Illia Polosukhin: Near Protocol – From AI to High-Throughput Blockchain

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2y ago 1:28:47

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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 & ML
Scaling large language models (LLMs) and the role of attention
Stochastic Parrot vs. Understanding spectrum
From Near AI to Near Protocol and the role of LLMs
How Near abstracted the blockchain away and enabled decentralised full stack development
Defining ecosystem standards to improve UX
Chain abstraction, account aggregation and interoperability
Chain threshold signature
Near’s intent layer
Near’s modularity, Nightshade sharding & stateless validation
EigenLayer integration

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This episode is hosted by Meher Roy & Felix Lutsch. Show notes and listening options: epicenter.tv/529

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