I-CARV's D.A.T.A. Uhlaka 2.0: I-DeepSeek kanye Nokuhlanganiswa Kwe-Carv ID Ukuze Kuthathwe Izinqumo Okuthuthukisiwe

I-SANTA CLARA, California, February 14th, 2025/Chainwire/---CARV i-AI-chain ecosystem ehamba phambili yokuzimela kwedatha, imemezele ukuthuthukiswa kwesisekelo sayo. IDATHA (Ukuqinisekiswa Kwedatha, Ukuthenjwa, Nobufakazi) Uhlaka , okumaka ushintsho olubalulekile endleleni ama-agent e-AI asebenzisana ngayo nedatha ye-on-chain kanye ne-off-chain.

NgeSigaba sesi-2, uhlaka lweDATHA ye-CARV luba uhlaka lokuqala lwe-ejenti ye-AI oluhlanganisa ngaphandle komthungo idatha eku-chain eqinisekisiwe, ukucabanga kwengqondo kwe-AI, nokuzazi kwezomnotho ngobuhlakani obuqhutshwa amathokheni, ukuthuthukisa imvelo kanye nezenzo zokwenza imali—ukuguqula i-AI isuke kubasizi abangenzi lutho ibe ukuzimela, ukwenza izinqumo.

Lesi sibuyekezo sethula amamodeli okucabanga athuthukile e-DeepSeek, I-ID ye-CARV ( I-ERC-7231 standard), kanye nobuhlakani bokuziphatha obushayelwa amathokheni, okuvumela ama-ejenti e-AI ukuthi acubungule idatha eqinisekisekayo, enze imisebenzi yezezimali, futhi asebenzisane ngokuguquguqukayo namasistimu ezinto eziphilayo ahlukaniselwe indawo.

"I-AI sekuyisikhathi eside isebenza kuma-silo, inqanyuliwe ku-ecosystem yezomnotho nedatha," kusho u-Yukai Tu, i-CTO ye-CARV. “Nge-DATA Framework 2.0, ama-agent e-AI awaselona nje amathuluzi asebenzayo; bangabahlanganyeli abakhuthele, abahlakaniphile ezweni elihlukaniselwe izifundazwe—abakwazi ukucabanga, ukuqinisekisa, nokwenza izinto ngokuzimele ngokuzazi kwezomnotho ngobuhlakani obuqhutshwa uphawu.”

I-Dawn of AI-Powered Web3 Economies

Amasistimu endabuko e-AI athembele emithonjeni yedatha evaliwe, engaqinisekisiwe, ebeka umkhawulo ekhono lawo lokusebenzelana ngokuzuzisayo nomnotho we-blockchain. I-DATA Framework 2.0 ishintsha le paradigm ngokuhlomisa abenzeli be-AI ngalezi:

• I-Economic Intelligence: Abenzeli be-AI bangaba ngabanikazi bezikhwama zemali, badale izimpahla zedijithali, futhi benze imisebenzi esekelwe kumamethrikhi okuthenjwa kanye nezinzuzo ezinamathokheni.
• I-Multi-Chain & Off-Chain Awareness: Ngokusebenzisa ukuhlanganiswa okujulile kwe-CARV ye-Web3, ama-agent e-AI manje angakwazi ukulanda, aqinisekise, futhi enze ngokuvumelana nedatha ye-blockchain yesikhathi sangempela.
• Amamodeli Wokuthemba Aqhutshwa Amathokheni: Ama-ejenti alungisa amaphethini okusebenzelana asekelwe ekubambeni okuqinisekisiwe neminikelo ye-ecosystem, okwenza izinkundla ezishayelwa yi-AI zivikeleke kakhulu futhi zithembeke.
• Ukubonisana kwe-AI Eqinisekisayo: Ngesakhiwo sokuqonda se-DeepSeek, amanxusa e-AI manje angakwazi ukuhlaziya idatha, enze iziphetho eziqinisekisayo, futhi acwenge amasu ngamandla.

Nge-Chain-of-Thiught Processing, amamodeli e-AI akhiqiza ukucabanga okuningiliziwe kwesinyathelo nesinyathelo ngaphambi kokwenza izenzo, ukuqinisekisa ukwaziswa okwengeziwe namasu okuthatha izinqumo.

Ukuqinisekiswa kwezigaba eziningi kuvumela ama-agent ukuthi azihlole eziphethweni zawo, athuthukise ukunemba nokuthembeka ezimeni eziyinkimbinkimbi. Ngaleso sikhathi, i-Reinforcement Learning inika amandla i-AI ukuthi iguquke ngokuguquguqukayo ngokusekelwe ekusebenzisaneni kwesikhathi sangempela se-blockchain, amasu okuthuthukisa nokwenza izinqumo ngokuhamba kwesikhathi.

Lokhu kuhlanganiswa kwezinqubo ezithuthukisiwe zokuqonda kunikeza amandla ama-agent e-AI ukuthi asebenze ngokuzimela okukhulu, ubuhlakani, kanye nokuphepha ngaphakathi kwezinhlelo zemvelo ezihlukaniselwe izwe.

Ngaphezu kwalokho, ngokucabanga okuhlakaniphile kwe-DeepSeek okushunyekwe ohlakeni lwe-DATA, ama-agent e-AI manje angakwazi ukuhweba, ahlukaniselane imali, futhi enze izinqumo zokubusa ngobuhlakani nokuphepha okungakaze kubonwe.

"Ukuhlanganiswa kwe-DeepSeek ku-CARV's DATA Framework kuphawula inguquko ekuthuthukisweni kwe-AI," kusho u-Yukai Tu, i-CTO ye-CARV. "Sisusa ama-agent e-AI kusukela kumathuluzi angenzi lutho siye ezinkampanini ezizishintshayo, eziqaphela umnotho ezisebenzisana ngokuzimele nakho kokubili idatha nezimpahla zedijithali. Ngokuhlanganisa ukucabanga, ukwethembana, nobuhlakani obuhlukaniselwe izwe, sibeka izinga elisha lendima ye-AI ku-Web3 ecosystem."

Ukuze kuthuthukiswe ukwethenjwa nokwenza kube ngokwakho, i-CARV ihlanganise i-CARV ID kuhlaka lweDATHA. I-CARV ID iyisendlalelo sokuhlanganisa umazisi we-cross-chain esenza ama-agent e-AI akwazi:

• Xhumanisa umsebenzi we-blockchain nokuba khona komphakathi (isb., Twitter, Telegram, Discord)
• Yenza imali ngokusebenzisana, uthuthukise umnotho wamathokheni, futhi ugqugquzele ukukhula okuzinzile
• Finyelela imininingwane ephelele, yamaketanga amaningi ngokusebenzisana komuntu siqu kwe-AI

Ngokuhlanganisa ubunikazi be-on-chain nesithunzi se-Web2, ama-ejenti e-AI angakwazi ukulungisa izimpendulo zawo, akhe amamodeli okuzibandakanya asekelwe ekuthembekeni, futhi alungise ukusebenzelana okusekelwe kuziqinisekiso zomhlaba wangempela. Funda kabanzi futhi wakhe manje nge I-CARV's DATA Framework .

Mayelana ne-CARV

I-CARV yakha i-AI chain ecosystem ukuze inike amandla ubukhosi bedatha esikalini. Ngokunika amandla abenzeli be-AI ngezingqalasizinda ezivikelekile, ezihlanganisiwe, i-CARV inika amandla ukusebenza okukhaliphile, okuhlanganyelwe nge-SVM Chain yayo, enikeza ukuvumelana okungathembeki, ubufakazi be-cryptographic, kanye nokubulawa okuqinisekiswayo.

Ngohlaka LweDATHA, i-CARV inothisa i-AI ngedatha yekhwalithi ephezulu, etholakalayo kanye ne-off-chain, evumela ama-ejenti ukuthi afunde, aguquke, futhi ahlanganyele ngokuguqukayo. Ngabasebenzisi abangaphezu kwe-15M kanye nama-ID e-CARV angu-8M, i-CARV iqinisekisa ubumfihlo nokulawulwa kwedatha kuyilapho ihlinzeka ama-agent e-AI ngemininingwane enamandla, ehlukahlukene, idala i-ecosystem evikelekile, emisha yakho kokubili i-AI nokusebenzisana kwabantu.

Isekelwe ngu-$50M ekuxhaseni ngemali evela kubatshalizimali bezinga eliphezulu njenge-Tribe Capital, HashKey Capital, kanye ne-Animoca Brands, futhi isekelwa ithimba lomakadebona abavela ku-Coinbase, Google, no-Binance, i-CARV izibophezele ekukhuthazeni ikusasa elihlukaniselwe indawo lapho idatha iyigugu, eliphethwe umsebenzisi.

Oxhumana naye

I-COO

UVictor Yu

I-CARV

[email protected]