Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
5,018 documents
The article describes Tutorial (TUT) as a meme token that began as a demonstration for launching a cryptocurrency on BNB Chain and is presented as an educational project. Its central feature is Tutorial Agent, an AI assistant intended to explain topics such…
The guide introduces Lumibot as an open-source Python framework for developing, backtesting, and deploying automated strategies across supported brokers and exchanges. It describes a strategy structure with setup and market-data iteration steps, and notes an…
Aethir is described as a decentralized network that pools underused GPUs from data centers, businesses, mining operations and individual owners. Its stated aim is to expand access to computing for AI, machine learning and cloud gaming. The article outlines…
The document describes Bless Network as a decentralized computing system that assigns workloads to spare capacity on personal devices. It says tasks are matched to device capabilities, randomized across nodes, and run in a WebAssembly environment intended to…
The article outlines a proposed model for venture funding that combines blockchain, artificial intelligence, token-based governance, and decentralized autonomous organizations. It describes AI as a potential aid to founders through operational risk…
The document presents BIO Protocol V2 as a decentralized science project that applies blockchain, token incentives, and AI tools to biotechnology research. Its proposed mechanisms include fixed-price token offerings at lower fully diluted valuations, staking…
The document describes Grass as a Solana-based project that uses a network of residential internet users’ nodes to collect and organize public web data for AI training. It presents GRASS as a utility token for transactions, staking, rewards, and governance,…
The article describes agentic commerce as shopping delegated to AI systems, shifting commercial decisions from human browsing and checkout toward user intent. It argues that merchants may need to make product information and trust signals legible to agents,…
The document outlines American Exceptionalism Acquisition Corp A, a $250 million SPAC targeting DeFi, artificial intelligence, energy, and defense. Its DeFi thesis centers on connecting traditional finance with blockchain systems through tokenized assets,…
The article describes possible uses of artificial intelligence in blockchain games, including adaptive non-player characters, personalized experiences, and software that adjusts in-game token supply, demand, or rewards. It also explains Web3 gaming concepts…
The document describes DeepSeek’s AI background, its open-source model, and the interest in a cryptocurrency token inspired by the platform. It states that DeepSeek itself has not issued a token, making claims of an official connection a key point for…
The document presents KapKap, a Web3 gaming platform backed by Animoca Brands, and describes its Key Attention Pricing System (KAPS). The system is intended to measure user engagement, creative contributions, and community influence, then represent that…
The document introduces Nodecoin, the token associated with Nodepay, a platform described as using participants’ unused internet bandwidth to support real-time data retrieval and AI training. It explains that contributors may receive tokens for providing…
The document describes app-based crypto mining services that let users participate without owning mining hardware. It highlights AI systems that allocate computing resources and seek to improve efficiency, renewable energy use, automated rewards, mobile…
The document explains a proposed market-cycle pattern in which Bitcoin halvings reduce new issuance, a Bitcoin rally may follow, and liquidity may then move into altcoins. It suggests considering projects with real-world uses and sustainable tokenomics, and…
The document explains Starknet as an Ethereum Layer 2 that batches transactions off-chain and uses ZK-STARK proofs to validate batches on Ethereum. It describes sequencers as responsible for executing and grouping transactions, and presents STARK proofs as…
The document introduces 0G as the token of an AI-focused Layer 1 blockchain. It describes a modular system intended to support decentralized AI operations, including model training and algorithm execution, with an emphasis on scalable and verifiable…
The document explains the Render Network as a decentralized marketplace connecting people who need GPU capacity for graphics and other compute tasks with providers who have spare resources. RNDR is described as the network’s utility token for payments, with…
The document sketches a progression from early decentralized exchanges, through liquidity mining and yield farming, to proposed DeFi applications using artificial intelligence and machine learning. It describes predictive models, autonomous agents that…
The document presents Aethir as a blockchain-based network that distributes GPU capacity for AI training, data analysis, and cloud gaming. It describes a proposed alternative to centralized cloud providers, with compute resources pooled across a distributed…
The document describes Bittensor as decentralized infrastructure for AI services organized around subnets, with TAO used to support mining, validator incentives, subnet activity, and governance. It attributes growing attention to the subnet market to…
The document introduces Newton Protocol as infrastructure for creating, authorizing, and governing automated on-chain agents. It presents a modular architecture intended to make automated processes more transparent and verifiable than centralized…
The document describes decentralized prover networks as distributed systems that pool computing resources to perform computations for blockchain applications. It explains how zero-knowledge proofs can let others verify a computation without exposing the…
The article describes three AI-supported approaches an exchange says it uses to detect fraud. Facial recognition is used to identify people operating multiple accounts. Machine translation helps analyze peer-to-peer messages alongside behavior and…