Ezinye izindlela zasendaweni esikhundleni se-NotebookLM: izinketho zangempela nokuthi ungakhetha kanjani

Uma uke wazama i-NotebookLM kodwa ukhathazekile ngobumfihlo, imikhawulo yamafayela, noma ukuthembela ngokuphelele efwini , awuwedwa. Abasebenzisi abaningi ngokwengeziwe bafuna uhlobo olufanayo lolwazi: ukulayisha amadokhumenti abo, ukubuza imibuzo esebenzisa i-AI, ukukhiqiza izifinyezo, amakhadi e-flash, kanye nezinto zokufunda... kodwa ngaphandle kokunikeza idatha yabo noma ukuncika kumhlinzeki oyedwa.

Izindaba ezinhle ukuthi sekukhona ezinye izindlela eziningana zasendaweni noma ezizisingathayo esikhundleni se-NotebookLM kanye, ngaphezu kwalokho, uhlelo olukhulu lokubhala amanothi kanye nezinhlelo zokusebenza zokuphatha ulwazi (ezine-AI noma ezingenayo) ezingamboza izidingo ezihlukene kakhulu: kusukela ocwaningweni oluqinile lwezemfundo, ekuphathweni kwamaphrojekthi eqembu, kuya emisebenzini ephelele yemfundo noma ekuhlaziyweni kwamaqoqo amakhulu emibhalo.

Yini enikezwa yi-NotebookLM futhi kungani abaningi befuna ezinye izindlela zendawo?

I-NotebookLM isibe uhlobo lokulinganisa lokukhiqiza okusebenzisa i-AI : ikuvumela ukuthi ulayishe amadokhumenti, uxhumanise imithombo, ubuze imibuzo yemodeli, futhi uthole izifinyezo, izinhlaka, iziqondiso zokufunda, ngisho nemibiko ebanzi esekelwe ezintweni zakho. Ilungele ukusebenza ngamanothi, amaphepha, izikripthi, noma amadokhumenti ochwepheshe ngaphandle kokukopisha nokunamathisela konke engxoxweni evamile.

Inkinga iphakama lapho ubumfihlo kanye nokulawulwa kwedatha kusetshenziswa . Nakuba umsebenzisi enquma ukuthi yimaphi amafayela okufanele awalayishe, ukucubungula kwenziwa ngokuphelele efwini le-Google. Ngokuqukethwe okubucayi (amadokhumenti enkampani yangaphakathi, imibiko yezokwelapha, izinkontileka, idatha ye-R&D, njll.), lokhu kuvame ukuba "cha" yenkampani eminyangweni yezomthetho noma yezokuphepha kwe-inthanethi.

Omunye umkhawulo obalulekile usayizi wefayela kanye nesilinganiso sevolumu yedatha : I-NotebookLM isebenza kahle kakhulu ngamasethi aphakathi amadokhumenti, kodwa uma ufuna ukuhlaziya amakhulu ezikripthi, umtapo wolwazi wonke wama-PDF, noma amaqoqo amakhulu amanothi, uzobhekana nemikhawulo ngokushesha. Kumaphrojekthi amakhulu okuhlaziya, lokhu kuyasilela.

Okokugcina, ukuhlanganiswa kwayo namamodeli endawo kusalinganiselwe kakhulu . Nakuba izinjini zangaphandle zingaxhunywa kwezinye izimo, ifilosofi eyinhloko ihlala ifana nefu kuqala. Kulabo abafuna ubukhosi bedijithali kanye nokucutshungulwa okungu-100% endaweni, lokhu akuhambisani kahle; izixazululo ezenzelwe ukusebenza namamodeli endawo zikhanga kakhulu.

Izindlela zokwenza izinto zasendaweni eziyi-100% esikhundleni se-NotebookLM: I-Open Notebook, i-Gloss, i-PageLM kanye namanye amaphrojekthi

Ezinyangeni zamuva nje, kuye kwavela izixazululo eziningana eziphinda umqondo oyisisekelo we-NotebookLM (layisha amadokhumenti, uwabuze nge-AI, ukhiqize izinto ezisuselwe kokunye) kodwa ngomehluko omkhulu: zingafakwa emshinini wakho noma engqalasizinda yenhlangano yakho, kusetshenziswa amamodeli endawo afana ne-Ollama noma amaseva e-LLM azisingatha wona.

I-Open Notebook ingenye yamaphrojekthi adonsele ukunaka okukhulu kulokhu. Iyipulatifomu yomthombo ovulekile eyenzelwe ngqo njenge-"local NotebookLM": ivumela abasebenzisi ukudala ama-notebook, ukulayisha ama-PDF, imibhalo, noma amadokhumenti azo zonke izinhlobo, bese bexoxa ne-AI ephendula kuphela ngokusekelwe kulokho okuqukethwe.

Inzuzo enkulu ye-Open Notebook ukuthi ungayilungiselela ukuthi isebenze kuphela namamodeli endawo , ngakho-ke amadokhumenti awalokothi aphume kunethiwekhi yakho. Lokhu kukhanga kakhulu abacwaningi, othisha, izikhungo zemfundo, noma izinkampani ezidinga ubumfihlo obuphelele futhi ezingafuni ukuthi noma yibaphi abathengisi bangaphandle babone idatha yabo. Ngaphezu kwalokho, ukuqonda okuyisisekelo ngemiqondo yokuxhumana kuyasiza uma uhlela ukugcina konke kunethiwekhi yakho.

Ukufaka i-Open Notebook kudinga ulwazi lweziqukathi ze-Linux ne-Docker , kodwa ukugeleza okuphelele kuqondile impela: ufaka i-Docker, ukopishe indawo yokugcina evela ku-GitHub, ulungise amafayela okucushwa (njenge-docker-compose.yml kanye ne-docker.env) ukuze unqume ukuthi yimaphi amamodeli ozowasebenzisa (ingxoxo, ukushumeka, izwi, njll.), qala iziqukathi, bese uzifinyelela kusuka kusiphequluli sakho kunethiwekhi yakho yendawo.

Uma usuqalile ukusebenza, ungadala abasebenzisi bendawo, uphathe izintandokazi zemodeli ngomsebenzi, bese uqala ukulayisha amadokhumenti . Ukusuka lapho, uhlelo lukuvumela ukuthi ubuze, ufingqe, uguqule, futhi uhlobanise imibhalo ngaphakathi kwendawo elawulwa ngokuphelele, ngaphandle kokuthembela ku-akhawunti yangaphandle noma kumaseva enkampani yangaphandle.

Enye iphrojekthi ethokozisayo yi-Gloss , uhlelo lokusebenza oluphinda umqondo we-"NotebookLM" yedeskithophu, kodwa olubhalwe kusukela phansi ku-Rust futhi oluklanyelwe ukusebenza ngendlela yemvelo, ngokushesha futhi ngaphandle kokumisa isikhombimsebenzisi ngisho nalapho kucutshungulwa inani elikhulu lamadokhumenti ngesikhathi esifanayo.

I-Gloss inesakhiwo esiyingqayizivele esakhiwe ngokucophelela : ungahudula bese uphonsa ifolda equkethe amadokhumenti amaningi obuchwepheshe (isibonelo, amafayela angu-70 noma angu-80), bese uhlelo lokusebenza luqala imicu ngemuva ukuze luyihlaziye, lukhiqize ukushumeka, futhi luyibeke kugrafu ye-HNSW, konke lokhu kuyilapho isikhombimsebenzisi sisaphendula. Kunoma ubani ofuna ithuluzi lendawo elinamandla futhi, ngaphezu kwalokho, ulwazi lokufunda lwe-Rust lwangempela, indawo yayo yokugcina i-GitHub iyigolide elicwengekile.

Esikhundleni sokuxhuma kusizindalwazi se-vector sangaphandle, i-Gloss ifaka injini yayo yokusesha ehlanganisiwe ngaphakathi kwekhreyithi ye-semantic-memory: ihlanganisa inkomba ye-HNSW yokusesha i-vector ne-BM25 ukuze kufaniswe igama elingukhiye eliqondile. Lokhu kukuvumela ukuthi ubone ukuthi izakhiwo zedatha eziyinkimbinkimbi, i-scalar quantization, kanye ne-ranking algorithms ezenzelwe ukusebenza kwimemori yendawo zisetshenziswa kanjani.

I-backend kaGloss iphinde inikeze ukubuka okuningiliziwe kokudluliselwa komongo kumamodeli endawo . Ungaxhuma uhlelo lokusebenza ku-Ollama noma kwamanye ama-LLM endawo bese ubona ukuthi iwindi lomongo liphathwa kanjani emisebenzini yendawo , ukuthi izingcaphuno ezitholiwe zifakwa kanjani, nokuthi yimaphi amasu asetshenziswayo ukunciphisa ukubona izinto ezingekho. Luhlobo lwelabhorethri esebenza ngezandla yokuqonda ukuthi ungakha kanjani isisombululo se-RAG sedeskithophu esakhiwe kahle.

I-PageLM: ipulatifomu yemfundo ephefumulelwe yi-NotebookLM ene-AI eguquguqukayo

Ngaphakathi kwezwe lemfundo, i-PageLM iveza indawo ehlukile ephefumulelwe yi-NotebookLM , kodwa igxile ekuguquleni izinto zokufunda zibe izinsiza ezisebenzisanayo nokunikeza inkululeko yokukhetha umhlinzeki we-AI (kufaka phakathi amamodeli endawo).

I-PageLM yamukela izinhlobo ezahlukene zokufaka (i-PDF, i-DOCX, i-Markdown, i-TXT) futhi iziguqula zibe izinto zokufunda eziwusizo, hhayi nje izifinyezo ezijwayelekile. Umgomo uwukumboza wonke umjikelezo wokufunda: ukuqonda, ukuzijwayeza, ukubuyekeza, nokuqinisa.

Phakathi kwezici zayo ezihlaba umxhwele kakhulu kukhona izinto eziningana "ezifana nekhampasi" : ingxoxo yomongo namadokhumenti, amanothi ahlakaniphile (ama-SmartNotes ngesitayela sendlela ye-Cornell), amakhadi ememori okuphindaphinda okunezikhala, imibuzo exhumanayo enamacebo nezincazelo, ukukhiqizwa komsindo wohlobo lwe-"podcast yemfundo", kanye nokubhalwa kwamarekhodi ekilasini ukuze kuguqulwe kube izinto eziseshekayo.

Isihluthulelo se-PageLM sisekucushweni kwayo kwabahlinzeki abaningi . Idokhumenti ikhuluma ngokuhambisana namamodeli avela ku-Google Gemini, i-OpenAI GPT, i-Anthropic Claude, i-xAI Grok, kanye, okubaluleke kakhulu, i-Ollama yokusebenza kwendawo, ngaphezu kwamasango afana ne-OpenRouter. Ngokufaka, ingathembela nakubahlinzeki bangaphandle noma bendawo.

Lokhu kuvumela isikhungo ngasinye semfundo ukuthi sikhethe ibhalansi phakathi kokulula kanye nokuzimela : ungasebenzisa umhlinzeki wefu lezentengiselwano uma udinga imodeli yekhwalithi ephezulu, noma, uma izinqubomgomo zokuvikela idatha ziqinile, khetha ukufakwa ne-Ollama kanye nama-LLM endawo, ugcine konke ngaphakathi kwengqalasizinda yakho.

Isibonelo esilula sekilasi kungaba yisifundo somlando wesikole samabanga aphezulu : uthisha ulayisha izihloko ngefomethi ye-PDF, engeza idokhumenti enezinhloso zokufunda, akhiqize amanothi ahlelekile abafundi, adale isethi ephelele yamakhadi okubukeza, kanye nombuzo wokuzihlola onezincazelo. Kulabo abathanda umsindo, isihloko singaguqulwa sibe yi-podcast encane yokubukeza ngenkathi uhamba ngezinyawo noma usezithuthweni zomphakathi.

I-PageLM ayithathi indawo kathisha, kodwa inciphisa imisebenzi ephindaphindwayo (ukudala izivivinyo, ukuhlela kabusha amanothi, ukuhlanganisa amaphepha okusebenzela) futhi iphindaphinde amafomethi okuqukethwe okufanayo, into ewusizo kakhulu emakilasini anezigqi nezitayela zokufunda ezihlukene kakhulu.

Ngokombono wobuchwepheshe, i-PageLM yakhelwe phezu kwe-stack yesimanje (i-Node.js, i-React, i-TypeScript) futhi inikeza ukuthunyelwa nge-Docker/Docker Compose, okwenza kube lula kakhulu ukufakwa kwayo kuma-server farms, ama-VPS, noma ngisho namadivayisi athile e-NAS athuthukile. Ngaphezu kwalokho, idinga i-ffmpeg ukuze isebenze kahle umsindo.

Noma kunjalo, ilayisensi yayo iyilayisensi yomphakathi : ikhodi iyatholakala, kodwa iLayisensi Yomphakathi ye-PageLM ithi ukusetshenziswa komuntu siqu nokwezemfundo kuvunyelwe, kuyilapho amaphrojekthi ezentengiselwano noma okuthengisa kabusha edinga imvume ecacile. Izikole, amanyuvesi, noma izikole ezizimele kufanele zibukeze ngokucophelela leli phuzu ngaphambi kokulihlanganisa nomnikelo okhokhelwayo.

Amapulatifomu okubhala amanothi nolwazi asebenza njengenye indlela esikhundleni se-NotebookLM

Ngaphandle kwama-clones aqondile, kukhona uhlelo lonke lokuthatha amanothi, ucwaningo, kanye namathuluzi okuphatha ulwazi , okuthi uma kuhlanganiswa ne-AI (yasendaweni noma esefwini), kungathatha indawo yalokho okwenziwa yi-NotebookLM noma kudlule ngisho nakwezinye izimo.

Isibonelo, i-Obsidian ingenye yezinkulu ze-local markdown . Igcina amanothi akho kumafayela e-markdown kudiski yakho, yakha igrafu yobudlelwano phakathi kwemibono, futhi ingandiswa ngenani elikhulu lama-plugin, kufaka phakathi amanye aqondiswe ekusesheni kwe-semantic kanye nokuhlanganisa ama-agent e-AI endawo.

Ukukhanga kwayo okuyinhloko ukulawula idatha yakho ngokuphelele : konke kutholakala kufolda yakho yamanothi, ongayivumelanisa ne-Git, uyibhale phansi, noma uyisekele ngendlela othanda ngayo. Ngokubuyisela, inohlelo lokufunda oluqinile, ikakhulukazi uma uhlola ukuzenzekela okuthuthukisiwe, amathempulethi ayinkimbinkimbi, kanye nama-plugin e-AI.

ULogseq wabelana ngefilosofi ka-Obsidian, kodwa egxile kakhulu ohlelweni lwe-Zettelkasten kanye nokuthatha amanothi okuxhumene . Ilungele ucwaningo lwezemfundo noma amaphrojekthi esikhathi eside lapho umgomo uwukwakha inethiwekhi ebanzi yemibono exhumene, kunokuba kube amadokhumenti aqondile ahlukene.

Amandla ayo afaka phakathi ukuhambisana kwe-Git kanye nokuguquguquka kokwenza ngezifiso imisebenzi yokusebenza , yize ngobuhle ingase ingabi ngcono njengezinye izinketho zezentengiselwano. Kulabo abazisa isakhiwo solwazi ngaphezu kwesibonisi, ingumncintisani onamandla kakhulu.

I-Idea isibe yisisombululo "esisetshenziswayo" samanothi eqembu, ama-database, nama-wiki . Ikuvumela ukuthi wakhe konke kusukela ohlwini olulula kuya ezinhlelweni zokuphatha amaphrojekthi eziyinkimbinkimbi, ama-CRM angaphakathi, noma izikhala zemibhalo yenkampani, ngamathempulethi asevele enziwe cishe nganoma yisiphi isimo sokusetshenziswa.

Ukuhamba kwayo kusobala ukuthi kuqala ngamafu, ngokubambisana ngesikhathi sangempela, amazwana, kanye nezindawo ezabiwe . Ihlanganisa imojuli ye-AI ekwazi ukufingqa, ukubhala kabusha, ukukhiqiza okuqukethwe, kanye nokukusiza ukuthi usebenze ngamadokhumenti akho, yize ingakafiki ezingeni lokusesha okujulile kwe-semantic noma i-RAG ethuthukisiwe enikezwa izixazululo ezikhethekile kakhulu.

I-Mem ne-Mem.ai zimelela igagasi elisha lezinhlelo zokusebenza zokuthatha amanothi ezisebenzisa i-AI . Isithembiso sabo sicacile: ubhala ngokukhululeka, futhi ithuluzi linakekela ukuhlela, ukumaka, kanye nokusikisela ulwazi olufanele uma uludinga, ngenxa yama-algorithms okuthola amaphethini kanye nezikhumbuzi zomongo.

Lawa mapulatifomu avelele ngokusesha kwawo okubikezelayo, izifinyezo ezizenzakalelayo, kanye nezikhumbuzo ezihlakaniphile , kodwa avame ukuthembela kakhulu kumamodeli efu kanye nebhizinisi elivaliwe. Ukuze uthole umlingo ozenzakalelayo omningi, udela ukucaca kanye nokulawula okwenzekayo kudatha yakho.

Ngakolunye uhlangothi, i-Zotero ingumphathi wereferensi ojwayelekile wocwaningo lwezemfundo . Akuyona "i-NotebookLM" evamile, kodwa ibalulekile uma usebenza ngamaphepha, izincwadi, kanye nezingcaphuno zezincwadi. Ikuvumela ukuthi uhlele imithombo, ukhiqize izingcaphuno kuma-word processors, futhi uthumele kwabanye abaphathi bezithenjwa.

Ubuthakathaka bayo, uma buqhathaniswa namathuluzi afana nezizindalwazi zegrafu, ukuthi ayihloselwe kakhulu amanothi axhumene . Yingakho abantu abaningi begcina behlanganisa i-Zotero ne-Obsidian, i-Logseq, noma ezinye izinhlelo zokusebenza zokubhala amanothi ukuze bathole okungcono kakhulu kuzo zombili lezi zindawo: uhlu lwezincwadi oluhlelwe kahle kanye nohlelo olucebile lokuxhumana phakathi kwemibono.

I-Roam Research yayingenye yamapulatifomu okuqala amakhulu okwandisa umqondo "wokucabanga kwenethiwekhi ." Esikhundleni sezindlela zakudala zesitayela samafolda, isebenzisa amanothi axhumene nezixhumanisi ezizenzakalelayo, okukhuthaza ukuhlola izihloko namaphrojekthi okungekho emgqeni.

Izinzuzo zayo zifaka phakathi uhlelo lokuxhumanisa olunamandla kakhulu, amathempulethi okubhala amajenali nokwenza izinqumo , kodwa inemodeli yokubhalisela kanye nesixhumi esibonakalayo esidinga ukujwayelana. Kulabo abajabulela ukucabanga ngamagrafu hhayi ohlwini, kungaba umlutha omkhulu.

Ezinye izindlela eziyishumi ezivamile zihlanganisa izidingo ezahlukene ezihlobene nokubhala amanothi . I-ClickUp, isibonelo, ivelele lapho, ngaphezu kwe-"AI notebook," udinga isikhungo esiphelele semiyalo yemisebenzi, amaphrojekthi, kanye nokubambisana kweqembu.

I-ClickUp ihlanganisa amadokhumenti, incwajana, umsizi we-AI othuthukisiwe (i-ClickUp Brain), kanye nezici zokuphathwa kwephrojekthi eziqinile . Ingabhala futhi ifingqe imihlangano, iguqule iziphetho zibe imisebenzi, ixhumane ne-Google Drayivu, i-Dropbox, i-SharePoint, i-GitHub, nokunye okuningi. Kuhle uma kugxilwe emsebenzini wokubambisana kunokugcina konke kusendaweni.

Phakathi kwezinketho ezigxile kakhulu ekuhleleni komuntu siqu kanye nomsebenzi ohlelekile, i-Notion kanye ne-Evernote zisalokhu ziyizilinganiso . I-Notion ngenxa yokuguquguquka kwayo kanye nomphakathi wamathempulethi, kanye ne-Evernote ngenxa yomlando wayo omude, ukuvumelanisa amadivayisi ahlukene, kanye nekhono lokugcina cishe noma yini (umbhalo, izithombe, izithombe-skrini, njll.).

Ucwaningo lwe-Obsidian kanye ne-Roam, futhi, lukhanya emkhakheni wemibono exhunyiwe : i-Obsidian ngokuthembela kumafayela endawo e-Markdown kanye negrafu ebonakalayo kakhulu, kanye ne-Roam ngendlela yayo yansuku zonke kanye nezixhumanisi ezingemuva ezizenzakalelayo. I-Tana ithatha lo mqondo iqhubekele phambili nakakhulu, ivumela izakhiwo zedatha ezithuthukisiwe ezisekelwe kuma-node namabhulokhi, cishe njengokuba nedathabheyisi ye-semantic yamanothi akho.

I-Afforai ne-Mem.ai ziwela esigabeni "esigxile kakhulu kwi-AI", zibeka phambili ikhono lesistimu lokukusiza ufunde, ufinyeze, futhi uhlele imibhalo eminingi . Ziwusizo ikakhulukazi uma ufuna ukuthola okuningi kuma-ebook akho amadala, ama-PDF, namanothi ngokukhiqiza izifinyezo, ukuqonda, kanye nezinto zocwaningo.

I-RemNote ithole ukuthandwa okukhulu phakathi kwabafundi ngenxa yokuhlanganiswa kwayo kokubhala amanothi nokuphindaphinda okunezikhala . Ayigcini nje ngokugcina ulwazi; iluguqula lube amakhadi okubuka kanye nemikhuba yokubuyekeza ukuqinisekisa ukuthi amaphuzu abalulekile awakhohliwe. Lokhu kuwusizo kakhulu ezivivinyweni, ezinhlelweni zeziqu ezidingayo, noma emfundweni eqhubekayo.

Okokugcina, iMicrosoft OneNote iyindlela ehlukile yemvelo esikhundleni se-NotebookLM ngaphakathi kwe-ecosystem ye-Office 365. Ivumela ukuthatha amanothi ngokukhululeka, ukuxuba umbhalo, imidwebo, umsindo, nezithombe ku-canvas eguquguqukayo, futhi ihlangana ne-Word, Excel, ne-Outlook. Kuyisisekelo esihle kakhulu sokuhlanganisa nezinsizakalo ze-AI (njenge-Copilot) ukwakha imisebenzi enamandla ngaphandle kokushiya imvelo ye-Microsoft.

Indlela yokuhlanganisa lezi zindlela zasendaweni ezinkampanini nasezinhlanganweni

Ezindaweni zezinkampani, isinqumo akusikho nje ukuthi yiliphi ithuluzi okufanele lisetshenziswe, kodwa ukuthi lizohlanganiswa kanjani nokwakhiwa kwe-IT . Yilapho izinsizakalo zamafu (i-AWS, i-Azure), amapayipi edatha, i-BI, kanye nokuphepha kwe-cyber okungathi sína kanye nezidingo zokuthobela imithetho zisebenza khona.

Isu elivamile ukuhlanganisa amanothi noma ikhambi lokuphathwa kolwazi nezinsizakalo zamafu ezingandiswa : isibonelo, i-Obsidian noma i-Logseq njengesixhumi esisebenzayo samaqembu olwazi, kanye nengqalasizinda ku-AWS noma i-Azure egcina , ibethele futhi ikopishe idatha ngokuya ngezinqubomgomo zenhlangano.

Ngokusekelwe kulesi sisekelo, ama-ejenti e-AI kanye namapayipi obuhlakani bokwenziwa angakhiwa axhumene nezinhlelo ze-BI njenge-Power BI. Ngale ndlela, idatha efanayo ephakela "i-smart notebook" ingasetshenziswa futhi ukukhiqiza amadeshibhodi, izexwayiso, kanye nokuhlaziywa kwesikhathi sangempela kokuphathwa nokusebenza.

Kulezi zinhlobo zamaphrojekthi, kubalulekile ukusebenzisa imikhuba emihle kakhulu yokuphepha kwe-inthanethi : ukuhlukaniswa kwenethiwekhi, ukulawulwa kokufinyelela okusekelwe ezindimeni, ukubethela ngesikhathi sokuthutha kanye nokuphumula, ukuhlolwa kokuthi ubani ofinyelela kumaphi amadokhumenti, kanye nezinqubomgomo ezicacile zokugcina. I-AI ayikho ngaphezu kwale mithetho; kufanele izivumelanise nayo.

Izinkampani eziningi ziphendukela kubalingani abangochwepheshe besofthiwe eyenziwe ngokwezifiso, i-AI, kanye nokuphepha kwe-cyber kulezi zinhlobo zokuhlanganiswa . Amaqembu afana ne-Q2BSTUDIO, isibonelo, asiza ukuklama izixazululo ezihlanganisa amathuluzi olwazi namapulatifomu ebhizinisi, asetshenziswa ku-AWS noma ku-Azure futhi axhunywe nezinsizakalo zobuhlakani bebhizinisi kanye ne-Power BI.

Laba bahlinzeki bavame ukuthuthukisa ama-ejenti e-AI aqondene nesimo ngasinye sokusetshenziswa (ukusekelwa kwangaphakathi, ukuhlaziywa kwamadokhumenti, izifinyezo zezehlakalo, njll.), ukwenza ngokuzenzakalelayo ukuhamba komsebenzi, futhi bachaze isu lokuphepha ezindaweni ezihlanganisiwe nezinamafu amaningi, lapho izinhlelo ezisendaweni kanye nezinsizakalo zangaphandle zihlala khona ndawonye.

Ngaphambi kokukhetha enye indlela esikhundleni se-NotebookLM ezingeni lenhlangano, kufanelekile ukucabangela okubaluleke kakhulu : uma ukulawula okuphelele kolwazi kubaluleke kakhulu, khona-ke izixazululo ezihambisana nesofthiwe eyenziwe ngokwezifiso kanye nokusetshenziswa kwendawo zingase zikhange kakhulu; uma isivinini sokwamukelwa kanye nokubambisana komhlaba wonke kuyizinto eziza kuqala, amapulatifomu afana ne-Notion noma i-ClickUp nokuhlanganiswa kwe-AI angase akhange kakhulu.

Ezikhungweni zemfundo kanye namaqembu ocwaningo, inhlanganisela evamile yi-Zotero + ithuluzi lamanothi axhunyiwe (i-Obsidian, i-Logseq, i-Roam, i-Tana) kanye, ngaphezu kwalokho, iphrojekthi ethile ye-Open Notebook noma i-PageLM yokwengeza ungqimba lwe-AI kumadokhumenti ngaphandle kokulahlekelwa ukulawula uhlu lwezincwadi noma inethiwekhi yemibono.

Isimo sezindlela zasendaweni nezizimele esikhundleni se-NotebookLM ngo-2025 siqine kakhulu kunangeminyaka embalwa edlule : kusukela kumaphrojekthi afana ne-Open Notebook, i-Gloss, noma i-PageLM aphinda umqondo wokuqala ngokuseduze, kuya ezimisweni zemvelo zamanothi, ucwaningo, kanye nokuphathwa kolwazi, okuhlanganiswe nama-LLM endawo noma asekelwe efwini, anikeza izixazululo eziguquguqukayo kakhulu ezenzelwe iphrofayili yomsebenzisi ngamunye; isihluthulelo sisekulinganiseni ubumfihlo, amandla e-AI, ukulula kokusetshenziswa, kanye nokuhlanganiswa namanye amathuluzi, ukwakha indawo yokusebenza lapho amadokhumenti akho, amanothi, kanye nedatha kukusebenzela ngempela, hhayi okuphambene nalokho.