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A chess game is showing what Kaspa's new proof opcodes actually do A testnet demo runs full multiplayer chess directly on Layer 1. The rules execute off-chain inside a RISC Zero virtual machine, then compress into one small proof that every Kaspa node checks. Illegal moves get rejected by...

49,103 次观看 • 4 天前 •via X (Twitter)

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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

Tom Yeh

16,744 次观看 • 15 天前

This is another piece about #kaspa and why you should accumulate as much as possible. I think people don't realize yet the tangible progress that $kas had from the launch of the project. And who complains about the chart going sideways for a few months, that is called redistribution after an amazing run during the bear market. Enjoy. Kaspa: The Blockchain Speed Demon Redefining Crypto Efficiency Kaspa has emerged as a significant player in the cryptocurrency landscape, particularly noted for its advancements in transaction speed and scalability while maintaining the foundational principles of Bitcoin (BTC). Here's an insightful look into Kaspa's achievements and its relation to Bitcoin: Unprecedented Speed on Testnet: Kaspa's testnet has demonstrated remarkable speed, achieving up to 10 blocks per second (BPS). This is a monumental leap when compared to Bitcoin, which processes about one block every 10 minutes. This speed was showcased in Kaspa's Testnet 11, where the network's peer-to-peer dynamics and node health remained stable, indicating the robustness of its design. This capability is facilitated by Kaspa's unique implementation of the GHOSTDAG protocol, which allows for parallel processing of blocks, significantly enhancing throughput compared to traditional blockchain structures. Similarities to Bitcoin: Decentralization and Security: Just like Bitcoin, Kaspa uses a Proof-of-Work (PoW) consensus mechanism, ensuring that the network remains decentralized and secure. Kaspa's approach, however, does not orphan blocks created in parallel but instead orders them within the consensus, maintaining a high degree of security without sacrificing speed. No Premine or ICO: Kaspa was launched with a fair distribution method, eschewing pre-mines or initial coin offerings, mimicking Bitcoin's launch ethos to ensure a level playing field for all participants from the outset. Scarcity: Similar to Bitcoin, Kaspa has a capped supply, which encourages a deflationary model. This aspect could potentially make Kaspa an attractive store of value, akin to Bitcoin's role as "digital gold," although Kaspa brands itself more as "digital silver" due to its focus on speed and utility. Advancements Beyond Bitcoin: Scalability: Where Bitcoin struggles with scalability due to its block size limit, Kaspa's BlockDAG structure enables it to process transactions at a scale that Bitcoin cannot match without significant network congestion or fee hikes. This makes Kaspa potentially more suitable for everyday transactions. Transaction Confirmation Time: Kaspa transactions are confirmed in about 10 seconds, compared to Bitcoin's minimum of 10 minutes, making it highly efficient for real-world applications where speed is crucial. Energy Efficiency: By design, Kaspa aims to be less energy-intensive than Bitcoin while maintaining PoW security, leveraging algorithms like kHeavyHash which are more suited to the high-throughput environment of a DAG. Future Adaptability: Kaspa plans to introduce features like smart contracts with very low fees, potentially positioning it as a platform for decentralized applications (dApps) without the scaling issues faced by other networks like Ethereum. The Road Ahead: Kaspa is not just another cryptocurrency; it's a project that challenges the established norms of blockchain scalability. By solving the blockchain trilemma of security, scalability, and decentralization, Kaspa could set a new standard for what's possible in cryptocurrency. However, its relatively new status in the market means it has yet to prove its resilience over decades like Bitcoin. The community's enthusiasm, combined with ongoing development like the Rust rewrite for better performance, suggests Kaspa is on a path to potentially significant growth and adoption. In conclusion, while Kaspa shares foundational similarities with Bitcoin, its advancements in speed, scalability, and adaptability make it a compelling alternative or companion in the crypto ecosystem. Its testnet achievements are just the beginning of what could be a transformative journey in the blockchain space.

Satoshi Vibz

11,501 次观看 • 1 年前

Aravind Srinivas just described a future most founders are pretending they are ready for. One person. One machine. A company that runs itself. Srinivas: “Buy a Mac mini, set up a Perplexity personal computer, and run their business on that.” Not a side project. Not a pitch deck. A real business with real revenue while the founder is not in the building. AI runs the ads. Handles SEO. Integrates Stripe. Ships features. Answers customers. All of it executing without a single employee. Srinivas: “Have this all working while you can be sipping wine in Napa.” But before he sold the dream he killed the one most people are already chasing. Srinivas: “Everybody talks about this one-person one-billion-dollar company. It’s not truly moving the GDP by one billion. It’s not truly creating new value.” One researcher collecting a billion in equity does not grow an economy. It rearranges numbers between balance sheets. Nothing gets built. No customer gets served. That is not value creation. That is valuation creation. Srinivas wants no part of it. What he described is the opposite. The person driving Uber between shifts who has the idea but not the payroll. Not the engineering. Not the marketing. Not the support staff. That person gets a machine that replaces all of it. Hundreds of thousands in revenue. Millions. Generated by autonomous systems doing the work that used to require ten employees and a burn rate. Not paper wealth. Not valuation theater. Output that moves through an economy and touches real customers. That is what moves GDP. Not one person worth a billion dollars. A million people each building something worth a million. That math rewrites a country. Then Srinivas said the part that separates him from every hype merchant in the room. Srinivas: “Everybody thinks AI is already there. It’s not there yet. Someone has to do that hard work.” The vision is real. The infrastructure is not. The agents are not autonomous. The integrations are not seamless. The plumbing is not finished. Someone has to wire the APIs. Connect the billing. Build the bridge between what a founder wants and what a machine can deliver. That work is not a keynote. It is not a tweet thread. It is engineering that nobody wants to do and everybody will depend on. Whoever finishes it first does not just build a product. They hand every ambitious person on Earth a company they can run alone. The corporations that need five hundred people to do what one founder with the right infrastructure could do are not efficient. They are exposed. And the person building the thing that exposes them just told you exactly what it looks like. He also told you it is not going to build itself.

Dustin

64,593 次观看 • 4 个月前