Following on from my last experiment with Hugo, I decided to dabble in a different static site generator (SSG). This time, Eleventy. I've rebuilt another one of my golden oldies, Jaza's World, using it. And, similarly, source code is up on GitHub, and the site is hosted on Netlify. I'm pleased to say that Eleventy delivered in the areas where Hugo disappointed me most, although there were things about Hugo that I missed.
After having it on my to-do list for several years, I finally got around to trying out a static site generator (SSG). In particular, Hugo. I decided to take Hugo for a spin, by rebuilding one of my golden oldies, Jaza's World Trip, with it. And, for bonus points, I published the source code on GitHub, and I deployed the site on Netlify. Hugo is great software with a great community, however it didn't quite live up to my expectations.
I've created a new online home for my formidable collection of 25,000 personal photos. They now all live in an S3 bucket, and are viewable in a private gallery powered by the open-source AWSPics. In general, I'm happy with the new setup.
Theories abound regarding what makes a good dev. These theories generally revolve around one or more particular skills (both "hard" and "soft"), and levels of proficiency in said skills, that are "must-have" in order for a person to be a good dev. I disagree with said theories. I think that there's only one thing that makes a good dev, and it's not a skill at all. It's an attitude. A good dev cares about code.
There are many aspects of code that you can care about. Formatting. Modularity. Meaningful naming. Performance. Security. Test coverage. And many more. Even if you care about just one of these, then: (a) I salute you, for you are a good dev; and (b) that means that you're passionate about code, which in turn means that you'll care about more aspects of code as you grow and mature, which in turn means that you'll develop more of them there skills, as a natural side effect. The fact that you care, however, is the foundation of it all.
I recently finished reading the classic novel War and Peace. The 19th-century epic is considered the masterpiece of Leo Tolstoy, and I must say it took me by surprise. In particular, I wasn't expecting its second epilogue, which is a distinct work of its own (and one that arguably doesn't belong in a novel): a philosophical essay discussing the question of "free will vs necessity". I know that the second epilogue isn't to everyone's taste, but personally I feel that it's a real gem.
I was also surprised to learn, after doing a modest bit of research, that Tolstoy is seldom mentioned amongst any of the prominent figures in philosophy or metaphysics over the past several centuries. The only articles that even deign to label Tolstoy as a philosopher, are ones that are actually more concerned with Tolstoy as a cult-inspirer, as a pacifist, and as an anarchist.
So, while history has been just and generous in venerating Tolstoy as a novelist, I feel that his contribution to the field of philosophy has gone unacknowledged. This is no doubt in part because Tolstoy didn't consider himself a philosopher, and because he didn't pen any purely philosophical works (published separately from novels and other works), and because he himself criticised the value of such works. Nevertheless, I feel warranted in asking: is Tolstoy a forgotten philosopher?
The past decade or so has been touted as a high point for achievements in Artificial Intelligence (AI). For the first time, computers have demonstrated formidable ability in such areas as image recognition, speech recognition, gaming, and (most recently) autonomous driving / piloting. Researchers and companies that are heavily invested in these technologies, at least, are in no small way lauding these successes, and are giving us the pitch that the current state-of-the-art is nothing less than groundbreaking.
However, as anyone exposed to the industry knows, the current state-of-the-art is still plagued by fundamental shortcomings. In a nutshell, the current generation of AI is characterised by big data (i.e. a huge amount of sample data is needed in order to yield only moderately useful results), big hardware (i.e. a giant amount of clustered compute resources is needed, again in order to yield only moderately useful results), and flawed algorithms (i.e. algorithms that, at the end of the day, are based on statistical analysis and not much else – this includes the latest Convolutional Neural Networks). As such, the areas of success (impressive though they may be) are still dwarfed by the relative failures, in areas such as natural language conversation, criminal justice assessment, and art analysis / art production.
In my opinion, if we are to have any chance of reaching a higher plane of AI – one that demonstrates more human-like intelligence – then we must lessen our focus on statistics, mathematics, and neurobiology. Instead, we must turn our attention to philosophy, an area that has traditionally been neglected by AI research. Only philosophy (specifically, metaphysics and epistemology) contains the teachings that we so desperately need, regarding what "reasoning" means, what is the abstract machinery that makes reasoning possible, and what are the absolute limits of reasoning and knowledge.
The Eiffel Tower, as it turns out, is far more than just the most iconic tourist attraction in the world. As the tallest structure ever built by man at the time – and holder of the record "tallest man-made structure in the world" for 41 years, following its completion in 1889 – it was a revolutionary feat of structural engineering. It was also highly controversial – deeply unpopular, one might even say – with some of the most prominent Parisians of the day fiercely protesting against its "monstruous" form. And Gustave Eiffel, its creator, was brilliant, ambitious, eccentric, and thick-skinned.
From reading the wonderful epic novel Paris, by Edward Rutherford, I learned some facts about Gustave Eiffel's life, and about the Eiffel Tower's original conception, its construction, and its first few decades as the exclamation mark of the Paris skyline, that both surprised and intrigued me. Allow me to share these tidbits of history in this here humble article.
I recently built a little web app called What If Stocks, to answer the question: based on a start and end date, and a pool of stocks and historical prices, what would have been the best stocks to invest in? This app isn't rocket science, it just ranks the stocks based on one simple metric: change in price during the selected period.
I imported into this app, price data from 2000 to 2018, for all ASX (Australian Securities Exchange) stocks that have existed for roughly the whole of that period. I then examined the results, for all possible 5-year and 10-year periods within that date range. I'd therefore like to share with you, what this app calculated to be the 12 Aussie stocks that have ranked No. 1, in terms of market price increase, for one or more of those periods.
As a computer programmer – i.e. as someone whose day job is to write relatively dumb, straight-forward code, that controls relatively dumb, straight-forward machines – DNA is a fascinating thing. Other coders agree. It has been called the code of life, and rightly so: the DNA that makes up a given organism's genome, is the set of instructions responsible for virtually everything about how that organism grows, survives, behaves, reproduces, and ultimately dies in this universe.
Most intriguing and most tantalising of all, is the fact that we humans still have virtually no idea how to interpret DNA in any meaningful way. It's only since 1953 that we've understood what DNA even is; and it's only since 2001 that we've been able to extract and to gaze upon instances of the complete human genome.
Image source: A complete PPT on DNA (Slideshare).
As others have pointed out, the reason why we haven't had much luck in reading DNA, is because (in computer science parlance) it's not high-level source code, it's machine code (or, to be more precise, it's bytecode). So, DNA, which is sequences of base-4 digits, grouped into (most commonly) 3-digit "words" (known as "codons"), is no more easily decipherable than binary, which is sequences of base-2 digits, grouped into (for example) 8-digit "words" (known as "bytes"). And as anyone who has ever read or written binary (in binary, octal, or hex form, however you want to skin that cat) can attest, it's hard!
In this musing, I'm going to compare genetic code and computer code. I am in no way qualified to write about this topic (particularly about the biology side), but it's fun, and I'm reckless, and this is my blog so for better or for worse nobody can stop me.
Shortly after arriving in Chile recently, I was dismayed to discover that – due to a new law – my Aussie mobile phone would not work with a local prepaid Chilean SIM card, without me first completing a tedious bureaucratic exercise. So, whereas getting connected with a local mobile number was previously something that took about 10 minutes to achieve in Chile, it's now an endeavour that took me about 2 weeks to achieve.
It turns out that Chile has joined a small group of countries around the world, that have decided to implement a national IMEI (International Mobile Equipment Identity) whitelist. From some quick investigation, as far as I can tell, the only other countries that boast such a system are Turkey, Azerbaijan, Colombia, and Nepal. Hardly the most venerable group of nations to be joining, in my opinion.
As someone who has been to Chile many times, all I can say is: not happy! Bringing your own mobile device, and purchasing a local SIM card, is the cheapest and the most convenient way to stay connected while travelling, and it's the go-to method for a great many tourists travelling all around the world. It beats international roaming hands-down, and it eliminates the unnecessary cost of purchasing a new local phone all the time. I really hope that the Chilean government reconsiders the need for this law, and I really hope that no more countries join this misguided bandwagon.