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NEAR co-creation sharing ecological application construction direction and distribution suggestions, covering AI, cross-chain payment, and privacy transactions, among other directions

Illia Polosukhin, co-founder of NEAR, stated that recently the activity of developers within the ecosystem has increased and the development threshold has further lowered, focusing on what kind of applications to build and how to establish distribution channels.In this regard, he proposed a series of potential construction directions, covering AI electronic pets that combine NEAR AI on-chain verifiable reasoning with non-fungible tokens (NFTs), a universal checkout component that supports full-chain intent payments, a decentralized encyclopedia that combines prediction markets with AI-generated content, a privacy off-chain trading (OTC) market based on NEAR Intents and management of anti-liquidation lending and perpetual contracts, a cross-chain activity registration custody tool in the form of a staking deposit, privacy code review agents, enterprise equity structure management tools, Delta neutral strategy management, privacy tracking single transactions based on view keys, end-to-end encrypted medical auxiliary diagnostic systems, privacy voice transcription desktop applications, and AI benchmarking based on private test sets.Regarding product distribution, he suggested combining NEARLegion with community channels like X, achieving multi-chain wallet compatibility through Aurora Intent Connect to lower cross-chain thresholds, and actively expanding across communities and platforms like Product Hunt.

first_img Tavus claims that the Griffin model causes 48% of video call participants to mistakenly believe they are interacting with a real person

AI startup Tavus released a new model called Griffin on October 1, referring to it as the first "human interaction model" that can understand and generate face-to-face conversations, paying attention not only to wording but also to expressions and pauses. Tavus stated that in tests, after a one-minute video call with Griffin-Lite, 26 out of 54 participants (48%) believed the other party was a real person; its previous generation system only convinced 1 out of 41 participants.Participants were told they would have a one-minute video call with another person to discuss things they were looking forward to this year, and only at the end of the call were they asked if they suspected the other party was not a real person. Tavus noted that those who became suspicious typically noticed within 20 seconds. This result comes from Tavus's own research page, where participants were recruited through a channel they call an independent research platform. Community comments on X pointed out that these results have not been independently verified and do not meet standard protocols.In the NVIDIA VideoFDB benchmark, Tavus claimed Griffin-Lite ranked first, with a generation dimension score of 3.83, the next best system scoring 2.8, and human reference scoring 3.92; the perception dimension score was 3.73, with the strongest baseline at 3.44 and human reference at 4.2. Tavus stated that NVIDIA independently conducted this evaluation. Griffin supports full duplex, allowing it to listen, see, and speak simultaneously, with an average audio-video delay of 0.43 seconds on the NVIDIA H100 chip. Tavus completed a $40 million Series B funding round led by CRV in November 2025.
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