Mario Caleb

@osasinrobotics @DEEN_OWA Exactly, I can't remember his name; once say his content Origami is beautiful

@MarioCaleb12 @DEEN_OWA Oh yeah origami. And there's this guy on Instagram that creates clothes that grow with children. It's quite flexible

@DEEN_OWA @MiracleAgitan_ @MasterMynd2004 @emmanuelakingb3 @chiamakachimix @KelvinOmoluyi @princess_yfe @_Keli_Chris @Emmanuel_Obe_1 @stealthexploit @yfe_embedded @thegeekcircleX @iamKingRobert Fingers crossed 🤞🏾.

@MiracleAgitan_ @MasterMynd2004 @MarioCaleb12 @emmanuelakingb3 @chiamakachimix @KelvinOmoluyi @princess_yfe @_Keli_Chris @Emmanuel_Obe_1 @stealthexploit @yfe_embedded @thegeekcircleX @iamKingRobert

I’m building a better rain protection system under REEVS and I’d love input from fellow builders, designers & creatives. I’ve started working on a concept and I’m stuck on the head/hood system So I’m hosting a Space to brainstorm it live and design through ideas together.

@princess_yfe Internet service providers like Glo and the likes

@MarioCaleb12 What's ISP?

@anis_neyo This is awesome

We got our first check ! By solving drone recharge

@doudou_19X Impressive!

Today I’m presenting OctOpus at the Africa Deep Tech Community. OctOpus is the first autonomous AI data scientist. It understands a dataset, plans the workflow, writes and runs Python, trains models, compares results, fixes errors, and produces usable outputs for business and research teams. The goal is simple: make real data science faster, more accessible, and more autonomous. Excited to walk the community through what we are building. Try it here: octoopus.dev #AI #DataScience #MachineLearning #DeepTech #Startups #AfricaDeepTechCommunity

God abeg 😂. Sticky benchmarks 😂😂

@princess_yfe We are getting there, a hardware at a time ☺️.

@MarioCaleb12 I feel you 🥹 Having a home lab has been in my mind for a while now

What's one thing that you wish you had when you started out in hardware? Or at least, one thing that you or lots of people in hardware struggle with that you wish you didn't? Maybe we at YFE will do something about it? 🌚

@Loganullyott I'd love to have more insight on this.

Hosting a thing for international founders to understand visa options. If you're applying to YC, Speedrun or other accelerators, this is for you. International student looking to start something? This is for you. Drop a comment/ emoji/ whatever and I'll send you the details.

@zikohercules Looking forward to your progress 🔥

This will be my first time working with the Raspberry pi framework I still have alot to learn Interesting projects ahead I assure you✅ I wasn't joking at all But I will keep moving at the pace available to me #Zedora #engineering

@MohDoumbia223 This is laudable 👏🏾

A few weeks ago, our team built Edusi in 24 hours at an MIT hackathon. Now we’re making it open source. Edusi is an AI-powered bilingual learning platform for Nigerian children, starting with Yoruba + English. The AI layer combines Gemini, OpenAI, Google Translate, and open-source Hugging Face models for lesson generation, illustrations, speech recognition, TTS, and mixed-language routing. The architecture is model-swappable, so others can adapt it for more languages and communities. Repo link in the first comment. #OpenSource #EdTech #AI #Yoruba #Nigeria #NLP

@OluwatolaAyomi4 😂😂

GT Squadco hackathon asked the participants to solve a leetcode problem to qualify for the next round 😂.

@EmmyCodes775 E no pass wetin u fit do

@MarioCaleb12 And what if i painted my remote like iPhone, i want to feel among 😔

What did the object said to the object detector……YOLO…..get it….because YOLO is a object detection algorithm…. imma leave now…….🥲

@Obinna32_ Keep building 🫵🏾.

First Hackathon 🔥🔥 Team's Position: 55th 😞 Nice Theme but most of us were not given the chance to pitch our ideas/project that we spent a week building😒 All in all, it was Great, met a lot of Awesome People 💯💯 Onto the next ✊🏻 #SquadHackathon #GTCO 🌟

@Tosin_afolabi09 @princess_yfe @yfe_embedded @GenovoT59335 Solid !!

@princess_yfe @yfe_embedded Folabi. Nigerian founder. I build compilers, train models, write research, and break software for fun. CEO @GenovoT59335 | AAAI-26 | NVIDIA Inception Here to build things that last.

It's Pitch Yourself Saturday! First time I'll be doing this with my community 🤭 Hi, my name is Princess, and I'm an embedded systems engineer I build hardware projects for a living, and I'm also inspiring this generation of hardware engineers to build their skills, show off their work, and connect with engineers like themselves I do this through my organization, @yfe_embedded We're building industry-ready professionals, who will get positions and build positions that will change the world 🌍 If that's you, reach out to me, so you can join our community We'd love to have you 🤗 Now, quote this post with who you are and what you do Let's have it! 😌🫴🏽🔥

@YuvrajS9886 This is amazing man ! It will definitely come in handy.

@MarioCaleb12 Oh that’s amazing! The thing I have been building smolcluster.com has the same aim of using whatever compute you have at your disposal too!

Hey everyone! Recently, I released a blog on how to setup a cluster out of your Mac Minis for distributed training and inference Now its time to do the same with Raspberry Pis! Why Raspberry Pis? - quite cheap (30-50 dollars) - easy to use - full blown OS the size of a credit card (small enough for edge projects)! This is a part of my current series where I’ll be releasing blogs and guides around learning distributed learning and building your own small compute clusters. The goal is simple: help more people get started with running and training AI models using the hardware they already have lying around. Old laptops, MacBooks, Mac minis, Jetson Nanos, Raspberry Pis, even phones and tablets. Distributed learning often feels intimidating from the outside, but it’s genuinely one of the coolest areas in systems and AI once you start playing with it yourself. Before we get into the fun stuff like distributed inference and training, the first few posts will focus on setting up hardware properly and building a working cluster environment, basically subtle amount of cabling and networking! The early guides will specifically cover setups around: * MacBooks and Mac minis (Done!) * Jetson devices * Raspberry Pis (This one hehe) After that, we’ll move into quick demos (smolcluster ) , and gradually learn the fundamentals side-by-side while actually running models across devices. I’m building this alongside smolcluster, so a lot of the content will stay very hands-on and practical instead of purely theoretical. Hopefully this helps more people realize that distributed AI systems are not something reserved only for giant datacenters anymore. There is just one question I want to answer: are heterogenous clusters, like what I am trying to make above, even possible for running models? Well, we'll know and till then do read me blog and let me know what you all think! Any comment, feedback etc are very welcome. (pls be gentle since its my first time writing one all by myself haha) Hail LocalAI! PS: All this is for educational purposes only and not meant for getting performance at par with dedicated GPUs...well not that I have figured out a way to do it yet. Please use this guides and information you'll get to learn the basics of how distributed learning is done! Thanks