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L2s inherited Ethereum's speed. The sequencer never made the trip. Arbitrum, Base & Optimism each run on ONE sequencer: a single node orders every transaction. That node can censor a wallet, reorder any trades, or halt the chain. Which L2 decentralises its sequencer first?

Mercek

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18,047 views • 3 months ago •via X (Twitter)

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Sustainable creator economy is the future of NFT innovation. We looked for a chain with embedded royalties at the node level and didn’t find one. So we launched our own. RARI chain, Arbitrum L3 with sequencer level royalties enforcement is live on Mainnet 👇🏻

Sustainable creator economy is the future of NFT innovation. We looked for a chain with embedded royalties at the node level and didn’t find one. So we launched our own. RARI chain, Arbitrum L3 with sequencer level royalties enforcement is live on Mainnet 👇🏻

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✨ Introducing the easiest way to force include txs on L2 Connect to dapps & send deposit txs on L1 for Optimism chains, with a single toggle! 🧠 be ahead of the curve if the L2 sequencer goes down

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1/ From the very first day, we were promised that an #Ethereum node could run on any consumer device. In 2024, you can run on a $200 ARM64 board using ~10w: - 1 Archive node + a validator client - A Supernode (L1+L2 on the same device) This is called decentralization. +info👇

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Ethereum on ARM (and RISC-V) 🦇🔊🐼👉👈🐼

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Arcana Network

27,107 views • 1 year ago

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vasucrypto

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232,783 views • 1 year ago

Introducing ZEPHY — every AI model. One window. Zero terminal. What you can do without ever leaving a single window: → Chat with cloud OR local/offline models, with smart routing that automatically picks the best one → Pull any model straight from Hugging Face uncensored too, auto-fit to your GPU → Write & run code in the built-in code editor → Chain steps into workflows on the node canvas → Generate media → Manage assets with an integrated crypto wallet Open source · Windows / macOS / Linux · no keys, no card. Site live -

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Pemersatu bangsa

17,800 views • 3 months ago

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Graph Convolutional Network by hand ✍️ ~ 12 steps walkthrough below Graph Convolutional Networks (GCNs), introduced by Thomas Kipf and Max Welling in 2017, are the tool for data shaped like a graph: social networks, recommendations, biological networks, drug discovery, molecular chemistry. I drew and calculated a simple GCN entirely by hand. Goal: run a two-layer GCN, then a small classifier, on a five-node graph, filling in every cell yourself. 1. Given A graph of five nodes, A to E, with edges between some of them. 2. Adjacency matrix (neighbors) Put a 1 wherever two nodes share an edge, in both directions. 3. Adjacency matrix (self) Add 1s down the diagonal, one self-loop per node. That is just adding the identity matrix. 4. Messages Multiply each node's embedding by the weights and biases, then ReLU. Negatives become 0. 5. Pooling Multiply the messages by the adjacency matrix. Each node gathers the messages of its neighbours and itself. 6. Visualize Node A pools [3,0,1] + [1,0,0] = [4,0,1]. 7. Second GCN layer Messages again: weights, biases, ReLU. 8. Pooling again Pool over each node and its neighbours, once more. 9. Visualize Node C pools [1,2,4] + [1,3,5] + [0,0,1] = [2,5,10]. 10. Fully connected layer Weights, biases, ReLU. This time there are no neighbours to pool, just the node itself. 11. Linear layer One more: weights and biases. 12. Sigmoid Squash each score to a probability (≥ 3 → 1, 0 → 0.5, ≤ -3 → 0). That is the classification for each node. You have just classified every node in the graph by hand. ✍️ The outputs: A: 0 (very unlikely) B: 1 (very likely) C: 1 (very likely) D: 1 (very likely) E: 0.5 (neutral) The takeaway: a GCN layer is two parts. The top part pools each node with its neighbours through the adjacency matrix. The bottom part is an MLP that transforms each node on its own. A transformer layer has the same two parts, with an attention matrix where the adjacency matrix was. Both matrices do one job, mixing across positions: attention over tokens, adjacency over nodes. In my class I call the GCN the transformer's little cousin: a bit more stubborn, because its attention is fixed by the graph rather than computed from Q, K, and V. Draw the two side by side and the resemblance is hard to miss. 💾 Save this post! #AIbyHand #GraphNeuralNetworks #DeepLearning

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Every EVM chains. One agentic gateway into Robinhood Chain. Project:VEX × Relay routes capital from Ethereum, Base, Arbitrum, Optimism, BNB Chain, and more into Robinhood. Give VEX one prompt/mission. It finds a live Relay route, verifies the wallet scope, assets, amount, slippage, and transaction steps, signs transactions locally, and tracks the destination fill. Bridge your capital into Robinhood. Teach VEX your strategy. Enable self-learning through execution. Let VEX operate autonomously within your rules. One mission. Your agent. 🟦

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39,721 views • 1 month ago

The first – and only – on-chain 2FA protection in the industry. Enabling a new security standard, one that can make any #MultiversX wallet practically unbreakable. Here’s how Guardians work & why 25% of our network daily transactions already take advantage of them.

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Multiversᕽ

35,756 views • 2 years ago

7 steps and 2 clues created a woman who was bought a drink by a stranger. She doesn't exist. A stranger sat at a club bar last week. She picked out a man, started a conversation, bought him a round. He smiled back. The whole scene lived in a 6-second clip that pulled comments asking who she was. She was never there. No club, no drinks, no face that belongs to anyone. Here is the full build, 7 steps end to end. Open Pinterest, search “girl selfie,” save one image. Open Nano Banana Pro and swap the face with a single prompt. That photo now belongs to no one. Move the image into a node editor. Create 3 nodes: a reference image node, a text node, a video generator node. Drop the photo into the image node. Write 1 video prompt into the text node, the line that turns a still frame into motion. Connect text to text-in, image to image-in. Select Kling 2.6, set duration, switch sound on. Hit generate. 2 prompts. One face that exists nowhere. A 6-second clip people argued was real. The next person who buys you a drink at a bar might run on a text prompt.

7 steps and 2 clues created a woman who was bought a drink by a stranger. She doesn't exist. A stranger sat at a club bar last week. She picked out a man, started a conversation, bought him a round. He smiled back. The whole scene lived in a 6-second clip that pulled comments asking who she was. She was never there. No club, no drinks, no face that belongs to anyone. Here is the full build, 7 steps end to end. Open Pinterest, search “girl selfie,” save one image. Open Nano Banana Pro and swap the face with a single prompt. That photo now belongs to no one. Move the image into a node editor. Create 3 nodes: a reference image node, a text node, a video generator node. Drop the photo into the image node. Write 1 video prompt into the text node, the line that turns a still frame into motion. Connect text to text-in, image to image-in. Select Kling 2.6, set duration, switch sound on. Hit generate. 2 prompts. One face that exists nowhere. A 6-second clip people argued was real. The next person who buys you a drink at a bar might run on a text prompt.

RGK

16,209 views • 3 months ago

THIS DEVELOPER CONNECTED 8 NVIDIA DGX SPARKS INTO ONE CLUSTER - AND RAN AN 800GB MODEL THAT MADE HIM 10X MORE PRODUCTIVE 21:47 he says it straight - "this is a terabyte of VRAM - we ran Quen 3.5, 800GB on disk, a model that doesn't even fit on a single Mac Studio - 24 tokens per second - I'd say that's a win" 8 Sparks connected through a $1,300 switch via RDMA over Ethernet - each node adding 128GB of memory into one unified pool of 1TB started with one Spark at 3 tokens per second - every added node doubled the speed - and eight together deliver 24 tokens on a model that physically cannot run anywhere else Kimi K2 at 600GB loaded in 15 minutes, 115GB per node, 13 tokens per second - a model that simply cannot run on anything smaller Claude helped configure the entire cluster - SSH mesh across all 8 machines, network config, jumbo frames, QSFP port speeds - all from one terminal most people rent cloud compute for models this size at $2,000+/month - he built the cluster once and now every token costs 20x less

THIS DEVELOPER CONNECTED 8 NVIDIA DGX SPARKS INTO ONE CLUSTER - AND RAN AN 800GB MODEL THAT MADE HIM 10X MORE PRODUCTIVE 21:47 he says it straight - "this is a terabyte of VRAM - we ran Quen 3.5, 800GB on disk, a model that doesn't even fit on a single Mac Studio - 24 tokens per second - I'd say that's a win" 8 Sparks connected through a $1,300 switch via RDMA over Ethernet - each node adding 128GB of memory into one unified pool of 1TB started with one Spark at 3 tokens per second - every added node doubled the speed - and eight together deliver 24 tokens on a model that physically cannot run anywhere else Kimi K2 at 600GB loaded in 15 minutes, 115GB per node, 13 tokens per second - a model that simply cannot run on anything smaller Claude helped configure the entire cluster - SSH mesh across all 8 machines, network config, jumbo frames, QSFP port speeds - all from one terminal most people rent cloud compute for models this size at $2,000+/month - he built the cluster once and now every token costs 20x less

Noisy

185,632 views • 2 months ago

Hedgehog Trades: Bet on the Chain, Not Just the Coin: 🫥 #Hedgehog 🦔 turns blockchain activity into binary trades: for example, you can go UP or DOWN on #Ethereum’s base fee over the next 10-minute window, bet on whether #BTC perp funding rates will rise, or hedge L2 posting costs when a batch-heavy bot runs each market settles off real on-chain metrics, with short cycles and transparent odds, so traders speculate on chain volatility, apps hedge operational budgets, and mints offset gas spikes, all without price speculation. Follow Hedgehog 🦔 🏆 #dyor

Hedgehog Trades: Bet on the Chain, Not Just the Coin: 🫥 #Hedgehog 🦔 turns blockchain activity into binary trades: for example, you can go UP or DOWN on #Ethereum’s base fee over the next 10-minute window, bet on whether #BTC perp funding rates will rise, or hedge L2 posting costs when a batch-heavy bot runs each market settles off real on-chain metrics, with short cycles and transparent odds, so traders speculate on chain volatility, apps hedge operational budgets, and mints offset gas spikes, all without price speculation. Follow Hedgehog 🦔 🏆 #dyor

zhao

15,931 views • 6 months ago

ComfyUI Tutorial for Beginners: Text-to-Image & Image-to-Image Workflows One graph, two workflows and Module 2 is where you build it node by node instead of loading someone else's. We start from a blank canvas and wire every connection, then change a single value and turn the same graph into image-to-image. What you'll learn: → The 5 core nodes, connected one at a time — checkpoint, CLIP encode, KSampler, empty latent, VAE decode → Why the data flows the way it does, not just where the wires go → Every KSampler setting: seed, steps, CFG, sampler, scheduler → Denoise from 0.9 to 0.0 — the one value that decides how much of your source survives → Locking seeds and generating takes instead of chasing one perfect image → Preview vs. save, and why every image carries the graph that made it → Reopen any result in your asset library as a live workflow → The 6 errors that break Comfy most often → How to read a red node like a sentence Click the links below to run the workflow ⬇️

ComfyUI Tutorial for Beginners: Text-to-Image & Image-to-Image Workflows One graph, two workflows and Module 2 is where you build it node by node instead of loading someone else's. We start from a blank canvas and wire every connection, then change a single value and turn the same graph into image-to-image. What you'll learn: → The 5 core nodes, connected one at a time — checkpoint, CLIP encode, KSampler, empty latent, VAE decode → Why the data flows the way it does, not just where the wires go → Every KSampler setting: seed, steps, CFG, sampler, scheduler → Denoise from 0.9 to 0.0 — the one value that decides how much of your source survives → Locking seeds and generating takes instead of chasing one perfect image → Preview vs. save, and why every image carries the graph that made it → Reopen any result in your asset library as a live workflow → The 6 errors that break Comfy most often → How to read a red node like a sentence Click the links below to run the workflow ⬇️

ComfyUI

52,731 views • 10 days ago

What if you could own a piece of the world's first orbital pharmaceutical laboratory? Acme Space is not a crypto concept or a whitepaper promise, it is a real aerospace program with NASA wins under its belt, launching actual hardware into orbit for its first physical space mission, and bringing space exploration, decentralized science, and DePIN infrastructure on-chain via Base. ACME's orbital supercomputer is designed to run pharmaceutical research in microgravity, unlocking drug discovery that is physically impossible on Earth, with Ankr now live as the official infrastructure partner powering its RPC and node layer. August 17th at 1PM UTC, ACME and Ankr are hosting a major AMA, and the Phase 1 Node Sale opens August 18th at 15:00 UTC for a strict 48-hour window. Space is going on-chain, and this is the entry point. Learn more: Disclaimer: This content was produced in collaboration with the client and is intended for informational purposes only. It does not constitute financial or investment advice. Always conduct your own research before making any financial decisions.

What if you could own a piece of the world's first orbital pharmaceutical laboratory? Acme Space is not a crypto concept or a whitepaper promise, it is a real aerospace program with NASA wins under its belt, launching actual hardware into orbit for its first physical space mission, and bringing space exploration, decentralized science, and DePIN infrastructure on-chain via Base. ACME's orbital supercomputer is designed to run pharmaceutical research in microgravity, unlocking drug discovery that is physically impossible on Earth, with Ankr now live as the official infrastructure partner powering its RPC and node layer. August 17th at 1PM UTC, ACME and Ankr are hosting a major AMA, and the Phase 1 Node Sale opens August 18th at 15:00 UTC for a strict 48-hour window. Space is going on-chain, and this is the entry point. Learn more: Disclaimer: This content was produced in collaboration with the client and is intended for informational purposes only. It does not constitute financial or investment advice. Always conduct your own research before making any financial decisions.

Mario Nawfal

73,179 views • 27 days ago

We cracked on-chain privacy... ⛓️💥 Multiple users. One address. Zero information leakage. Our CTO, koreli.eth, presented the Hinkal wallet architecture at Devcon Argentina - Ethereum's flagship developer conference, breaking down the full Hinkal wallet architecture: ZK proofs, stealth addresses, and UTXO pools on EVM. Enterprise-grade privacy that works seamlessly with any DeFi protocol. "This is a normal transaction in Hinkal" - That's the point. Privacy by default. 🎙️ Watch him walk you through the magic:

We cracked on-chain privacy... ⛓️💥 Multiple users. One address. Zero information leakage. Our CTO, koreli.eth, presented the Hinkal wallet architecture at Devcon Argentina - Ethereum's flagship developer conference, breaking down the full Hinkal wallet architecture: ZK proofs, stealth addresses, and UTXO pools on EVM. Enterprise-grade privacy that works seamlessly with any DeFi protocol. "This is a normal transaction in Hinkal" - That's the point. Privacy by default. 🎙️ Watch him walk you through the magic:

hinkal

12,911 views • 8 months ago