std::panic

Jan–Feb Recap: • Built Chronos : high performance job scheduler (single digit µs latency) github.com/aryan55254/Chr… • Built Scruffy : simple mark & sweep Garbage Collector github.com/aryan55254/Scr… • Trips to Gaon, Baidyanath Dham, Vrindavan, Mathura & Agra

@microtaskq @golok727

@golok727 me hu na 😎

hmmm i'm alone again 😂 so boring without my og oomfs.. kinda wanna leave this app too ngl

wrote a blog on how JavaScript's flagship JIT Compiler works...go check it out guys!!

@shouryasharma33 Uble ande khae nhi jaate inter roj

u actually do not need whey, u can make up for one scoop with 4 eggs, at least main to yahi karta tha if these egg white carton thingys become common I'm eating those like nothing and I'm a huge sucker for eggs bro I'm telling u

@itsgintoki_ @shouryasharma33 muesli mtlb ? oats keh rhe ?

@stdpanic @shouryasharma33 hn pr ab papa ko boldeta manga dete pr phir bi 2 kg se km me impossible hi h agr veg khara iske upr se bi eggs muesli milk lena hi pdta

india should have one of those carton egg white thingys they will actually be so goated but they better make em cheap

@itsgintoki_ @shouryasharma33 haan mene suna whey bc pchne mein dikkat hoti achanak se jyada lene lge toh

@itsgintoki_ @shouryasharma33 whey yaar kuch jyada hi mehenga h mkc , meri toh job lg jaye uske baad bhi sochunga khridne se pehle

@stdpanic @shouryasharma33 lmfao😭 imo - >earn first >buy whey >then gym

@itsgintoki_ @shouryasharma33 haan whi lg rha h , i would like to lose this fat for once tho

@itsgintoki_ @shouryasharma33 mujeh toh lg rha h ye 3 hafte ka fluke h aur i will go back to eating kurkure momos once and never look back at ts again 😭

@itsgintoki_ @shouryasharma33 kaahe ?? uske bina toh khel khtm ho jayega sb kuch ka mere

@itsgintoki_ @shouryasharma33 soya bean kha leta sauted , paneer sandwich mein (daily khud hi bna leta toh mummy ko dikkat nhi hoti) eggs (bahar khrid k khane pdte ghr pr nhi bnta), milk aadha litre jod jaad k ho jata kisi trh , kisi trh thoos rha huun ngl

@stdpanic @shouryasharma33 70 without whey is very good how tho?

@itsgintoki_ @shouryasharma33 mera toh 70+ hua h filhal kisi trh mr mra k i am just trying to lose weight while not losing muscle(barely kuch h) for the moment , baaki baad mein dekhenge 100gm toh kaafi kathin lg rha without whey

@stdpanic @shouryasharma33 yup wo bi dikkt h but see u can just add a protein source along w it even ~35-40g would suffice

@itsgintoki_ @shouryasharma33 baat h agr ghr walo k sath rehte ho khane ko daal chawal bhujiya hi milega (it slaps tho) aur jb ghr mein rehte khud jaakr bnane mein alas aata h

@shouryasharma33 actually india should have a lot of protein options especially the ones we import canned tuna being one of those

@404Found808 Us bro us

I don't relate to people who complain about reach......... Because I never had reach.

@MrAdityaPathak Post your art work as well bro

I think that sycophancy is probably the reason why many people start relying on AI's decisions while using it for a help. This makes a person more confident in their own delusions that what AI is saying has to right instead of getting a reality check.

found you

@9elcapitano @Mboomo19 I just know for a fact half of every set piece they get is gonna get scored coz y'all are so bad at defending them

@Mboomo19 how true Is this if at all we play arsenal in the semis and all those who watch this arsenal regularly?

@maaz404 Mujhe toh nhi aaye yaar wishes modii ni dwaara

Now I want our PM to email us Eid Mubarak

@maaz404 Gaon nhi gye ??

BharatGas ftw

@flying_jatt45 @ryuzaki2401 Not really a right wing or liberal or any specific thing , most people in general regardless of political stance are highly ignorant in terms of looking through a different lens

@ryuzaki2401 Same with every right wing too

political discussions with some self-proclaimed liberals feel like smashing your head against a wall. their ignorance and dishonesty toward their own ideology is astonishingly annoying. they kept academia hijacked for decades, with no space for an alternate narrative. now that people are calling out the one-sided stories presented to indians for so long, and offering a different perspective, they're unable to breathe. that's indian liberals for you.

I managed to compress ~30GB of 10M vector embeddings into ~370MB cause RAM prices are too high. While rewriting my vector search library for the 3rd time, I decided to stress test it with 10 million 768-dim vector embeddings. My ThinkPad has 31GB usable RAM but the dataset is ~30GB uncompressed. I was just a few hundred MB from an OOM while loading the data for the first time XD So I figured out how to implement Product Quantization. Github: github.com/datavorous/sph… Using PQ, I got to split each high dim vector into smaller subvectors, then approximate each subvector by its nearest centroid from a learned codebook, because of that we can now store a tiny integer code per subspace instead of storing the raw floats. During query time, we reconstruct an approximation from those centroids and compute distances in that compressed space, and that makes it lossy. For generating a candidate set, a ~80x reduction should amortize the decrease in accuracy (~83% recall@10-in-100). But again, a re-ranking post-processing step should help with that. I will giving OPQ a shot next, which should improve the recall by exploiting the fact that embedding dimensions are correlated. It was really a cool month where I stripped down ~700 lines of unnecessary code, and implemented PQ from scratch by just reading its the paper. It was really a cool month where I stripped down ~700 lines of unnecessary code, and implemented PQ from scratch by reading only the paper itself.