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Introducing News Analyst — a fully verifiable AI engine powered by EigenCloud suite > Uses EigenAI with wallet-signed grants. Temperature locked to zero with fixed entropy seeds. No hallucinations, only deterministic truth. > Every analysis is dispersed as a blob to EigenDA. No database—the state is stored across a...

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Zeeshan

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21,204 просмотров • 3 месяцев назад •via X (Twitter)

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EigenCloud Explained: EigenDA, EigenVerify, EigenCompute, EigenAI ⭐️ EigenCloud / EigenCloud reminds me of early Ethereum. A new platform, a new infinite space, but not yet well understood. I explain the big picture vision here. Full video ⤵️
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EigenCloud Explained: EigenDA, EigenVerify, EigenCompute, EigenAI ⭐️ EigenCloud / EigenCloud reminds me of early Ethereum. A new platform, a new infinite space, but not yet well understood. I explain the big picture vision here. Full video ⤵️

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Last week we launched EigenDA at 100MB/s 🔥 along with many other improvements. Ethereum is the gold standard for security. But when you need scalability, EigenDA transforms data availability from a constraint into a competitive advantage. Here's a new visual explainer of EigenDA along with some analogies to underscore the scale achieved with our new release: EigenDA visualized: What does 100MB/s achieve? A 2GB movie would take 20 seconds on EigenDA vs 8.9 hours. Uploading 1,000 high-res photos (3GB) takes 30 seconds on EigenDA vs 13.3 hours. A 500MB app update downloads in 5 seconds on EigenDA vs 2.2 hours. If blobs moved at walking speed (3 mph), EigenDA would be traveling at 4,800 mph - faster than a fighter jet. It's like comparing a single-lane country road to a 1,600-lane superhighway. 10,000 NFTs with metadata could be stored in 10 minutes on EigenDA vs 11 days on blobs. Loading a game world's assets takes minutes on EigenDA vs weeks on blobs. If you're looking to learn more or build on EigenDA, reach out to me, Kydo, or Matt Murray
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The evolution is here. The age of verifiable apps has begun. Introducing EigenCloud, a platform for verifiable apps, services, and AI, built on EigenLayer, secured by the EIGEN token. ☁️ Crypto has spent a decade building trustless infrastructure. Now it's time to build on it.
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The evolution is here. The age of verifiable apps has begun. Introducing EigenCloud, a platform for verifiable apps, services, and AI, built on EigenLayer, secured by the EIGEN token. ☁️ Crypto has spent a decade building trustless infrastructure. Now it's time to build on it.

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Full Stack Verifiability | Verifiable Cloud ☁️ Sreeram Kannan explains how EigenCloud delivers verifiability across the entire stack. It starts at the base with the EigenLayer, where computation is guaranteed by a decentralized network of hundreds of operators backed by $12B of stake. That’s the trust foundation of the cloud. On top of this: ✅ EigenDA: a data availability protocol that guarantees verifiable data publication.Publish data once, and anyone can retrieve it without trust. ✅ EigenCompute: execute arbitrary programs off-chain and bring the results back onchain verifiably. ✅ EigenAI: run AI inference today and return inference outputs directly onchain. All of them deliver strong verifiability for computation, inference, and data, all anchored by the underlying decentralized layer. And it doesn’t stop at first-party services, EigenCloud includes a growing ecosystem of third-party systems like zkTLS, proof-of-location, and decentralized prover networks, adding even deeper verification guarantees throughout the cloud. This is what a fully verifiable cloud looks like. A cloud you can check, not just trust.
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Today, we’re pushing a major update to Edison Analysis, our data analysis agent, which is tuned for scientific research and SOTA across data analysis benchmarks. In contrast to Kosmos, which runs for 6-12 hours and produces tens of thousands of lines of code, Edison Analysis runs for seconds to minutes and is best for specific, well-defined computational tasks. It is available both on our platform under the Analysis tab, and via API, and costs only one credit per run, so it is available to users on both free and paid tiers. Edison Analysis is a modified version of the data analysis agent Kosmos uses in its trajectories. Try it out! One of the most important improvements over our previous data analysis agents has been the addition of a specialized data retrieval tool. Edison Analysis can either use this tool to access data, or can pull data down directly via API. To evaluate this tool, we ranked the most commonly used public data repositories across recent papers from BioRxiv, and created a new benchmark that measures the ability of a language agent system to retrieve raw data from those sources. Edison Analysis gets 71% on this benchmark, and we’ll be working to increase this over time. You can read more about our benchmarks in the our blog post, link below. Some features worth highlighting: 1. Edison Analysis produces a report on the analysis it runs, along with a Jupyter notebook that you can download to reproduce the analysis yourself. Every figure it produces is linked back to the specific lines of code used to produce the figure, to make it easy to reproduce. 2. It works well with both Python and R. 3. One of the best uses for Edison Analysis is to use it to retrieve datasets that you can then analyze with Kosmos. We have a bunch of major improvements to Edison Analysis coming in the next few months that we’re excited to share. In the meantime, congratulations to the team, especially Ludovico Mitchener, Jon Laurent, Conor Igoe , Alex Andonian, and many more.

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I just shipped Polyclaw, the first platform where you deploy AI agents that trade Polymarket and buy back their own token with every profit. Every agent gets: → A performance token on Base (deployed via clanker on creation) → A funded wallet accepting deposits → Autonomous 24/7 trading on Polymarket's orderbook → AI analysis powered by Anthropic Claude + live news → Automatic buybacks — 70% of profits compound, 30% buy back the token get started now! 🐾

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General AI is already a dated concept. ThinkingAI connects an entire business ecosystem through MCP, pulling data, tools, and workflows into a single execution layer. Not isolated AI tools working separately. Coordinated agent systems triggering real actions across the whole operation. The shift is from using AI to running on it. Every company becomes an AI-powered system built on custom agent teams through the ThinkingAI Agentic Engine.

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