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.
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.
The premise: each time a certain API method is called within a Flask / SQLAlchemy app (a method that primarily involves saving something to the database), send various notifications, e.g. log to the standard logger, and send an email to site admins. However, the way the API works, is that several different methods can be forced to run in a single DB transaction, by specifying that SQLAlchemy only perform a commit when the last method is called. Ideally, no notifications should actually get triggered until the DB transaction has been successfully committed; and when the commit has finished, the notifications should trigger in the order that the API methods were called.
There are various possible solutions that can accomplish this, for example: a celery task queue, an event scheduler, and a synchronised / threaded queue. However, those are all fairly heavy solutions to this problem, because we only need a queue that runs inside one thread, and that lives for the duration of a single DB transaction (and therefore also only for a single request).
To solve this problem, I implemented a very lightweight function queue, where each queue is a deque instance, that lives inside flask.g, and that is therefore available for the duration of a given request context (or app context).
Communism – or, to be more precise, Marxism – made sweeping promises of a rosy utopian world society: all people are equal; from each according to his ability, to each according to his need; the end of the bourgeoisie, the rise of the proletariat; and the end of poverty. In reality, the nature of the communist societies that emerged during the 20th century was far from this grandiose vision.
Communism obviously was not successful in terms of the most obvious measure: namely, its own longevity. The world's first and its longest-lived communist regime, the Soviet Union, well and truly collapsed. The world's most populous country, the People's Republic of China, is stronger than ever, but effectively remains communist in name only (as does its southern neighbour, Vietnam).
However, this article does not seek to measure communism's success based on the survival rate of particular governments; nor does it seek to analyse (in any great detail) why particular regimes failed (and there's no shortage of other articles that do analyse just that). More important than whether the regimes themselves prospered or met their demise, is their legacy and their long-term impact on the societies that they presided over. So, how successful was the communism experiment, in actually improving the economic, political, and cultural conditions of the populations that experienced it?
I have become quite a fan of Python's built-in namedtuple collection lately. As others have already written, despite having been available in Python 2.x and 3.x for a long time now, namedtuple continues to be under-appreciated and under-utilised by many programmers.
# The ol'fashioned tuple way
fruits = [
('banana', 'medium', 'yellow'),
('watermelon', 'large', 'pink')]
for fruit in fruits:
print('A {0} is coloured {1} and is {2} sized'.format(
fruit[0], fruit[2], fruit[1]))
# The nicer namedtuple way
from collections import namedtuple
Fruit = namedtuple('Fruit', 'name size colour')
fruits = [
Fruit(name='banana', size='medium', colour='yellow'),
Fruit(name='watermelon', size='large', colour='pink')]
for fruit in fruits:
print('A {0} is coloured {1} and is {2} sized'.format(
fruit.name, fruit.colour, fruit.size))
namedtuples can be used in a few obvious situations in Python. I'd like to present a new and less obvious situation, that I haven't seen any examples of elsewhere: using a namedtuple instead of MagicMock or flexmock, for mocking objects in unit tests.
Them robots are gonna take our jobs! Image source:Day of the Robot.
Most discussion of late seems to treat this encroaching joblessness entirely as an economic issue. Families without incomes, spiralling wealth inequality, broken taxation mechanisms. And, consequently, the solutions being proposed are mainly economic ones. For example, a Universal Basic Income to help everyone make ends meet. However, in my opinion, those economic issues are actually relatively easy to address, and as a matter of sheer necessity we will sort them out sooner or later, via a UBI or via whatever else fits the bill.
The more pertinent issue is actually a social and a psychological one. Namely: how will people keep themselves occupied in such a world? How will people nourish their ambitions, feel that they have a purpose in life, and feel that they make a valuable contribution to society? How will we prevent the malaise of despair, depression, and crime from engulfing those who lack gainful enterprise? To borrow the colourful analogy that others have penned: assuming that there's food on the table either way, how do we head towards a Star Trek rather than a Mad Max future?
Most countries have one city which is clearly top of the pops. In particular, one city (which may not necessarily be the national capital) is usually the largest population centre and the main economic powerhouse of a given country. Humbly presented here is a quick and not-overly-scientific list of ten countries that are an exception to this rule. That is, countries where two cities (or more!) vie neck-and-neck for the coveted top spot.
Note: all population statistics are the latest numbers on relevant country- or city-level Wikipedia pages, as of writing, and all are for the cities' metropolitan area or closest available equivalent.
