Joined April 2018
- Tweets 5,345
- Following 164
- Followers 502
- Likes 7,623
573 Photos and videos
Pinned Tweet
19 Sep 2021
nobody talks about nodejs much on twitter but today is not that day.
→Learn basics of what and how of Nodejs:
LIKE AND RETWEET
thread 🧵👇
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2 Nov 2025
Re-designed the gear drive to be 16:1 gear reduction,
needed the extra kick for small sized robotic leg actuator.
Improvements:-
1. Torque peak 5Nm(before 2Nm)
2. Torque nominal 3Nm
3. Weight ~305gm
4. Smooth small scale motion.
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11 Oct 2025
Just finished building complete MIT style QDD actuator module with 4:1 gear drive train.
Improvement from last design:
- can communicate over CAN bus.
- easily programmable with arduino
- expected good torque rating (yet to benchmark fully).
- handling high current upto 40 amps
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1 Sep 2025
Just finished prototyping cheapest possible foc based position control motor/actuator.
- 1: 4 planetry gear based output.
Able to do velocity, torque and position control.
Can not find a good affordable 3 phase motor driver in india... 🥲
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30 Apr 2024
If anyone is interested in how CPU works, I have created this project that work as 6502 cpu emulator, you can load assembly programs directly onto cpu, also included some references.
looking forward to create BIOS for it.
github.com/navdhakar/6502cpu
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Navdeep⚡ retweeted
23 Apr 2024
If you want to use @karpathy 's llm.c gpt2 on low end gpu (in my case MX 330, 2GB memory), you can use unified memory in cuda, just replace
cudaMalloc->cudaMallocManaged
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23 Apr 2024
If you want to use @karpathy 's llm.c gpt2 on low end gpu (in my case MX 330, 2GB memory), you can use unified memory in cuda, just replace
cudaMalloc->cudaMallocManaged
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35,771
23 Apr 2024
- explanation
It basic doesn't statically load all parameter in GPU but stream it from shared memory (SLOW)
- possible optimization
Training using this is bad but looking to optimize this with "cudaMemPrefetchAsync" etc. for reasonable inference speed on consumer gpu.
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22 Apr 2024
even small LLMs are insanely data hungry, I fine-tuned mistral7B with 20k data points it still overfits in less than 100 iterations
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21 Apr 2024
Some things to do as a developer.
Been diving deep into linux for a month, Just read this book, awesome stuff, was very Intimidated by linux, but when you can build kernel and drivers from scratch linux become so much easier.
Resources that I went through👇
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21 Apr 2024
- deep dive books (kernel, drivers)
kroah.com/lkn/
lwn.net/Kernel/LDD3/
- install gentoo os (how real life linux distros are packaged and installed)
gentoo.org/
- awesome youtube channels
youtube.com/@Doriandotslash
youtube.com/@nirlichtman
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21 Apr 2024
One important channel I forgot, he gets right into meaty stuff of building real life linux drivers, its easy and its useful, you will never complain why your nvidia card is not working on linux.
youtube.com/watch?v=XoYkHUnm…
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17 Apr 2024
I ran @karpathy's llm.c as pytorch and native c on low-end cpu.
difference is already significant.
👇 below is simple comparision.
1. model compiled with C
-almost 1 GB less memory use (no pytorch overhead)
-efficient use of all 8 threads on cpu
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17 Apr 2024
2. model using pytorch
- some cores are being used and some not
- 1GB memory uses as compared to native
these memory save and efficiency can be useful if we want to run these model in offline on consumer hardware.
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18 Mar 2024
✅successfully trained 1st test LLM for generating prompt from text chunks of raw data that can acts as synthetic data generator for anyone to make domain specific dataset.
-comparison between base model and finetuned
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18 Mar 2024
difference might seem very subtle but the finetuned version ask question in much more depth regarding variables in code etc. and try to mimic capabilities for GPT-3.5,
which can make a lot of difference when this is used to train model that has knowledge about this data.
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