Room Mining

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Room Mining

Room Mining

@RoomMining

Welcome to @RoomMining we focus on stabilizing blockchain mining operations, providing solutions for distributed networks. #blockchain #mining #managment #btc

United States Katılım Mayıs 2017
683 Takip Edilen151 Takipçiler
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Room Mining
Room Mining@RoomMining·
Mining ⛏ SHA-256 cryptocurrencies becomes stable at large enough level of scale, as the cost to attack the Proof of Work network (PoW 51% attack) becomes too expensive and unrealistic. This is why #Bitcoin  remains a stable network 10 years later. ⚡️ #btc
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Isabelle Zhou
Isabelle Zhou@isabelle_zhou·
I’m hiring for my research team @OpenAI 🪄 Data will pave the way for AGI. This is a foundational TPM role to shape frontier AI models with real world data, RL environments, and data acquisition. Looking for: - Entrepreneurial, gritty, high horsepower - Highly technical and deeply curious about AI research - Excited to lead relationships with CEOs and data partners from day 1
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0xMarioNawfal
0xMarioNawfal@RoundtableSpace·
The Hugging bay, The Pirate bay for open LLM's, model weights downloadable with torrents. This is a game changer. huggingbay.xyz
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Room Mining
Room Mining@RoomMining·
@boardyai We offer blockchain mining and management services ⚡️
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Tech with Mak
Tech with Mak@techNmak·
A dev got so frustrated watching his AI agent write 500 lines for a 5-line problem that he built a fix. He called it Ponytail. Named after the guy every team has - long ponytail, oval glasses, been there longer than the version control. You show him fifty lines; he looks at them, says nothing, and replaces them with one. Now your agent does the same. Before writing anything, it looks for a reason not to. 80-94% less code. 47-77% cheaper. 3-6x faster. The best code is the code you never wrote. GitHub Repo: github.com/DietrichGebert…
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Rony
Rony@Ronycoder·
Instead of watching an hour of Netflix, watch this 30-minute speech by the Head of Anthropic’s Coding Agents research team. It will teach you more about vibe coding than 100 paid courses.
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sarpstar
sarpstar@sarpstar·
Viktor X'te tasarım tarafında takip ettiğim tartışmasız en iyi isimlerden biri. Adamın çıkardığı işler her seferinde estetikten yıkılıyor. Ve şimdi Claude Design + Opus 4.7 üzerine 18 dakikalık tutorial çıkarmış. Kendi adıma bu videoyu izledikten sonra tasarımlarınızın tamamen bambaşka bir seviyeye çıkacağına eminim. Claude Design zaten tek başına oyunu değiştiriyor, bir de Viktor gibi birinin elinden öğrenmek varken kaçırılmayacak bir kaynak. Yumulun!
Viktor Oddy@viktoroddy

Claude Design is insane. ❤️‍🔥Just recorded a 18-min tutorial on how to build animated, award-winning websites with Claude Design + Opus 4.7!

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Resolv
Resolv@resolvfinance·
Here’s to the crazy ones.
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Ethereum
Ethereum@ethereum·
ZKPass is built on Ethereum. @zkPass is a privacy-preserving identity protocol letting users prove information about themselves without revealing the underlying data. It enables secure verification of credentials onchain while keeping personal information private by default.
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CG
CG@cgtwts·
Holy shit, this is INSANE. Andrej karpathy just open-sourced an autonomous AI researcher that runs 100 experiments while you sleep > He built a free AI agent that improves itself while you sleep > it runs fully autonomously, executing real experiments with no supervision > runs 100 experiments per night, one every 5 minutes on a fixed budget > edits its own training code, measures validation loss, keeps improvements and discards failures > results automatically adapt to your specific hardware > only one GPU is needed to run it > Best part is it’s completely free.
Andrej Karpathy@karpathy

I packaged up the "autoresearch" project into a new self-contained minimal repo if people would like to play over the weekend. It's basically nanochat LLM training core stripped down to a single-GPU, one file version of ~630 lines of code, then: - the human iterates on the prompt (.md) - the AI agent iterates on the training code (.py) The goal is to engineer your agents to make the fastest research progress indefinitely and without any of your own involvement. In the image, every dot is a complete LLM training run that lasts exactly 5 minutes. The agent works in an autonomous loop on a git feature branch and accumulates git commits to the training script as it finds better settings (of lower validation loss by the end) of the neural network architecture, the optimizer, all the hyperparameters, etc. You can imagine comparing the research progress of different prompts, different agents, etc. github.com/karpathy/autor… Part code, part sci-fi, and a pinch of psychosis :)

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AgentMail (YC S25)
AgentMail (YC S25)@agentmail·
Agents can now create email inboxes with USDC on @base AgentMail supports @CoinbaseDev’s x402 protocol to give agents access to email without accounts or API keys See how it works 👇
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vitalik.eth
vitalik.eth@VitalikButerin·
Now, the quantum resistance roadmap. Today, four things in Ethereum are quantum-vulnerable: * consensus-layer BLS signatures * data availability (KZG commitments+proofs) * EOA signatures (ECDSA) * Application-layer ZK proofs (KZG or groth16) We can tackle these step by step: ## Consensus-layer signatures Lean consensus includes fully replacing BLS signatures with hash-based signatures (some variant of Winternitz), and using STARKs to do aggregation. Before lean finality, we stand a good chance of getting the Lean available chain. This also involves hash-based signatures, but there are much fewer signatures (eg. 256-1024 per slot), so we do not need STARKs for aggregation. One important thing upstream of this is choosing the hash function. This may be "Ethereum's last hash function", so it's important to choose wisely. Conventional hashes are too slow, and the most aggressive forms of Poseidon have taken hits on their security analysis recently. Likely options are: * Poseidon2 plus extra rounds, potentially non-arithmetic layers (eg. Monolith) mixed in * Poseidon1 (the older version of Poseidon, not vulnerable to any of the recent attacks on Poseidon2, but 2x slower) * BLAKE3 or similar (take the most efficient conventional hash we know) ## Data availability Today, we rely pretty heavily on KZG for erasure coding. We could move to STARKs, but this has two problems: 1. If we want to do 2D DAS, then our current setup for this relies on the "linearity" property of KZG commitments; with STARKs we don't have that. However, our current thinking is that it should be sufficient given our scale targets to just max out 1D DAS (ie. PeerDAS). Ethereum is taking a more conservative posture, it's not trying to be a high-scale data layer for the world. 2. We need proofs that erasure coded blobs are correctly constructed. KZG does this "for free". STARKs can substitute, but a STARK is ... bigger than a blob. So you need recursive starks (though there's also alternative techniques, that have their own tradeoffs). This is okay, but the logistics of this get harder if you want to support distributed blob selection. Summary: it's manageable, but there's a lot of engineering work to do. ## EOA signatures Here, the answer is clear: we add native AA (see eips.ethereum.org/EIPS/eip-8141 ), so that we get first-class accounts that can use any signature algorithm. However, to make this work, we also need quantum-resistant signature algorithms to actually be viable. ECDSA signature verification costs 3000 gas. Quantum-resistant signatures are ... much much larger and heavier to verify. We know of quantum-resistant hash-based signatures that are in the ~200k gas range to verify. We also know of lattice-based quantum-resistant signatures. Today, these are extremely inefficient to verify. However, there is work on vectorized math precompiles, that let you perform operations (+, *, %, dot product, also NTT / butterfly permutations) that are at the core of lattice math, and also STARKs. This could greatly reduce the gas cost of lattice-based signatures to a similar range, and potentially go even lower. The long-term fix is protocol-layer recursive signature and proof aggregation, which could reduce these gas overheads to near-zero. ## Proofs Today, a ZK-SNARK costs ~300-500k gas. A quantum-resistant STARK is more like 10m gas. The latter is unacceptable for privacy protocols, L2s, and other users of proofs. The solution again is protocol-layer recursive signature and proof aggregation. So let's talk about what this is. In EIP-8141, transactions have the ability to include a "validation frame", during which signature verifications and similar operations are supposed to happen. Validation frames cannot access the outside world, they can only look at their calldata and return a value, and nothing else can look at their calldata. This is designed so that it's possible to replace any validation frame (and its calldata) with a STARK that verifies it (potentially a single STARK for all the validation frames in a block). This way, a block could "contain" a thousand validation frames, each of which contains either a 3 kB signature or even a 256 kB proof, but that 3-256 MB (and the computation needed to verify it) would never come onchain. Instead, it would all get replaced by a proof verifying that the computation is correct. Potentially, this proving does not even need to be done by the block builder. Instead, I envision that it happens at mempool layer: every 500ms, each node could pass along the new valid transactions that it has seen, along with a proof verifying that they are all valid (including having validation frames that match their stated effects). The overhead is static: only one proof per 500ms. Here's a post where I talk about this: ethresear.ch/t/recursive-st… firefly.social/post/farcaster…
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Jeff Weinstein
Jeff Weinstein@jeff_weinstein·
Autonomous agents are an entirely new category of users to build for, and, increasingly, to sell to. Today, we’re launching (a preview) of machine payments on @stripe—a way for developers to directly charge agents, with a few lines of code. 🤖💸 $ Let’s start tinkering… ⤵️
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Linea.eth
Linea.eth@LineaBuild·
Trustless agents are now live on Linea. ERC-8004 brings verifiable identity and portable reputation to AI agents across Ethereum's ecosystem. An open agent economy where trust compounds, reputation transfers, and agents coordinate.
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Ethereum
Ethereum@ethereum·
The first thing you ever did on ethereum was _______
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