What began as an AI company trying to seek solutions in order to pay remote (unbanked) workers, Near AI became, in 2018, Near Protocol. Its sharded design was inspired by modern database architecture and large language model (LLM) training. Near Protocol aimed to solve the scalability trilemma, through a modular approach, combining data availability sharding with stateless validation. By abstracting away archaic blockchain standards, Near basically enabled decentralised full stack development and, in terms of UX, a distributed custodial solution via chain abstraction and account aggregation.We were joined by Illia Poloshukhin, co-founder of Near Protocol, to discuss Near’s journey, from AI company to high-throughput L1 blockchain, and how LLM training influenced the modular design choice.Topics covered in this episode:Illia’s background in AI & MLScaling large language models (LLMs) and the role of attentionStochastic Parrot vs. Understanding spectrumFrom Near AI to Near Protocol and the role of LLMsHow Near abstracted the blockchain away and enabled decentralised full stack developmentDefining ecosystem standards to improve UXChain abstraction, account aggregation and interoperabilityChain threshold signatureNear’s intent layerNear’s modularity, Nightshade sharding & stateless validationEigenLayer integrationEpisode links:Illia Polosukhin on TwitterNear Protocol on TwitterSponsors:Gnosis: Gnosis builds decentralized infrastructure for the Ethereum ecosystem, since 2015. This year marks the launch of Gnosis Pay— the world's first Decentralized Payment Network. Get started today at - gnosis.ioChorus1: Chorus1 is one of the largest node operators worldwide, supporting more than 100,000 delegators, across 45 networks. The recently launched OPUS allows staking up to 8,000 ETH in a single transaction. Enjoy the highest yields and institutional grade security at - chorus.oneThis episode is hosted by Meher Roy & Felix Lutsch. Show notes and listening options: epicenter.tv/529