If college did not fund your projects, we might be able to help. (we are starting a grants pool!)
▲ 37 r/iiests

If college did not fund your projects, we might be able to help. (we are starting a grants pool!)

Hey r/iiests

tldr: we will fund your non-cs projects, and connect you with people. FPGA boards, 3d printers etc. are on us.

I am an incoming second year student. Last year, I wanted to join the robotics club, but pretty quickly realised it wasn't really worth my time. There's no funding for personal projects, and no real drive to aggressively make things either.

I assume a lot of you have a version of this story.

Now I get it. If you're not doing CS, or your thing needs physical components, the current Indian engineering landscape isn't really tuned for that. Money is a problem, so are resources, and so are the people who'd want to build things with you AND not quit when shit gets tough.

Institutional funding exists on paper, but "on paper" and "before you lose interest" are very different timelines, and none of us can sustain interest if funding takes a whole semester to process.

The point I want to make is:

  1. Real engineering happens in the physical world. Software gets all the limelight because it's cheaper to get started with.

  2. Physical stuff needs more resources and money.

  3. It needs a feedback loop from likenminded people.

  4. And it needs good connections with people already making cool stuff (think engineers at pixxel.space, unitree, etc.) to get good insights.

But institutional bureaucracy and bloated club/society dynamics aren't getting you the tools or equipment in time. So, taking matters into our own hands, a couple of friends and I are willing to build a maker grants pool.

We would rather help 2 people make something cool than end up spending that money on a mechanical keyboard(s) or diet coke which we don't need.

We'll help you bootstrap prototypes and connect you with people from our own network. In return, you just need to document whatever you build, and make a pledge to pay it forward at least once in your lifetime.

We'll operate extremely lean (no GS, treasurer, club leads, or any of that bullshit). Instead of an application process, we'll just have two conversations with you, anywhere on campus you want. Online communities don't really work for this.

We NEED the offline adrenaline.

Yes, we're basically a16z, but in a foetal stage, with no strings attached.

Word of mouth works best, so do reach out! (dm me, or shoot an email at admin@grafitelab.in) Or let any of your friends know about us.

grafitelab.in

We're maxing out operations from August, and our main targets are the '29 and '30 batches.

Cheers.

Note: Aim is to help 2 people (minimum) get a jumpstart, yes only 2. I live in an apartment near the first gate, if needed will convert my room to a shared workspace for electronics/mechanical stuff. Money comes from our own stipends/prizes and grants.

u/Shonku_ — 2 days ago
▲ 15 r/iiests

Got nerd-sniped into reading about Architecture! Our college was at the forefront of the field post-independence + Prof. Fuller played around with geodesic domes here

https://preview.redd.it/n918ctvi7t9h1.png?width=629&format=png&auto=webp&s=46776702ca2e131ba6ecf8e71b2907cbe79d7d98

I am not a BArch student, but hey it was nice read to read about architecture.

Here's the article.

main points:

  1. the first institution in India to award a Bachelor’s Degree in Architecture (1949)
  2. apparently, this place had such a profound impact on the man behind Delhi's "Steinabad", Prof Allen Stein, that he ended up staying in India for decades.
  3. Buckminster Fuller experiments with bamboo-made Geodesic domes in here

I think architecture is more interesting than I had imagined it to be.

https://preview.redd.it/ts8xpik79t9h1.png?width=668&format=png&auto=webp&s=00f171d94ec3f70e3844695f6246ab6b052400c5

reddit.com
u/Shonku_ — 10 days ago

I reverse engineered Qualcomm's NPU compiler to find undocumented behaviour

This was my first reverse engineering attempt with a proprietary software artifact. I work on Edge AI, and I was about to rage quit due to the staggering lack of documentation about NPUs which everyone from Qualcomm to MediaTek to Apple is hiding.

I found some genuinely never known before stuff:

  1. the compiler silently can downgrade your model weights' precision without telling you

  2. memory placement uses HiGHS (an open source software) which is a linear programming solver (not heuristics)

  3. the same model on two different chips with identical reported VTCM (place where NPUs store model weights) can have 33x difference in DDR (normal RAM memory) traffic, why? I don't know, Qualcomm never published the memory capacity the VTCMs of any of their SoCs

  4. There's an undocumented internal simulator called Hextimate pricing ops without the hardware

The Whole Writeup

Apart from this, the placing of memory in the VTCM uses something akin to 3D binpacking (each block gets a tuple of three u32 ints), that was genuinely shocking as till now everyone had thought of it as a linear memory lane. The allocator (they literally call it FancyAllocator) uses recursive backtracking as well.

I have also written about NPUs before. Perhaps, I am single handedly bridging the gap between the marketing fluff and academic literature on NPUs on the internet XD

I hope it helps people who are working with Qualcomm DevKit (like me!) to get over the itch.

Edit: added full forms :)

u/Shonku_ — 18 days ago

145 programming challenges/projects you can build this summer! (thanks 4chan)

boards.4chan.org/g/

add to that, this book: The Programming Contest Training Manual (leans more towards the algorithmic side).

hope it helps

cheers

note: i personally made/solved/created 1,4,9,10,11,12,15,17,18,20,25,38,43,44,46,50,52,55,57,58,59,60,61,66,69,72,74,75,82,86,92,94,102,107,111,125,141 which is barely 25% of it.

p.s. I will personally reward whoever builds 125 using their own 87, and has a technical blog explaining their entire thought process and mistakes - especially the mistakes and how they tackled them.

(only 87 would also work if you do it right - assume a subset of the language)

reddit.com
u/Shonku_ — 21 days ago

how to decide a ballpark figure for working at an SF based AI infra startup?

hi there,

background:

- vc funded SF based AI infrastructure startup ( with < 10 people)

- they reached out to me after seeing my systems/ml infra work

- its an internship

they've asked me to suggest "any ballpark figure" - and i got no clue how to do that

using an LLM i came up with this formula:

Ballpark = max(Previous salary * 3, 0.15 * US market monthly)

which gives roughly 800-1200 USD per month, considering ill be working remotely from india.

i have a hard time (i feel uncomfortable?) talking about money, and have only worked with indian startups till now.

i am unconfident slightly for being an upcoming second year student - i dont want to overshoot or be underpaid.

so the main question boils down to - how to know your actual worth?

would be glad if anyone guides me through this tough decision.

reddit.com
u/Shonku_ — 22 days ago

I'll answer all questions on how to utilize your first year of CS major.

hi, i finished my first year of college, and have a 2 day break before I start working onsite.

if you don't know me already from this subreddit, i do research on a fairly niche subfield of machine learning, and have worked at early stage startups doing hardware-software co-design, im in talking stage with a couple of YC founders / antler backed startups, and have fairly good connections with many engineers in my niche, and tech leads from faang.

i receive a LOT OF dms on twitter and reddit - asking me how I do, what i do, and how I got in, despite having no "elite" or "above average" schooling.

I decided to write a mega document, answering pretty much everything I know and what I got to know from people who are levels above me.

Just know, I want to work as a research engineer at labs and early stage startups - preferably at the frontier ones.

Not the generic SDE roadmap, for me doing something _interesting_ >> getting high paid job _anywhere_.

Some of my previous writeups which might give you a teaser:

  1. https://www.reddit.com/r/Btechtards/s/7wvIf62Fp0

  2. https://www.reddit.com/r/developersIndia/s/jd3hVB56Nq

  3. https://x.com/i/status/2054541796437582011

yes im a moderator of this subreddit, and one of the duties of an internet moderator is to curate and publish information which helps the community as a whole.

Edit: travelling for a while, will answer everything in a bit.

u/Shonku_ — 1 month ago
▲ 16 r/iiests+2 crossposts

Information Brochure for BS-MS Admission (Physics, Chemistry and Geology) has been released!

Link: https://www.iiests.ac.in/assets/images/notifications/BS-MS%20Brochure%20Final.pdf

For any confusion/query, make a post on this subreddit (faster), or reach out to the authorities directly (slower).

Regarding Placements:

> 4 Year BS (Hons) and BS (Hons with Research) degree holders can take part at IIEST campus placement together with the 4 Year Engineering graduates

> 5 Year BS-MS Dual Degree holders can take part in IIEST campus placement together with the Masters students of Engineering disciplines

https://www.reddit.com/r/iiests/s/Y9xkCTTk5O

u/Alert-Improvement-81 — 2 months ago

Hi, I am a freshman who is trying to break into research.

I got into a well known university research lab in my country for the upcoming summer, and the prof said I am "better positioned than numerous others" for hardware-aligned machine learning topics. I am facing a couple of problems, and I would like to know how seasoned researchers deal with them:

  1. How do you develop the intuition for what's open vs. what just looks open? When I look at a research space, everything either looks already solved or impossibly vague. There's no middle ground visible to me, yet. This bothers me.

  2. How do you handle the feeling that every idea is either already done or not good enough, without it paralyzing you?

Ideas that I have "thought" of but have been done already: PQCache, async KVCache prefetching, roofline modeling for GQA decode phase.. etc.

A paper that says "future work includes X" BUT it is not the same as X being open, right? Someone may have done X last month and not published yet, or X may be open but intractable, or X may be open but require equipment which I don't have. I would have no way to know which. Morever the thing I want to work on might exist under three different names across three different communities, and if you search the wrong name you conclude it's open when it isn't. (LLMs with Web Search seems to help a bit)


Reddit threads that I have already looked into:

  1. https://www.reddit.com/r/MachineLearning/comments/1sayptq/d_physicistturnedmlengineer_looking_to_get_into/
  2. https://www.reddit.com/r/MachineLearning/comments/1nsvdqk/d_machine_learning_research_no_longer_feels/
  3. https://www.reddit.com/r/MachineLearning/comments/kw9xk7/d_has_anyone_else_lost_interest_in_ml_research/

My motivation to work on this field is to speed up ai-for-science initiatives, while making it more affordable.

reddit.com
u/Shonku_ — 2 months ago