AI na nzaghachi ọdachi
AI na-enyere aka ịkọ, chọpụta, na ịzaghachi idei mmiri, ọkụ ọhịa, ala ọma jijiji, na oké ifufe - na-atụgharị idei mmiri nke satịlaịtị, ihe mmetụta, na data mgbasa ozi mgbasa ozi n'ime mkpebi ngwa ngwa.
Nchịkọta
When minutes save lives, speed and accuracy matter enormously.
Ime miri emi
Nzaghachi ọdachi na-agafe usoro - amụma, ịdọ aka ná ntị mbụ, nzaghachi, na mgbake - na AI na-emetụ onye ọ bụla aka ugbu a. Tupu mmemme, ụdị mmụta igwe na-ebu amụma ihe egwu: Google's Hub Hub na-ebu amụma ụbọchị idei mmiri na-abịa n'ihu na mba 80, na ụdị ihu igwe dị ka GraphCast na FourCastNet na-eji amụma amụma n'ime nkeji kama awa. N'oge ihe omume, ọhụụ kọmputa na-atụnyere n'ihu na mgbe ihe oyiyi satịlaịtị (dịka, Maxar na xView2 datasets) ka ọ bụrụ ihe mebiri emebi ụlọ, ebe NLP na-enyocha mgbasa ozi ọha na eze maka mkpu enyemaka ma na-eduga ha na ndị na-azaghachi. Netwọk nchọpụta ọkụ dị ka ALERTWildfire na sistemụ satịlaịtị na-agbanye ọkọlọtọ n'oge. Na mgbake, AI na-eme atụmatụ mmebi ego ma na-ebute ụzọ enyemaka. Ihe ịma aka: Ọdachi dị ụkọ na ọgba aghara, yabụ ụdị a zụrụ azụ na ihe omume gara aga nwere ike na-atụfu ndị ọhụrụ, na njikọta na-adakarị mgbe achọrọ sistemu kachasị.
Nghọta nka nka
Maapụ mmebi na-eji nchọpụta mgbanwe: ihe atụ na-atụnyere satịlaịtị tupu na emesịa ma ọ bụ pikselụ onyonyo drone site na pikselụ, na-ekewa ụlọ dị ka emebighị emebi, mebiri emebi, ma ọ bụ bibie. Ụdị ihu igwe ọgbara ọhụrụ dị ka GraphCast na-eji netwọọdụ akwara ndị a zụrụ azụ n'ime ọtụtụ iri afọ nke data nyochagharị, na-ebu amụma ihu igwe zuru ụwa ọnụ n'okpuru otu nkeji n'otu igwe - iwu nke ịdị ukwuu karịa ịme anwansị physics ọdịnala, na-adakọ ma ọ bụ na-akụ izi ezi ha n'ọtụtụ metrik.
Mmetụta atụmatụ
Gburugburu na iwu
Ọnọdụ ụlọ ọrụ na-ekpebi ma echiche AI na-adị ndụ na kọntaktị na eziokwu.
Quality akara
Mmachi ngalaba na-emetụta ọnụego njehie anabatara yana ụdị nlekọta.
Mee nhọrọ
Mbugharị ndị na-aga nke ọma na-ejikọta ikike teknụzụ yana usoro ọrụ n'ihu.
Ọdịnihu nke AI na nzaghachi ọdachi
Na-atụ anya ka AI jikọtara ya na igwe kpakpando satịlaịtị na netwọkụ IoT sensọ maka maapụ ihe egwu dị nso, ụdị ngwaọrụ na-arụ ọrụ mgbe netwọkụ dara, yana ejima dijitalụ nke obodo na-eme ka idei mmiri ma ọ bụ ọkụ tupu ha emee. Ụdị ntọala maka nleba anya ụwa (dị ka Prithvi si NASA na IBM) bu n'obi ikpokọta ihe egwu niile. Ókè a kwesịrị ntụkwasị obi, ịdọ aka ná ntị a ga-akọwa nke ndị isi na ndị obodo ga-eme ihe n'ezie - gbakwunyere iru mpaghara adịghị ike, nke nwere njikọ dị ala nke kacha chọọ ha.
Mmejuputa n'ezie n'ụwa
Google Ebe Iju Mmiri na-ebu amụma ụbọchị idei mmiri ga-eme n'osimiri gafee ihe karịrị mba 80 iji kpalite ịdọ aka ná ntị mbụ.
Ihe ịma aka xView2 na ụdị ụgbọ oloko ihe onyonyo Maxar iji mapụta mmebi ụlọ sitere na foto satịlaịtị mgbe ala ọma jijiji na ajọ ifufe gachara.
GraphCast na FourCastNet na-ewepụta amụma ihu igwe zuru ụwa ọnụ n'ime nkeji, na-eme ka oké ifufe na ịdọ aka ná ntị okpomọkụ.
Sistemụ NLP na-enyocha mgbasa ozi ọha na eze n'oge ọdachi iji chọpụta na geolocate ndị chọrọ nnapụta na ụzọ na-akọ ndị na-azaghachi
Ihe ize ndụ & okporo ụzọ nche
Ihe ndị achọrọ n'usoro iwu nwere ike imebi ụdịdị siri ike ma ọ bụghị ya.
Ihe ndekọ akụkọ ihe mere eme nwere ike itinye nhụsianya na-emerụ obodo ụfọdụ.
Usoro ihe nketa nwere ike ịmepụta mkpọkọ ọnụ na ọnụ ahịa zoro ezo.
Map mmejuputa
Kpọnye ndị ọkachamara na ngalaba site na nhazi nsogbu ruo na nyocha.
Chepụta ụzọ nyocha na akwụkwọ tupu mmalite.
Kwado nnabata na ọrụ nchekwa n'oge.
Tụgharịa n'usoro na njirisi nkwụsị na ntụgharịgharị doro anya.
Nọgide na-eme nchọpụta
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Ntuziaka na-esote
AI na njikwa mmiri ara ehi
Ajụjụ a na-ajụkarị
What is AI in Disaster Response?
AI na-enyere aka ịkọ, chọpụta, na ịzaghachi idei mmiri, ọkụ ọhịa, ala ọma jijiji, na oké ifufe - na-atụgharị idei mmiri nke satịlaịtị, ihe mmetụta, na data mgbasa ozi mgbasa ozi n'ime mkpebi ngwa ngwa. Mgbe nkeji na-azọpụta ndụ, ọsọ na izi ezi dị oke mkpa.
Kedu ihe ebe nchekwa Iju mmiri Google na-eme?
Ebe nchekwa ide mmiri na-eji igwe mmụta na-ebu amụma ụbọchị idei mmiri nke osimiri n'ihu gafee mba 80, na-eme ka ịdọ aka ná ntị mbụ pụta.
Kedu ka sistemụ AI na-esi akọwapụta mmebi ụlọ mgbe ọdachi gasịrị?
Ụdị nchọta mgbanwe atụnyere ihe onyonyo satịlaịtị ma ọ bụ ihe nlere tupu ihe emee tupu oge eruo iji wepụta ụlọ dị ka ndị emebighị emebi, mebiri emebi, ma ọ bụ bibiri.
Kedu ihe mere GraphCast ama ama ma e jiri ya tụnyere ụdị ihu igwe ọdịnala?
GraphCast na-eji netwọk akwara eserese a zụrụ azụ n'ime ọtụtụ iri afọ nke data iji buru amụma ihu igwe zuru ụwa ọnụ n'ihe na-erughị nkeji nkeji, ngwa ngwa karịa ịme anwansị physics ka ọ dabara nke ọma na ọtụtụ metrik.
Gịnị mere ụdị nzaghachi ọdachi nwere ike iji na-alụso ihe ọhụrụ ọgụ?
Ọdachi dị ụkọ na ọgba aghara, yabụ ụdị a zụrụ n'ụdị akụkọ ihe mere eme nwere ike tufuo ọnọdụ ndị na-adịghị ka ihe omume gara aga.
Kedu ọrụ NLP na-arụ n'oge ọdachi?
Nhazi asụsụ eke na-enyocha ozi mgbasa ozi ọha na eze ka ịchọta na geolocate oku maka enyemaka, na-ebuga ha na ndị na-aza ihe mberede ngwa ngwa.