Abhinab

Its supposed to be other way around idiot. You fund the research first, Nobels will come eventually.

@reyavocado ???

@Kimi_Moonshot @cursor_ai

La Pinoz Pizza

just got an increment guys now my annual yearnings will be higher

I had an offer from an incredibly well-funded startup in early 2020 ($150M+ raised). I was supposed to join their ML team in April. I had already resigned and was serving my notice when COVID hit. HR called and said they were deferring my offer. Assured me the offer was safe and that they just wanted me to join once offices reopened. For the next couple of months we stayed in touch. Every conversation repeated the same thing: the offer is safe. The market was dead, so I spent the time doing research with an ex-advisor. We finally set my joining date: June 1st. In the last two weeks of May I had multiple calls with my future manager. We discussed MacBook configs, projects I’d work on, brainstormed approaches. I even shared my shipping address for the laptop. Two days before joining they rescinded the offer. That day I learned something important: Your employer will not hesitate to rescind an offer or lay you off if it benefits them. You shouldn’t feel guilty about optimizing for yourself either. Everyone is optimizing for their own interests. It’s a ruthless market. An employer has 100 / 1000 / 10000 employees. You only have one job.

@m44dh4v Ye kaunsa app h?

Conceptually this is what quant shops do with CS undergrads

Grinding LeetCode while the recruiter selecting candidates using family tree traversal

What do these people think "physics" is? Do they imagine it's a finite list of unsolved hard physics problems, the ultimate homework set? Do they think if an LLM solves them, we'll shrug and say "that's it, we have no more curiosity. physics is done" ????

most humans cluster tightly around the mean of the cognitive distribution. the rest of us accept the model: intelligence variance is small relative to outcome variance. we are all - so to speak - retvrded. lifetime outcomes ≈ f(effort, persistence, stochastic initial conditions) where stochastic initial conditions ≈ spawn parameters (family, health, geography, f(time)). given roughly similar human hardware, the gradient of success is driven less by raw cognition and more by repeated work plus favorable draws from the luck distribution.

the republic of india nowadays:

@urgfsmeftalspas Secure a job, max out substances and maybe a few trips w homies

what r u supposed to do in ur last year of college i feel like i had a better idea of what i wanted to do with my life before coming to college than i do rn living semester to semester has done irreparable damage to my brain

“How dare everyone use the same brand as me. How am i going to stand out and consider myself elite anymore “

Arey India ke industry walon, koi IIT Bombay main bhi khol do is tarah ki fundu lab. Tumhe nahi chahiye CUDA optimized kernel ya koi aur innovation? Mere bachche taras gaye hain GPU access aur industry-relevant problem pe kaam karne ke liye. cuda-agent.github.io

@d0ntblameprachi Wat da hell

i just woke up khamenei is dead?

“male loneliness epidemic” when you close the twitter app

sorry to bite this ragebait but these are the kind of people who have never multiplied two matrices and think AI is a long chain of if-else statements