reading about Elon Musk’s ambitious plan to build a constellation of over 40,000 satellites for providing Internet coverage, I discovered a pretty awesome website for tracking viewing opportunities for his Starlink constellation, as well as other notable objects in orbit (such as the ISS):
See a Satellite Tonight is a project put together by James Darpinian, that shows you which satellites will be visible in your location per the next few days. As an added bonus, you can view where in the sky the satellites will pass overhead using Google Streetview. It’s pretty neat!
On the off chance that the SpaceX Starlink constellation is passing overhead, check it out — you’ll see a train of (as of this writing) 60 satellites appear overhead.
Due to weather and lighting condition in Oakland, I haven’t been able to see it yet, but my dad sent me the following message after using the same website:
Made a point to get up early this AM to watch for Elon’s Starlink. Wow, what a sight! 60 satellites in a row. Just thinking about all the implications of this. Definitely a visual I’ve never seen in my lifetime! Kind of surreal, actually.
I’m always searching for better ways to improve my workflow, increase productivity, and just generally learn new and exciting things. (Besides, it’s part of having a healthy growth mindset.)
We’ve had some big changes on our team during the past year and I’ve felt like I’ve needed to step up when it comes to reviewing code that my fellow colleagues write. While searching for some ideas on how to improve my code review skills, I discovered a blog post from 2018, entitled “Code Review from the Command Line“.
This blew my mind and really helped reframe how we engineers should approach code reviews:
When I ask that other people review my code, it’s an opportunity for me to teach them about the change I’ve just made. When I review someone else’s code, it’s to learn something from them.
Jake, the author of the above post, goes on to describe his setup and custom tooling for conducting an interactive code review.
He uses custom git alias to see which files have changed and how many changes there are, a custom script that visualizes how often the files within the pull request have changed over time, and another custom script that can visualize the relationship between changed files.
All of these go above and beyond the call of duty for reviewing code, but it’s stuff that decreases friction and can make a sometimes tedious process much more enjoyable.
I’ll be implementing some of these ideas into my own workflow in the near future.
“Talking to Strangers” examines how our internal and cultural biases affect our interactions and perceptions of the people around us.
Early in the book, Gladwell mentions a study that gets right to the heart of the book and was really eye opening for me.
It’s a study into the “illusion of asymmetric insight” and shows us how we think we’re good an interpreting what a stranger is thinking or their intentions (spoiler: we’re actually really horrible at it).
Participants were required to complete a set of words with missing letters and then asked what the results say about them.
For example, someone was given “TOU _ _”. Some people would fill in the blanks as “TOUGH” and others would put “TOUCH”.
Afterward, the participant was asked if they think these results reflect their beliefs and core values. Nearly every participant said their word choices were random and had no relation on how they view the world.
Then they were given a random set of words from other people and asked the same question: What do you think these word choices say about these strangers?
Everyone had a strong opinion within literally minutes of being asked the same question about themselves! “Whoever wrote these sounds pretty vain“, or “this person sounds very obsessed with money and power.“
Crazy, right?
The book is full of studies like this, as well as specific examples from real life interactions like this (some with very tragic consequences) and takes a deeper look into why things might have played out the way they did — from a traffic stop in Texas that went very wrong, broken diplomatic promises before World War II, a high-profile sexual assault that occurred at Stanford, and even looking into the motivations of people who try to commit suicide and our collective misunderstanding as to why and where these things happen.
I went into this book not knowing exactly what it was about. I thought, “Oh! New Malcom Gladwell book and it seems to be getting some good reviews, let’s go for it”. It took around a chapter or two for me to really get into the book and see where it was going, but when things finally clicked for me, this was fascinating and enlightening look at every day interactions.
You Look Like a Thing and I Love You is a great, quick read for anyone who is even remotely curious about what things like AI, machine learning or neural networks actually mean and how it affects your day-to-day life.
Whether it’s facial recognition, to self-driving cars, to the search results you get from Google, this book describes the different types of machine learning algorithms, often in a humorous way (the first few pages deal with the author trying to generate pick-up lines using a neural network — hence the title of this book).
It’s a quick read and dives into some of the limitations that machine learning algorithms are bound by and how machine learning algorithms can be tricked, return results outside the parameters of a problem, or even cheat (e.g., when one AI agent was given an objective to minimize the number of times a character died in a video game, it found out how to simply pause the game).
One particular section of the book talks about the recently released GPT-2 data model by OpenAI, which can be used to generate fairly intelligent and coherent sounding blocks of text. It prompted me to try and run the model on my own machine.
After giving the model a prompt of “machine learning can be scary,” the computer responded with the following block of text:
“The problem is, it’s easy to forget that we can’t avoid the problem with software. It’s often hard to avoid the problem, but knowing how to avoid it is not the same as knowing how to avoid it. The problem is, the problem is easy to avoid, but the problem is hard to avoid.”
Do we need to worry about robot overlords any time soon? Probably not.
This is a book that I’d recommend to both people who are tech savvy and to parents who might still call you with questions on how to turn on a computer… or at least anyone curious to how machine learning affects various aspects of our lives.
It’s hard to believe that I’ve been sending music data to Last.fm for nearly 15 years! Because of this, we can start doing some crazy things… like compiling a list of all top artists I listened to over this entire decade.
We generate copious amounts of data each day and give our personal electronic devices and social networks almost unfettered access to all of it. Everything from how long we sleep, how often we exercise, where we go each day to the types of songs, movies and books we like.
There was one passage from the book that I found both amazing and frightening:
A recent study commissioned by Google’s nemesis – Facebook – has indicated that already today the Facebook algorithm is a better judge of human personalities and dispositions than even people’s friends, parents and spouses. The study was conducted on 86,220 volunteers who have a Facebook account and who completed a hundred-item personality questionnaire.
The Facebook algorithm predicted the volunteers’ answers based on monitoring their Facebook Likes – which webpages, images and clips they tagged with the Like button. The more Likes, the more accurate the predictions. The algorithm’s predictions were compared with those of work colleagues, friends, family members and spouses.
Amazingly, the algorithm needed a set of only ten Likes in order to outperform the predictions of work colleagues. It needed seventy Likes to outperform friends, 150 Likes to outperform family members and 300 Likes to outperform spouses. In other words, if you happen to have clicked 300 Likes on your Facebook account, the Facebook algorithm can predict your opinions and desires better than your husband or wife!
This is one of the main reasons why both Google and Facebook have some of the largest (and most effective) advertising networks on the internet.
They fundamentally know who you are and what you like and know us better than we know ourselves.
Indeed, in some fields the Facebook algorithm did better than the person themself. Participants were asked to evaluate things such as their level of substance use or the size of their social networks. Their judgements were less accurate than those of the algorithm.
Excerpts from “Homo Deus: A Brief History of Tomorrow” by Yuval Noah Harari.
I wanted to play around with Event Emitters in Node tonight. Pretty neat! I’m going to have to figure out a way to incorporate this into future projects.
It gives me a bit more insight into how things like WebSockets work as well.
