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Illia Polosukhin

NEAR co-founder and NEAR AI founder

Blockchain and AI design, from coauthored machine-learning papers to NEAR's approach to programmable money.

@ilblackdragon on X

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Why read Illia Polosukhin?

Illia's work connects two useful reading paths: machine-learning research and the design of blockchain applications. Attention Is All You Need is the technical foundation for understanding his research background. Neural Program Search asks a different question: how to generate a program from a natural-language description and a few examples of its inputs and outputs.

His NEAR commentary gives you the builder's own explanation of the network's direction. In his September 2026 post, he distinguishes permission to own assets or deploy a contract from the policies of individual applications and liquidity providers. Start there for a concrete protocol-versus-application distinction, then use the papers if you want to explore the AI research behind his broader work.

Selected work

  1. Post,

    Does a permissionless network require every application to process every transaction? His opening distinction explains how network access and a provider's transaction policy are separate questions.

    Cite this selection

    XFollowList, “Permissionless programmable money and application policies” reading notes in the Illia Polosukhin profile. https://xfollowlist.com/people/illia-polosukhin#work-404268875cce

    The linked work is the original source; this permalink identifies XFollowList’s reason to read it. Original work published .

    Profile-source checking date and references · Dated reading map

  2. Paper,

    What was the Transformer proposal? This coauthored research paper introduces an architecture based on attention instead of recurrence or convolution. It is a technical paper for readers with machine-learning background.

    Cite this selection

    XFollowList, “Attention Is All You Need” reading notes in the Illia Polosukhin profile. https://xfollowlist.com/people/illia-polosukhin#work-a7468c685165

    The linked work is the original source; this permalink identifies XFollowList’s reason to read it. Original work published .

    Profile-source checking date and references · Dated reading map

  3. Paper,

    Can descriptions and input/output examples guide program generation? Coauthored with Alexander Skidanov, this paper combines a learned model, a domain-specific language and program search.

    Cite this selection

    XFollowList, “Neural Program Search: Solving Programming Tasks from Description and Examples” reading notes in the Illia Polosukhin profile. https://xfollowlist.com/people/illia-polosukhin#work-c51ff03b49f9

    The linked work is the original source; this permalink identifies XFollowList’s reason to read it. Original work published .

    Profile-source checking date and references · Dated reading map

Projects & roles

  • NEAR

    The blockchain he co-founded.

  • NEAR AI

    Its company page identifies him as founder and describes private, verifiable AI infrastructure.

Sources & further reading

Profile sources checked . This describes checking these references, separately from the publication dates of selected works.

Cite this profile’s source check

XFollowList, Illia Polosukhin profile sources. Sources checked 2026-10-09. https://xfollowlist.com/people/illia-polosukhin#sources-checked