Think Forward.

The Misadventures of a Helpful Bionic Arm

Anas Bedraoui, 9 mon.
0 min read.
Once there was a man with a bionic arm that had a mind of its own. One day, while dining in a fancy restaurant, his bionic arm suddenly decided to help. It began pouring water, but missed the glass, showering a nearby cat instead. The cat, startled, leaped onto the chandelier. The man, embarrassed, tried to control his arm, but it enthusiastically started serving bread to everyone, including a bewildered dog outside. The chaos ended with a round of applause from the amused diners and a very proud bionic arm, convinced it was the best waiter ever.

The adventures of Billy (part 1)

The Ren, 9 mon.
Billy liked driving his car To see his friends who lived afar Billy's driving wasn't intricate He never forgot to indicate Except sometimes at roundabouts His indicator would mess about And so did Billy wonder Was it for worse or for better That he should think less But to endure the stress Of never knowing which Turn would make it glitch And so did billy wonder And so did billy wonder

The Ideal

EL MONO MAS GRANDE, 9 mon.
As the biggest ape was at his desk, a small child approached him. He was tiny, much smaller than children his age with clear, sparkling eyes. -"What are you doing", said the child. -"I am writing a book", said the biggest ape. -"About what?" -"The ideal." The child paused a minute, thinking. -"Are you the ideal?" -"No." -"Have you seen it?" -"No." "Then how can you write about something you don't know?" The biggest paused and laughed. -"That is the nature of the ideal.", said the biggest ape. "It can always be perceived, but never seen. When you call upon it, it comes. Never fully, never for long. When you've been touched by it, it is your duty to keep some of it's sent about you." Turning towards the child he added. -"This is how you call the ideal: you think about it, you perceive it and you write about it. So others as well might be touched by it". -"I understand." Thus spake the child.

Four keys to create supervised learning model

Tima EL, 9 mon.
1 min read.
Supervised learning is a strategy in machine learning that enables a model to learn from data without being explicitly programmed. In other words, in supervised learning, the model tries to find the relationship between the "input" X and the "output" Y. Therefore, the first key to creating a supervised learning model is the dataset. **Key 1 : Dataset** Having a labeled dataset is essential, including two important types of information: the target variable Y, which is what we want to predict, and the explanatory variable X, which are the factors that help us make predictions. Let's take an example: imagine we want our model to predict the weather (Y) based on factors like temperature, humidity, and wind speed (X). To do this, we gather a dataset with information from the past, where we already know both the weather outcomes (Y) and the corresponding factors (X). This dataset acts like a box of puzzle pieces. Each piece represents one of the factors, and finding the relationship between these pieces defines the weather. We can represent this relationship as a mathematical equation, like this: Y = F(X), where F represents our model. Therefore, the second key is the Model. **Key 2: Model** The fundamental model in supervised machine learning is a linear model expressed as y = ax + b. However, the real world often presents nonlinear problems. In such cases, we explore non-linear models, such as a polynomial of degree two like y = ax² + bx + c, or even of degree three, and beyond. It's crucial to understand that each model has parameters requiring adjustment during training. Consequently, the two remaining critical components are the cost function and the optimization algorithm. **Key 3 : Cost Function** In machine learning, a cost function, also called a loss or objective function, quantifies the gap between the target and predicted values, signifying the model's error. The aim is to minimize this error to craft the most effective model. **Key 4 : Optimizer** Optimizer forms the core of a machine learning model, representing the strategy to discover parameter values that minimize the cost function. It plays a crucial role in fine-tuning the model for optimal performance.

Part 5/5: PhD - The Eternal Optimist: Next Time Will Be Different (But Not Really)

Anas Bedraoui, 9 mon.
1 min read.
PhD Students: Where Schedules are Fiction and Coffee is King! "Colorful Calendars, Doomed to Fail": PhD students craft rainbow schedules, thinking this time it'll stick. Spoiler: It doesn't. "Surprise! More Work": Just when they think they've got it sorted, in swoops an email with a 'fun' new task. So long, free time! "Becoming a Night Creature": Who needs sunlight? The real magic happens at 2 AM, fueled by the glow of a laptop screen. "Coffee: The New Water": PhD students don't just drink coffee; they breathe it. It's not a choice; it's survival. "Procrastination Olympics": Watch as they masterfully avoid work by reorganizing sock drawers. Followed by panic-induced hyper-productivity. "Time, What's That?": One minute it's Monday; next, it's deadline day. Time flies when you're... panicking. "Free Time? Sounds Fake": When they do get a break, they're too puzzled to enjoy it. Ends up napping with books as pillows. "Deadline Superhero Mode": Everything gets done in a last-minute frenzy. How? Magic (and maybe a bit of crying). "Post-Deadline Amnesia": Once it's over, they forget the chaos and swear to never repeat it. Narrator: "They will." "Next Time Will Be Different": The eternal PhD mantra. Hope springs eternal, but so does the chaos. Basically, PhD students are like superheroes who fight the villains of procrastination and deadlines with the power of caffeine and last-minute panic. "Running on coffee and a questionable understanding of time management!"

Melusine - Part 1

Live reports from dreamland, 9 mon.
The sun, that day, had forgotten to set. As he was reclining on a curvy and narrow chaise longue, Sebastian Byrne looked at the slant rays glimmering through the yellowing leaves on the lowest branches of the elms. Their brass-trimmed green lace ebbed and flowed as the wind blew away the last minutes of the golden hour. Sebastian brought the quilt closer to his neck. He sighed, scattering some crumbs around for the birds; but that evening none dared to fly by. Maybe Nathan had lost track of time on his way to the post office and back, and would not come, as he promised, before dusk. They had always watched the sun set together. They did so for the last six weeks, before Sebastian fell ill; and for the first day he could step outside, Nathan did not even bother to be on time. Undergrads will be undergrads… Sebastian was staring absentmindedly at the slow, suspended vanishing of the light when muffled footsteps echoed down the hill, along the side path that lead to the verandah. - Sebastian! The silvery voice rushed towards Sebastian, followed from a distance by a buoyant, youthful figure clad in light linen, waving a folded paper. The figure flew nearer, leaping, kid-like, on the smooth slope where Mrs Byrne’s garden weaved itself into a wilderness of low bushes and wild roses. A smile flickered across Sebastian’s thin, slightly parched lips, and disappeared. He had always seen Nathan skipping and leaping around, from the day he had interviewed him as a candidate for Oxford. While most of the applicants were timidly sliming along the college’s staircases and the tutors’ questions, Nathan jumped along the steps as he did through Greek and Latin periods. A rare breed he was, that seventeen-year-old brat, in a time when undergraduate faces were drawn by sullenness and tedious ploughing. And here he was, two years later, running back from Mrs Byrne’s country house, a letter in his hand. It was that white rectangle that chased Sebastian’s smile away. It was, doubtlessly, the answer Nathan had been expecting for weeks. Sebastian, they wrote back! « I know », thought Sebastian. « They wrote back and had the answer been negative, you would not have leaped so vivaciously, would you now? » Presently Nathan threw himself on the chaise longue, which squeaked under the attack, and stuck the letter under Sebastian’s nose. - Tolle, lege! Sebastian’s lips quivered as he caught glimpses of the words carefully drawn in dense black ink on the white paper. The handwriting leaned gently towards the right, on even lines that left an elegant margin on each side of the silken-white paper. Dear Sir, I am very grateful for you reply. I have read the reference letter sent to me by Doctor Byrne with great interest and his account of your accomplishments… We are very pleased that you are able to join us in spite of the circumstances… Looking forward… Did Madame de La S*** answer herself? Sebastian did not read any further. The thin, straight lines seemed to curl up, fading into one another, becoming barely legible. He smiled and extended his hand: « Well done, young man. This is an unexpected step, but an expected success. And they seem quite keen. » The last paragraph was indeed pressuring. It was urgent that the position would be filled. As many other applicants had manifested interest, Nathan was expected to arrive as early as possible, or they will be forced to hire someone else. « I would need to go as early as possible, maybe the day after tomorrow », said Nathan. It was not until then that Nathan looked at his tutor’s face. As the golden sunlight was turning to purple, he realized the sudden and deep changes the disease had impressed on Sebastian Byrne’s face, once full of strength, intelligence, and mercy. When he had first met Sebastian — then Doctor Byrne to him, Nathaniel Kiernan fell under the spell of these grey eyes, so deeply grey they sometimes seemed black. For two years, almost every day, he had sat under their keen gaze in Sebastian’s room, a shabby but spacious set that overlooked Saint Mary’s tower and the Bodleian’s dome. Those were the days we shall remember as the last golden golden glory sining over the Spires. Not that these were better days, but this time is gone. Surely, then, tutors complained about the termly fifth)week gloom, about the food, at times too rich and at times too poor, and about the noises that the new automobiles made, covering the trodding and rattling of the carriages. Those days poured over the city one after the other, year after year. Matriculation speech faded into Christmas carols as we snuggled in library nooks during the winter; then Summer Eights dragged us out by the river, revision books in hand, then graduation ceremonies rushed upon us and after the long, and yet too short, summer vacation, Matriculation happened again, ushering in a new cohort of Freshers’ faces, at once enthusiastic and anxious, the youthful barbarians from Eton or Harrow, the models of appropriateness from hard-working grammar schools. Under the gaze of the dreaming spires, the streets teemed with laughter that rang along the chiming bells, with inebriated songs at the crack of dawn, with the joyful glee and careless wrath that came with the examinations’ results. While the colleges remained unchanged, their stones and statues clad in centuries of iteration, the young faces around made every morning new. Even Sir Rayleigh, the provost, seemed like a playful young man to Nathan the first time he met him, his eyes sparkling with cheerful wit under his wrinkled forehead and his snow-white hair. Nathan was one of these modern foundlings, all family ties loosened by a scandalous divorce that threw the name he bore into shame, then into oblivion. Her mother at least had the decency to spare enough money for his education but just enough. Her family would refuse to do anything for a Kiernan boy. As he settled in Oxford, Nathan saw Doctor Byrne as a master more than a tutor. He was impressed by the man’s thoughtful silences as much as by his constant good spirits; he mimicked the way Byrne’s long white fingers rose in a slow arabesque before he spoke, strived to reform the sharp angles of his character to match Byrne’s composed temperance, and copied Byrne’s way of parting his hair in a falsely messy line he wore slightly askew. « Byrne has his way with the young gentlemen, the provost used to say. He talks to them like he was their father, and smiles at them like he was their sister! ». What a difference a few months had made. Oxford, in a few days, was deserted as people ran away from a nameless disease, that seemed to appear nowhere else.

The nomad developer setup #2: infrastructure as code

Antoine, 9 mon.
1 min read.
In a first article, I shared a quick and easy way to access VScode from any browser. You still need to create a cloud provider account and setup a server. In this second article I will share with you a way to automate all the steps needed from the moment you have created your account to using VScode in the browser. In order to do this I am sharing a GitHub repo at the end of this article. It contains all the Infrastructure as Code (IaC) you need. IaC is a practice in software engineering, mostly on the devops side, that involves managing and provisioning infrastructure through code, rather than manual processes. It allows for the automated deployment and configuration of infrastructure, enabling consistency, scalability, and version control for your infrastructure. The repository combines three very powerful tools: Packer, Ansible and Terraform. - Packer is a tool to create machine images avoiding to re-install everything every time you start an instance. - Ansible is an automation tool that simplifies complex tasks like configuration management. In a simple yaml file (a playbook) you can install and configure your server(s). - Terraform is an infrastructure as code tool that enables the provisioning and management of cloud resources using declarative configuration files. Please check the README carefully, it lists the current limitations and will be updated when the repo evolves. In a next article I will add even more automation to it using a ci/cd (continuous integration and continuous delivery) pipeline using GitHub workflow to allow you to start/stop this infrastructure as you wish without accessing anything else than a web browser. Happy Devops!
github.com/azieger/remote-workst...

The Gates of Hell

EL MONO MAS GRANDE, 9 mon.
Many days and many nights did the biggest ape spend on this strange planet. The planet of moral people who talk often of hell. They had a dress for man, one for married women, one for boys, one for girls. When the priests called to prayers they came, when the priests called to sacrifice they sacrificed. They all woke up at the same time, ate a same time, prayed at the same time. Their lives ruled by a religion under the rhythm of the stars. -"We do it for this is good", said some. -"We do it because it's best", said others. Never did the biggest ape enquire further for he knew they had no more explanation to give. One day at the market he met a learned man of those people. "We do it because our fathers did it, and before them our forefathers", said the old man, his voice as dry and leathery as his skin. "Obedience was the primary virtue of our forefathers and what brought them glory and paradise". He paused for a while, appearing to think. "We are nowhere as obedient as they were and for that we suffer, this is the reason for our poverty and wretchedness." And with that the old man raised his eyes, deeply sunken in dark caves, hidden behind the weight of eyebrows too big for the emaciated face. The biggest ape rose and took his leave, he had nothing to say. As he was making his way out, a man stood in front of him, unmoved by the lamentations, unstirred by the calls of the priests. There he stood behind his stole. -"Who is this man?", asked the biggest ape. -"He is the richest merchant. ", said one. -"We buy from him because he cheats less", said another, "if only he was more moral like us". -"If only he would pray like us", lamented a woman. -"If only he would give some of his money", said a beggar. -"It pains us that he should go to hell", whispered and old woman. Hearing the talk the man looked up, locking eyes with the biggest ape. 'If I ever enter a god's hell', said the man, 'I will make sure to do so an a honest man.' 'I understand'. Thus thought Apathustra.