CaveeA

[CaveeA @calvazz]

@neetcode1 Is there any feature to 1) invite a friend to a problem 2) start when you want and get the time when you pass all the tests 3) friend can also start when he wants and when both finishes you both can see the time diff somewhere?

[CaveeA @calvazz]

@JessicaPusser @elonmusk @visegrad24 noone has guns here, only police

[Alex Plaskett @alexjplaskett]

The Path of a Packet Through the Linux Kernel

https://t.co/Opd8uuk5OI

[Andrej Karpathy @karpathy]

Sharing an interesting recent conversation on AI's impact on the economy.

AI has been compared to various historical precedents: electricity, industrial revolution, etc., I think the strongest analogy is that of AI as a new computing paradigm (Software 2.0) because both are fundamentally about the automation of digital information processing.

If you were to forecast the impact of computing on the job market in ~1980s, the most predictive feature of a task/job you'd look at is to what extent the algorithm of it is fixed, i.e. are you just mechanically transforming information according to rote, easy to specify rules (e.g. typing, bookkeeping, human calculators, etc.)? Back then, this was the class of programs that the computing capability of that era allowed us to write (by hand, manually).

With AI now, we are able to write new programs that we could never hope to write by hand before. We do it by specifying objectives (e.g. classification accuracy, reward functions), and we search the program space via gradient descent to find neural networks that work well against that objective. This is my Software 2.0 blog post from a while ago. In this new programming paradigm then, the new most predictive feature to look at is verifiability. If a task/job is verifiable, then it is optimizable directly or via reinforcement learning, and a neural net can be trained to work extremely well. It's about to what extent an AI can "practice" something. The environment has to be resettable (you can start a new attempt), efficient (a lot attempts can be made), and rewardable (there is some automated process to reward any specific attempt that was made).

The more a task/job is verifiable, the more amenable it is to automation in the new programming paradigm. If it is not verifiable, it has to fall out from neural net magic of generalization fingers crossed, or via weaker means like imitation. This is what's driving the "jagged" frontier of progress in LLMs. Tasks that are verifiable progress rapidly, including possibly beyond the ability of top experts (e.g. math, code, amount of time spent watching videos, anything that looks like puzzles with correct answers), while many others lag by comparison (creative, strategic, tasks that combine real-world knowledge, state, context and common sense).

Software 1.0 easily automates what you can specify.
Software 2.0 easily automates what you can verify.

[ThePrimeagen @ThePrimeagen]

28 months in to 6 months from AI taking your jobs
* 4 months into 24 months until cursor is obsolete
* 6 months into 6 months until ai writes 90% of your code (part 2, the codening)

[CaveeA @calvazz]

@zack_overflow This is actually my current stack

[Linus ✦ Ekenstam @LinusEkenstam]

This is next level.

MeshBlend for Unreal Engine

Just wow.

[Feoramund @Feoramund]

My sources for algorithms:
- https://t.co/E5WSn9DaWP
- https://t.co/fWAadCS4uM

The pathfinding algorithm is an implementation of Jump Point Search:
- https://t.co/0GnhLlilMV

The visibility algorithm is an implementation of Symmetric Shadowcasting:
- https://t.co/0GTVUbiw8D

[Yohei Nishitsuji @YoheiNishitsuji]

for(float e,i,a,w,x,g,h;i++<99.;){vec3 p=vec3((FC.xy-r)/r*g+2.,g);p.zx*=rotate2D(.5);e=p.y;h=e;for(a=.7;a>.001;a*=.8)p.xz*=rotate2D(5.),e-=w=exp(sin(p.z/a+t)-3.)*a,h+=abs(dot(sin(p.zx/a*.27)*a,r/r));g+=e=min(e,h*.5-1.);o.rgb+=.01-.03/exp(max(s,e)*4e3)/h*hsv(.2/h,.04*h*h,1.);}

[Xor @XorDev]

Blackhole in 350 characters of #GLSL:

vec2 p=(FC.xy*2.-r)/r.y/.7,d=vec2(-1,1),c=p*mat2(1,1,d/(.1+5./dot(5.*p-d,5.*p-d))),v=c;v*=mat2(cos(log(length(v))+t*.2+vec4(0,33,11,0)))*5.;for(float i;i++<9.;o+=sin(v.xyyx)+1.)v+=.7*sin(v.yx*i+t)/i+.5;o=1.-exp(-exp(c.x*vec4(.6,-.4,-1,0))/o/(.1+.1*pow(length(sin(v/.3)*.2+c*vec2(1,2))-1.,2.))/(1.+7.*exp(.3*c.y-dot(c,c)))/(.03+abs(length(p)-.7))*.2);

[FFmpeg @FFmpeg]

FFmpeg makes extensive use of hand-written assembly code for huge (10-50x) speed increases and so we are providing assembly lessons to teach a new generation of assembly language programmers.

Learn more here:
https://t.co/u6MKBb3Xbk

[CaveeA @calvazz]

@EMBuxmann Merry Christmas, late!

[Karl Zylinski @karl_zylinski]

My digital book "Understanding the Odin Programming Language" is OUT NOW! ✨

If you want to learn Odin and demystify low-level programming, then this book is for you!

Read more or buy at: https://t.co/No76UDZrQs

[CaveeA @calvazz]

@ScalpState @tsoding @hajivat Check his ping pong repo on GitHub

[Vivek Galatage @vivekgalatage]

I am reading about Conflict-free Replicated Data Types (CRDT). And I came across these fantastic implementations by Evan Wallace!

It's interesting to see how real-world collaborative applications work with the help of these data structures and algorithms!

Links in 🧵

[pikuma.com @pikuma]

Writing an OS in Rust:

🔗https://t.co/lM60z3EffI

[Daniel Lemire @lemire]

Microsoft makes over a 15 billion dollars of profit per year. And they won't bother to provide a clean, user friendly system. And nobody cares.

It explains so much.

[CaveeA @calvazz]

@AdamDuda @levelsio @sereck28 @vicnaum Italian salaries are basically frozen since we got euro

[CaveeA @calvazz]

@nickchapsas I was just looking today at your lovely L2 repos, great stuff man! Maybe I will fork your l2dotNet ❤️ much love nick