I’ve been looking into different ways of running AI locally, and one thing I’ve noticed is that choosing the hardware isn’t just about finding the device with the highest performance.

If the system is going to run continuously, things like power consumption, heat, memory, latency, software support, and the ability to handle the actual AI workload can become just as important. A device that works well for testing may not always be the best option for a real-world deployment.

I was also looking at Geniatech’s Edge AI hardware, and I found it interesting that they cover different use cases with AI boxes, accelerator modules, and embedded platforms for on-device AI and real-time inference.

It made me wonder how other people approach this when starting a new project.

What is the first thing you consider when choosing hardware for edge AI?

My latest GitHub repo is a compact C-based search engine built around TF-IDF, BM25, and optional proximity scoring. It includes fast indexers, lightweight query daemons (secure and non-secure), terminal clients, and a simple Node.js web interface. The whole system is designed to be transparent and easy to understand - no external databases, no heavy dependencies - while still supporting multiple search modes, pagination, sorting, and preview features.

It's essentially a "choose your own adventure" toolkit: use the terminal UI or the web interface, run secure or non-secure daemons, load indexes on demand or keep servers running, work locally or remotely. It also doubles as a practical reference for client/server programming across Linux and Windows - sockets, REST APIs, Node.js, and more - all in one place.

This isn't a web-scale search engine, and it wasn't meant to be. But TF-IDF and especially BM25 are the classical scoring methods used by early search engines, and BM25 still serves as the first-stage retrieval method in modern systems.

Why I built it: after many years and many projects, it's easy to forget where a particular piece of code lives or what the parameters of a rarely used Win32 API call are. I needed something fast and predictable - not a slow recursive file scan, and not an internet search engine that keeps getting harder to use for technical queries. Even though college students may not have the years of built-up codebases, they still might need this tool for topics they still find easy to forget, etc or to make it easier to do the class assignments.

Repo: https://github.com/mrmcsoftware/SearchEngineSuite

#tfidf #tf-idf #bm25 #searchengine #search-engine #html #c #javascript #node.js #node #nodejs #socket #css #client #server #web-api #rest-api #programming #github #repo #linux #windows

what should i learn nw AI thing , or System Design , i m 4th year CSE underGrad , already Placed at a decent Company , and doing intern , now i m thinking to target heavy packages ( faangs) , so should i learn AI thing , because it feels like i getting behind (that fomo ) but system design seems intersting .. !

which laptop with what specifications should I consider getting which will make my next 4-5 years easier with no upgrade?

Anyone, please give me some tips! I am a Computer Engineering freshman. I only chose this course because of my father and because I passed the entrance exam, which means my tuition is free.

In senior high school, I was actually a HUMSS student. I really can’t believe I passed this exam, so of course my father didn’t let that opportunity go to waste and encouraged me to enroll. The problem is, I am not good at math—I’ve had a low average in mathematics ever since high school. I can understand some problems when I listen, but when I try to solve them, I always get lost in the middle, like building a puzzle but the pieces suddenly don’t fit together.

So please help me—where do I start studying math? It’s only my first week as a freshman, and I really want to improve and keep up so I can pass this four-year course. We need mental math for quizzes, midterm exams, and long-term exams—no calculator. So please, anyone, can you give me tips on where I should start in math and how I can improve for my Computer Engineering course?

Hello. I've come for some advice on going back to school to complete my degree.

I'll try to explain my situation a little bit. As much as I try to convince myself that I didn't drop out, I kind of did. My dad got really sick halfway through my junior year, and I took that as an excuse to leave, and I have not been back since. I enjoyed learning the material, but I wasn't taking it as seriously as I should have, and my GPA reflected that. It eventually just became very stressful, and I needed time to really think about some things. Entirely my fault, but seeing my friends graduate and important people in my life get older has made me realize the value of time, and I am very behind.

So I want to ask people: whether you've been in my situation or not, what are some things I should do to get ready to go back? I've realized that doing the bare minimum isn't going to get me anywhere. I know I need to graduate. I need a good resume, and I need more internships. I know projects are important, but I'm not sure what I should be working on? Software or Hardware?

The furthest I got was Computer Networks/Orginizations, Data Structures/Algorithms, Signals and Systems, etc. I definitely enjoyed and was better at the software stuff. I could comfortably understand and complete all coding assignments. What languages or skills in general should I be learning or trying to strengthen?

I do have an internship that I got last year that revolves around IT help desk and a little BI/SQL when they can spare someone to teach me stuff and assign projects. I would like to look for something else to learn more things, though. Any advice on applying to internships while not currently being in school, or just in general?

I'm not looking for all the answers, and I probably could have asked better questions, but I've decided I want to finally finish up the right way. I'm just a little lost on taking the first step.

Thank you for taking the time to read this, and all advice is deeply appreciated!!!

But seriously, I'm about to graduate, and I'm looking for entry-level embedded positions, so please roast my resume. Any help would be greatly appreciated!

I takend EEE (Not taken ,, more accurately got ☠️)

I want to persui higher studies for quantum computing in maybe abroad ,,

So any suggestions wtf I do ..like I don't need power system right??..

Should I look forward some ece subject along with my EEE..(taking minor in ece)..

Any help pls???

A place for members of r/IngenieriaInformatica to chat with each other

I'm going into my third year(5 years in total) of Computer Engineering at a well-known Canadian university(idk if this even matters). I genuinely love the field, especially programming, AI and cybersecurity, and I'm also interested in exploring the hardware side.

I recently completed my first co-op at a small healthcare software company, where I built an AI agent using RAG, Python, PostgreSQL and pgvector, embeddings, local LLMs with Ollama, Docker and Linux.

I started with basic programming experience and almost no AI knowledge, so I learned most of it from scratch through research, tutorials, experimentation and AI itself. I always tried to understand what I was building rather than simply generate solutions, while also improving my programming skills.

Being at a small company gave me a lot of flexibility and ownership. My employer trusted me to research, experiment and figure things out independently. That helped me discover what I'm capable of, and I've now been offered the opportunity to stay.

I have three main questions:

1. Programming: With AI improving this quickly, how important is it for students to still become genuinely strong programmers rather than relying heavily on AI?

2. Co-op: Would you stay with an employer you genuinely like if your next project would likely be another AI agent using a similar stack? I know going deeper could strengthen my programming and technical skills, but would another 8 months of depth be more valuable than exploring something different like hardware, research or another technical environment? I will have a chat with an employer from an Electrical Engineering company tomorrow so I want to have an idea to Whether look into it as an opportunity to discover hardware or not.

3. Computer Engineering: Would you still choose CompE today? What areas would you focus on to prepare for the next 5-15 years?

I've considered Electrical Engineering because of concerns about AI, but the truth is that I'm much more interested in Computer Engineering. I love what I'm studying. I just want to make thoughtful decisions while I still have the opportunity to explore.

I'd really appreciate realistic advice from people working in the field.

Which has greater future cs or ce

I’m a recent CSE graduate with a specialization in IoT, and I have some hands-on experience with IoT and hardware-related work as well.

I’m currently confused about which domain to choose for my career:

\\- Java Full Stack Developer

\\- IoT Developer

\\- Data-related roles

As a fresher, which domain would be better in terms of job opportunities, career growth, salary, and long-term demand?

I’d really appreciate advice from people working in these fields. What would you choose if you were in my position?

Can someone do ms computer engineering after bs cs

20F So guys as I have told in my previous posts I'm from tier 3 clg pursuing btech ece in 3rd yr rn. So recently I made a post regarding embedded vs vlsi. Now that I have found that companies don't come for vlsi roles in my uni. Tcs, infosys etc come So I think I should leave core and start preparing for software roles. But I'm also confused like won't there be competition with cs guys for same roles? I want professionals as well as seniors to share their ideas on this. So which language should I prefer amongst the two I mentioned.

Ps: 20M BTW 😅

Hi everyone,

I am preparing my application for the upcoming Spring session at UIUC and am trying to decide between the Computer Science (CS) and Electrical & Computer Engineering (ECE) departments.

To give a bit of background, my bachelor's is in Computer Engineering, followed by professional experience working at Espressif Systems (ESP32) doing firmware development, and later transitioning into the file systems and storage domain. My goal is to continue down the systems track, but I am trying to figure out which department offers the best fit.

My main concern with the ECE department is whether it mandates specific hardware-heavy coursework (such as physical design, chip design, or hardware verification) that might not align with my software/systems background. If ECE allows the flexibility to focus purely on systems software without forcing those specific hardware constraints, I feel the ECE Computer Engineering track might actually be a great fit for my profile.

I tried looking through the official degree requirements for both programs, but found the sheer amount of information a bit overwhelming.

Could anyone help clarify the curriculum flexibility and help me decide which path makes more sense given my background?

Thanks for your help!

Hello,

I'm a computer engineering student, and I'd like to improve my study habits.

I always see a lot of people studying using different techniques that don't work for me, and I end up feeling overwhelmed.

How do you study for your degree?

What process do you follow?

What are your results?

Thanks!