Digital: The perfect undying art
Great paintings deteriorate, great statues erode, fall and break, great literature is forgotten and it's subtleties lost as languages for ever evolve and disappear. But now we have a new kind of art. A type of art that in theory cannot die, it transcends space and time and can remain pristine for ever and ever. That is digital art.
Digital art is pure information. Therefore it can be copied for ever and ever, exactly reproduced for later generations. Digital art cannot erode, cannot break, it is immortal. Thus is the power of bits, so simple zeros and ones and yet so awesome. Through modern AI and Large Language Models we can now store the subtleties of languages in an abstract vectorial space, also pure information, that can be copied ad infinitum without loss of information. Let's think about the future, a future so deep that we can barely see it's horizon. In that future, with that technology we can resurrect languages. However the languages resurrected will be the ones we speak today.
We have a technology that allows us to store reliably and copy indefinitely that technology is called the *Blockchain*. The most reliable and resilient ledger we have today. We have almost everything we need to preserve what we cherish.
Let's think of a deep future.
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AI+Health: An Undelivered Promise
AI is everywhere, or so would it seems, but the promises made for Drug Discovery and Medicine are still yet to be fulfilled. AI seems to always spring from a Promethean impulse. The goal of creating a life beyond life, doing the work of gods by creating a new life form as Prometheus created humanity. From Techne to independent life, a life that looks life us. Something most people refer to as AGI today.
This is the biggest blind spot of AI development. The big successes of AI are in a certain way always in the same domains:
- Image Processing
- Natural Language Processing
The reason is simple, we are above all visual, talking animals. Our Umwelt, the world we inhabit is mostly a world of images and language, every human is an expert in these two fields. Interestingly, most humans are not as sound aware as they are visually aware. Very few people can separate the different tracks in a music piece, let alone identify certain frequencies or hear delicate compressions and distortions. We are not so good with sound, and it shows in the relatively less ground breaking AI tools available for sound processing.
The same phenomenon explains why AI struggles to achieve in very complex domains such as Biology and Chemistry.
At it's core, modern AI is nothing more than a powerful general way to automatically guess relevant mathematical functions describing a phenomenon from collected data. What statisticians call a *Model*. From this great power derives the domain chief illusion: because the tool is general, therefore the wielder of that tool can apply it to any domain. Experience shows that this thinking is flawed.
Every AI model is framed between two thing: its dataset (input) and its desired output as represented by the loss function. What is important, what is good, what is bad, how should the dataset be curated, how should the model be adjusted. For all these questions and more, you need a deep knowledge of the domain, of the assumptions of the domain, of the technicalities of the domain, of the limitations that are inherent to data collection in that domain. Domain knowledge is paramount, because AI algorithms are always guided by the researchers and engineers. This I know from experience, having spent about 17 years closely working with biologists.
Pairing AI specialists with domain specialist with little knowledge of AI also rarely delivers. A strategy that has been tested time and time again in the last 10 years. Communication is hard and slow, most is lost in translation. The best solution is to have AI experts that are also experts in the applied domain, or domain experts that are also AI experts. Therefore the current discrepancies we see in AI performances across domains, could be layed at the feet of universities, and there siloed structures.
Universities are organized in independent departments that teach independently. AI is taught at the Computer Science department, biology at the Biochemistry department. These two rarely meet in any substantial manner. It was true went I was a student, it is still true today.
This is one of the things we are changing at the Faculty of Medical Science of the University Mohammed VI Polytechnic. Students in Medicine and Pharmacy have to go through a serious AI and Data science class over a few years. They learn to code, they learn the mathematical concepts of AI, they learn to gather their own datasets, to derive their hypothesizes, and build, train and evaluate their own models using pyTorch.
The goal being to produce a new generation of scientists that are intimate with their domain as well as with modern AI. One that can consistently deliver the promises of AI for Medicine and Drug Discovery.
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AI+Health: An Undelivered Promise
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El Salvador: The most important country you barely hear about
El Salvador has a significant diaspora, so much that money coming from the US is a major source of income. **Not so long ago you would have been pressed to find a Salvadorian who wanted to go back to El Salvador. Now things seems to be changing.**
El Salavador, used to have one of the highest homicide rates in the Americas, now it looks relatively safe. El Salvador showed an interesting strategy. First boost the economy before handling the crime situation. Crime is indeed a part of GDP, albeit a hard one to quantify. Since it is an economic activity, it participates in exchanges and provides people with activities that supports them and their families. Drastically reducing crime has the effect of creating *'unemployed criminals'* people with a skillset that's hard to sell in a traditional economy.
El Salvador probably did take a hit to its GDP, but that was compensated by the increase in economic activity and investments.
Bitcoin was a big part of that.
Bitcoin got a lot of bad press as a technology only used by criminals, or a crazy investment for crazy speculators. These takes failed to understand the technology and it's potential. What Bitcoin offers is a decentralized, fast and secure payment system for free. El Salvador doesn't have to maintain it, regulate it, or even monitor it. All very costly activities that a small country can do without. Bitcoin is a mathematically secure way of payment.
In a country where road infrastructures are challenging, Bitcoin offers people in remote areas the possibility to pay their bills without travelling for hours. In a country that was unsafe, Bitcoin offered people the possibility to go out without the fear of being robbed.
It also attracted a kind of investors that would go nowhere else. And even if these investment can appear small, for a country like El Salvador it's a big change.
The Salvadorian experiment in a freer economy, crypto-friendly and smaller government, in a time of increasing inflation, has a lot of people watching. In a continent that leaned left for so long, this is a big change.
My opinion is that there would be no Javier Millier hadn't there been a Nayib Bukele before. Argentina has been a bastion of the left for decades. If the libertarian policies of Millier succeed in bettering the lives of Argentinians, we might be on the brink of a major cultural shift in the Americas and then the world.
Argentina is a far bigger country than El Salvador, with far more people watching.
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Applied Machine Learning Africa!
I have been to more scientific conferences than I can count. From to smallest to the biggest like NeuRIPS (even back when it was still called NIPS). Of all these events AMLD Africa is my favorite, by far.
I first met the team two years ago when they organized the first in-person edition of the conference at the University Mohammed VI Polytechnic. I was immediately charmed by the warmth and professionalism, ambition and fearlessness of the team. So much that I joined the organization.
AMLD Africa is unique on every aspect. By its focus on Africa, by its scope and ambition, by its incredibly dynamic, young, passionate, honest and resourceful team, all volunteers. It is hard to believe that this year in Nairobi was only the second in-person edition.
AMLD Africa does the impossible without even realizing it. It has an old school vibe of collegiality, community and most importantly **__fun__** that is so lacking in most conferences today. All without compromising on the quality of the science.
It offers one of the best windows into everything AI and Machine learning happening in Africa. Africa is a continent on the rise. But a very hard continent to navigate because of information bottlenecks. Traveling across Africa is not easy (it took me 28H from Nairobi to Casablanca), there are language barierers separating the continent into different linguistic regions (French, English, Portuguese being the main ones). And just the fact that all too often we do not look to Africa for solutions.
AMLD Africa is solving all that, by bringing everybody together for a few days in one of the best environments I got to experience.
Thank you AMLD Africa.
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Applied Machine Learning Africa!
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GenZ: The Fiscally Aware Generation
I am sitting at Paul's cafe at the airport en route to Nairobi via Cairo for Applied Machine Learning Days (AMLD) Africa (a wonderful conference, more on that later). **In front of me 4 young males, early 20s, they speak loudly in french as they eat the burgers and fries they bought at another restaurant.**
They talk about money.
"You have no idea how much money I lose to taxes", says one of them. "40 to 50%! It's a lot of money, I would make so much more without it". He sees taxes not as a net necessary good, as most have been trained to see it, but as any other cost.
Interesting, that's not the type of conversations you would expect from someone that young. It's not the first time I hear this type of conversation from GenZs. Why are GenZs becoming more fiscally aware than previous generations? I think it comes down to two factors:
- Inflation
- The entrepreneurial culture
Inflation has hit everybody, for obvious reasons. However one constant with inflation is that it hits the poorest hardest. Young people tend to have less money. But that's not enough to raise awareness about a subject that most consider beyond boring. This brings us to the next point: *The entrepreneurial culture*.
As a millennial I witnessed it's burgeoning and blossoming. It started timidly with a few books and blogs, then massive blogs, then best sellers, then YouTube videos and finally podcasts. Not so long ago being an entrepreneur was considered an unwise life choice. Successful people go to work for established companies. Such was common wisdom. However, as the 2008 recession hit and people started to look for more revenue streams, they also discovered the concept that having one's business can also mean more freedom and better financial security.
There is however a big difference between the Millennial Entrepreneur and the GenZ Entrepreneur. The Millennial was still uneasy with the idea of making money and as such would speak about *"making a positive impact in the world"*, the GenZ is not burden in this way. You can see the shift in YouTube ads, today it's all bout how much you will make if you buy this or that business course.
So whatever online business they start, being it drop shipping or whatever, they tend do it in a money aware way. Starting an online business is a hard, the competition is fierce. Naturally, they try to invest their hard earned money wisely. When the tax bill comes, they see it as it is: an unexpected cost that does not necessarily translate to a better life quality. Nothing is free in this incarnation. Some are not even shy about relocating to fiscally advantageous locations like Dubai and making videos about it.
This could be the end of the blissful fiscally unaware generations.
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How Bluwr is optimized for SEO, Speed and Worldwide Accessibility.
TL;DR: Bluwr is Fast & Writing on Bluwr will help you get traffic.
We made some unusual choices while building Bluwr. In an age where front-end web development means Javascript frameworks, we took a *hybrid* somewhat old-school approach. Our stack is super lean, fast, and optimized for ease of maintenance and search engines.
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Most of the website is served statically through python Jinja Template and we use Javascript when interaction is needed, for these cases we use Vue.JS, 100% homemade vanilla JS and JQuery. For looks we use Uikit and in-house custom made CSS.
These choices allow us to have a lighting fast website and have great benefits for our writers. Because most of Bluwr appears as static HTML, articles appear first, readers never have to wait for them to load, and search engines have no difficulty indexing what's on Bluwr.com. This makes everything you write on Bluwr easier to find on the internet. It also means that Bluwr.com loads fast even on the worst of connections. Something noteworthy as even a slight delay in loading can significantly reduce the chances of your article being read.
Our goal is to make Bluwr accessible to anybody on the internet, even on a limited 3G connection.
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