#randomlinearnetworkcoding 검색 결과

Matrix👨‍💻 while :;do echo $LINES $COLUMNS $(( $RANDOM % $COLUMNS)) $(printf "\U$(($RANDOM % 500))");sleep 0.05;done|gawk '{a[$3]=0;for (x in a){o=a[x];a[x]=a[x]+1;printf "\033[%s;%sH\033[2;32m%s",o,x,$4;printf "\033[%s;%sH\033[1;37m%s\033[0;0H",a[x],x,$4;if (a[x]>=$1){a[x]=0;}}}'

Introducing RND1, the most powerful base diffusion language model (DLM) to date. RND1 (Radical Numerics Diffusion) is an experimental DLM with 30B params (3B active) with a sparse MoE architecture. We are making it open source, releasing weights, training details, and code to…

Hello everyone, Let’s break down how Random Linear Network Coding (RLNC) compares to traditional error correction methods and why it’s a game changer for Web3 & modern networks. 🔹What is RLNC ? Random Linear Network Coding (RLNC) is a network coding technique that transmits…

landscapes of arbitrary detail and expanse can be generated by layering random noise of increasing frequency and decreasing amplitude

🧵 Everyone is chasing new diffusion models—but what about the representations they model from? We introduce Discrete Latent Codes (DLCs): - Discrete representation for diffusion models - Uncond. gen. SOTA FID (1.59 on ImageNet) - Compositional generation - Integrates with LLM 🧱

Matrix while :;do echo $LINES $COLUMNS $(( $RANDOM % $COLUMNS)) $(printf "\U$(($RANDOM % 500))");sleep 0.05;done|gawk '{a[$3]=0;for (x in a){o=a[x];a[x]=a[x]+1;printf "\033[%s;%sH\033[2;32m%s",o,x,$4;printf "\033[%s;%sH\033[1;37m%s\033[0;0H",a[x],x,$4;if (a[x] >= $1){a[x]=0;} }}'

Select one random number : 1-40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Check your DM 24 hours #RubiNetwork

🚨Our new paper: Random Policy Valuation is Enough for LLM Reasoning with Verifiable Rewards We challenge the RL status quo. We find you don't need complex policy optimization for top-tier math reasoning. The key? Evaluating the Q function of a simple uniformly random policy. 🤯

Apple and Meta have published a monstruously elegant compression method that encodes model weights using pseudo-random seeds. The trick is to approximate model weights as the linear combination of a randomly generated matrix with fixed seed, and a smaller vector t.

I don’t know if it’s real, but I did something very similar back in 2003 — I needed random numbers and just hardcoded them.

𝐑𝐄𝐂𝖎𝐏𝐄: (1) Random points on a plane (2) Voronoi digram from points (3) Scale & turn Voronoi cells (4) Orbit the random points. Code & article: community.wolfram.com/groups/-/m/t/3…

Can we go smaller than micro-interactions? How about nano-interactions just because it sounds cool? Interactive random loader made with @rive_app

I continue on little things that GPT-5(-Codex) actually can do. This time the following setup in GPT-Codex-CLI (high mode). Challenge: let the model explain a very popular random generator: Mersenne Twister. With code, formulas, examples etc. (1/n)

BULK Net uses Reed-Solomon erasure coding for data protection and resilience to packet loss. A simple analogy: a parabola is defined by three points. If only they are sent, the loss of one point will make it impossible to restore the curve. @bulktrade 🧠

Quasi-randomized nnetworks in Julia, Python and R thierrymoudiki.github.io/blog/2023/11/2… #Techtonique #DataScience #Python #rstats #MachineLearning

We’ve just built the first SLM on a Fortytwo-generated dataset Announcing Fortytwo’s Strand-Rust-Coder-14B Now the best coding model for Rust Made possible by the high-quality, synthetic dataset, generated through Swarm Inference ✷ Ranked #1 on the RustEvo^2 and Hold-Out…

This is why you shouldn’t use Math.random() in Java for cryptographically sensitive functions (like generating a token), talk by @b4stet4 #hacklu #cryptography

RLNC (Random Linear Network Coding) - makes data transfer more fast and effective. For example, when you want to send a file, the system cut it for a lot small pieces, mix it and sends it in different variations for the whole network. How @get_optimum uses it? Optimum uses it…

#pico8 #tweetcart ::_:: cls(1) srand(34) for y=0,141,3 do x=rnd(144)-8 h=14+rnd(24) for i=0,h do circfill(x-i*2,y+2,(h-i)/6,0) end line(x,y,x,y+2,5) for i=-15,15 do line(x+i*h/80,y-abs(i)/6,x+sin(t()/5+x/150+y/200)/5*h,y-h,i>0 and 3 or 0) end end flip() goto _

LLMs have a repetition problem. ask for a joke → same joke every time ask to roll dice → always returns 4 ask for creative ideas → predictable garbage Try this instead: Generate 5 responses with their corresponding probabilities, sampled at random from the tails of the…