Summary

We are back again, with two intriguing tech articles, one a feature and another a deep rooted reflection on someone's personal journey in tech; the next edition of our ebook accepting submissions and our STEM Writing contest in collaboration with Cherielle! Last few weeks have been packed, yet busier days are still ahead. Read below to discover exciting new updates and find out all we've been working on lately!

Technical Article

When downloading apps on your new Macbook, have you ever encountered issues like “runs smoothly on silicon chip versions”, “requires rosetta to run on intel core”, etc? You probably wondered what they are even talking about, what is the silicon chip or intel core? Even if you haven’t, I’m sure you are now. So let’s solve the mystery.

Computers and laptops of the same brand or same line released by a brand, often look similar, in a way like siblings or members of a family; looks very alike on the outside, but the genetic makeup of each is vastly different on the inside.

While most macbooks look pretty similar, versions released before the macbook air M1, are extremely different in terms of their internal organs.

Before the M1, Apple had to use Intel Processors to power their laptops. Intel processors are basically the CPU used in computers and laptops. Denoted as i3, i7, i9 etc, the Intel Core chips are the most common processors used in both windows and mac systems. The higher number of models indicates the chip is faster and more efficient.

So until the M1 chips, macbooks had the same internal blueprint as windows laptops and computers. The processing unit CPU, the graphics processor GPU and the memory card RAM, were all physically arranged separately across the computer motherboard. This required information to travel from one component to another through an arrangement of wires, causing inefficiencies and minor delays.

However, Apple designed their M chips in a way that all those components as well as the neural engine (handles AI related tools) are all placed in a single piece of silicon. This is why the M-series chips are also called Soc i.e systems on a chip processor. As the components are closer they can share the same pool of data. The latest of this series is the M5.

This made the macbooks extremely efficient. Intel cores were infamous for internal heating, so large and noisy internal fans were used to keep things cool, while the battery life of those computers were also significantly lower. In contrast, most macbooks don’t even require internal fans as the M chip doesn’t have the same heating issue and they also have nearly double the battery life of intel core processors.

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My Experience in Tech

Harshita

Nobody in my city was talking about artificial intelligence. Not in the way that mattered — not in classrooms, not in community centres, not in the conversations young people were having about their futures. Technology existed around us, of course. Phones, apps, social media.

But the deeper layer — the one about how AI is being built, who it's being built for, and who gets left out of that conversation — that layer was simply absent. That absence is what started everything for me. I found my way into AI through a program that handed me something rarer than a curriculum: a community of people who believed young people from places like mine deserved to be inside this conversation, not just adjacent to it. YouthXAI became my entry point and, eventually, my responsibility. What began as me learning became me teaching — organising workshops, running events, trying to make sure that the gap I'd felt wasn't one the next person had to feel alone.

There's something clarifying about teaching something you're still learning yourself. You stop pretending the edges of your knowledge are further than they are. You get honest. And that honesty is what eventually led me to MediMind. The idea came from a simple observation: managing health is genuinely hard for most people. Not because they don't care, but because the systems around healthcare — the prescriptions, the dosage schedules, the medical language — weren't designed with ordinary people in mind. I kept seeing it: the elderly relative who missed doses because nobody reminded them, the person who didn't understand what their prescription actually said, the general sense that your own health information was somehow written for someone else. MediMind is my answer to that. It's an AI-powered health companion — a prototype I've built that reminds users to take their medicine on time, tracks symptoms and health metrics over time, and helps people actually understand their prescriptions in plain language.

The goal isn't to replace doctors. It's to close the distance between a person and their own health data, and make that information feel like something that belongs to them. Building it taught me things no certification could. That the hardest part of building for people is resisting the urge to assume what they need. That good design is mostly listening. That a prototype is a question you're asking the world, waiting to see what it says back. Through Newton School of

Technology, I started understanding the difference between knowing and making. Newton pushed me toward the latter — toward treating ideas as things that deserve to be tested, broken, and rebuilt. I stopped collecting knowledge and started using it. What drives me now is the same thing that drove me at the beginning: the gap. The places where technology hasn't arrived yet, or has arrived in forms that don't serve everyone equally. I want to work at that edge — in healthcare, in education, in the communities that tend to be afterthoughts in conversations about innovation. Nobody was talking about AI where I grew up. I'm trying to change that — one workshop, one project, one prototype at a time.