Ptk

an alt account dedicated for learning in public (main acc - @0xPtk )

[Ptk @ptkthe2nd]

Starting from today , I’ll be sharing what I’ve learnt for each day.
My posts will be about data science, machine learning and deep learning.

[blurrylogics @Blurrylogics]

A Conclusion to Our On-Chain Experiment

We tried a pretty unique experiment to bring IRL fun on-chain.
During the Halloween event hosted by @AvaxTeam1 and @BitkubOfficial , we built an app where participants could complete both online and IRL activities to earn chances to spin, open mystery packs, and transfer jigsaw pieces to each other.

Throughout Halloween night, a total of 90 users completed 831 activities, including both X tasks and IRL tasks.
Our app executed a total of 919 on-chain transactions, including 408 NFT mint transactions that minted 908 NFTs.
Everything, from jigsaw pieces to reward NFTs, is verifiable on the @avax chain.
You can check out the stats here:
https://t.co/fUlOTPdoRC
A big thank you to everyone who participated in this on-chain experiment. We learned a lot from it, and we'll try to make the experience better next time.

Blurrylogics

[zack @zack_overflow]

Of course, that’s your contention. You’re a first-year machine-learning engineer. You just got finished readin' Attention Is All You Need, probably watched a Karpathy video too. So now you’re convinced everything is just transformers and scaling laws.

That's gonna last until next month when you discover convolution, and then you're gonna be talkin' about inductive biases and locality and how CNNs were actually incredibly compute-efficient for vision.

Then you're gonna read the FlashAttention paper, and suddenly everything's about IO complexity and SRAM and how FLOPs don't matter because the whole goddamn thing is memory-bandwidth bound.

That'll last until somebody shows you an MoE model, and then you're gonna be in here regurgitating DeepSeek, talkin' about expert parallelism and active parameters and how dense models are economically obsolete.

Then six months from now you'll write one shitty Triton kernel, look at an Nsight trace for the first time, and start telling everybody Python isn't actually the bottleneck because the GPU is asynchronous.

And by next year you're gonna be standing right here explaining to me that your 400-billion-parameter model is fast because you turned on CUDA graphs.

[Ptk @ptkthe2nd]

@grok @GenxFactB4Feels @sam_sisc @melonkoly @RemmerShaw @elonmusk He did actually post this you may find in some reliable articles , he just deleted it

[Ptk @ptkthe2nd]

And, hopefully posting here will act as a reinforcement loop to motivate me further.

[Ptk @ptkthe2nd]

Starting from today , I’ll be sharing what I’ve learnt for each day.
My posts will be about data science, machine learning and deep learning.

[Ptk @ptkthe2nd]

My background :
A sophomore Cs student with decent understanding in maths ( calculus, linear algebra,probability and statistics) I have learnt web development for a time until I get bored of it and now I’m thinking of pursuing my career in data science field .