Ukusa kwenkathi yomshini nomshini nemithelela yawo kumshwalense

Ubuchwepheshe bomshini ukuya emshinini (M2M) empeleni bubandakanya izinzwa endaweni ye-inthanethi Yezinto (IoT) lapho zithumela khona idatha ngokungenantambo kuseva noma kwenye inzwa. Enye inzwa noma iseva isebenzisa i-Artificial Intelligence (AI) ukuze ihlaziye idatha futhi isebenze kudatha ngokuzenzakalelayo ngesikhathi sangempela. Izenzo zingaba yinoma yini efana nezixwayiso, isexwayiso, noshintsho endleleni, amabhuleki, isivinini, ukujika, ngisho nemisebenzi. Njengoba i-M2M ikhula ngokuphawulekayo, maduzane sizobona ukusungulwa kabusha kwawo wonke amamodeli ebhizinisi nobudlelwano bamakhasimende. Impela, izicelo zizonqunyelwa kuphela umcabango wamabhizinisi.

Lokhu okuthunyelwe kuzohlola okulandelayo:

1. Ukubuka konke kobuchwepheshe be-M2M obubalulekile namandla abo okuphazamisa.
2. Ukuthengiselana kwe-M2M; uguquko olusha lapho imishini ikwazi ukusebenzisana ngokuqondile neminye imishini eholela emnothweni wemishini.
3. Umthelela we-AI yiwo osiholela ku-M2M nakuba; idatha enkulu, ukufunda okujulile, ukusakaza ama-algorithms. Ubuhlakani bomshini ozenzakalelayo nokufundisa ngomshini. Ukufundisa ngomshini mhlawumbe ukuthambekela okukhulu kakhulu komnotho wemishini.
4. Imodeli yebhizinisi lomshwalense yesikhathi esizayo: Ukuqala kwe-Insuretech okusekelwe ku-blockchain.
5. Ukuphetha amazwi

Uhlolojikelele lobuchwepheshe be-M2M obubalulekile

Cabanga ngezimo ezingokoqobo:

1. Imoto yakho izwa uhambo lwakho lohambo futhi ithenga umshwalense lapho udingeka khona ngemayela ngokuzenzakalelayo. Umshini uzithengela owawo umshwalense wesikweletu ngokuzenzakalela.
2. Ama-exoskeleton agqokekayo anikeza umthetho kanye nefekthri isebenza amandla namandla angaphezu kwawomuntu
3. I-Brain-Computer interfaces ihlangana nobuchopho bethu ukuze sakhe ubuhlakani bomuntu (isibonelo, i-Neural Lace ka-Elon Musk)
4. Amaphilisi ahlakaniphile agaywe yithi kanye nezinto ezigqokwayo zezempilo ahlola ngokuqondile ukufa kwethu kanye nezingozi zokugula.
5. Ungathola umshwalense wempilo ngokuthatha isithombe ozishuthe sona. Izithombe ozishuthe zona zihlaziywa nge-algorithm enquma ngokwempilo ubudala bakho bemvelo ngalezi zithombe (sezenziwa kakade isofthiwe ye-Chronos yokuqala i-Lapetus).
6. Amafriji akho ayaqonda imikhuba yakho evamile yokuthenga neyokuthenga futhi athole ukuthi into ethile efana nobisi iyaphela; ngakho, ithenga ubisi ngokuthenga online ngqo. Isiqandisi sakho sizohlala sigcwele kabusha ngokusekelwe emikhubeni yakho evamile. Ngemikhuba emisha nokungajwayelekile, ungaqhubeka nokuthenga izinto zakho ngokuzimela futhi uzibeke esiqandisini njengenjwayelo.
7. Izimoto ezizishayelayo zixhumana zodwa kugridi ehlakaniphile ukugwema izingozi nokushayisana.
8. Irobhothi lakho lizwa ukuthi ucasuka kakhulu futhi udangele kamuva nje ngakho lizama ukukujabulisa. Itshela i-bot yomqeqeshi wakho wezempilo ukuthi akhulise okuqukethwe ukuze uqinise imizwa.
9. Izinzwa zizwa ukuqhuma okuzayo epayipini futhi ngaphambi kokuthi ipayipi liqhume, ithumela umlungisi ekhaya lakho
10. I-chatbot yakho ingumsizi wakho siqu. Iyakuthengela, iyakuzwa lapho udinga ukuthenga umshwalense wokuthi ake sithi uma usohambeni, isingatha imisebenzi yakho yansuku zonke futhi ikugcina unolwazi ngohlelo lwakho lwansuku zonke olwenzile ngokubambisana ne-bot.
11. Unephrinta ye-3D yokwenza izixubho ezintsha. Isixubho samanje esihlakaniphile sizwa ukuthi imicu yaso isizoguga ngakho sithumela isignali kuphrinta ye-3D ukwenza imicu emisha.
12. Esikhundleni soswebezane lwezinyoni, manje sibona izixuku ze-drone zindiza zifeza imisebenzi yazo ngobuhlakani obuhlangene.
13. Umshini udlala i-chess ngokumelene nawo ngaphandle kwanoma iyiphi idatha yokuqeqeshwa futhi ushaya cishe wonke umuntu nayo yonke into (i-AlphaGoZero isivele yenza lokhu).
14. Kunenqwaba yezimo ezingokoqobo ezifana nalezi, ezinqunyelwe kuphela umcabango wethu.

Kukhona ama-meta-themes amabili avela kubuchwepheshe be-M2M: ukuvimbela kanye nokwenza lula. Izimoto ezizishayelayo zingaqeda noma zehlise kakhulu izingozi njengoba iningi lezingozi zezimoto zidalwa amaphutha abantu. Izinto ezigqokwayo zingaholela ekuphileni okunempilo, ukuqhuma kwepayipi lezinzwa zasekhaya ezihlakaniphile nezinye izinkinga ngaphambi kokuba zenzeke futhi zizilungise. Lokhu kuvimbela kunciphisa ukugula, izingozi nezinye izehlakalo ezimbi. Ukunethezeka kuyisici esigxile kakhulu ekutheni yonke into yenzeka ngokuzenzakalelayo isuka komunye umshini iye komunye futhi ezimeni ezimbalwa ezisele, ikhuliswa ngobuchule nokunaka kwabantu. Umshini ufunda lokho ohlelelwe ukuthi uzifunde wona ngokwawo usebenzisa idatha evela kuzinzwa zawo mayelana nokuziphatha kwethu ngokuhamba kwesikhathi. Kwenzeka ngemuva futhi ngokuzenzekelayo ukukhulula isikhathi sethu nemizamo kwezinye izinto zomuntu ezifana nokuba nobuciko.

Lobu buchwepheshe obusafufusa buholela ezinguqukweni zokuchayeka futhi bunomthelela omkhulu kumshwalense. Inani elikhulu lezindawo zokuthintwa zenziwa lapho umshwalense engakwazi ukusebenzisana nekhasimende, kunokugxila okuncane ekuhlinzekeni komuntu siqu futhi okwengeziwe esicini sezentengiselwano (njengokuthi uma imoto ezishayelayo ingasebenzi kahle noma igqekezwa, umsizi wasekhaya uyagqekezwa, esikhundleni salokho kugqekezwe umsizi wamaphilisi ahlakaniphile. yokuhlinzeka ngedatha yesikhathi sangempela ukuze kuhlolwe ngokuguquguqukayo ubungozi bokushona nokugula) nokunye. Imvamisa yezimangalo izokwehla kakhulu, kodwa ukuqina kwezimangalo kungaba nzima kakhulu futhi kube nzima ukubhekwa njengoba abathintekayo abahlukahlukene kuzodingeka bangene ebhodini ukuze bahlole umonakalo futhi babone ukuthi isabelo sokulahlekelwa sihluka kanjani ngokulingana amaphutha ababambiqhaza abehlukene. Ukugebenga kwe-Cyber ​​kuzophindaphindeka okuholela emathubeni amasha kubadayisi bomshwalense emnothweni wemishini.  

Lobu buchwepheshe abubodwa; ubunxiwankulu angeke bube khona ngaphandle kokuguqula njalo ubuchwepheshe kanjalo nobudlelwano bethu nabantu nabo. Uma udinga ukuqwashisa okwengeziwe ngalokhu, bona ukuthi ama-algorithms nobuchwepheshe bubumba kanjani ukucabanga kwethu, izimo zengqondo zokuziphatha kwethu nezenzo futhi ubone ukuthi bonke ubuchwepheshe buvela ngokushesha kangakanani. Okumangazayo ukuthi lokhu kubuka kwenziwa nguKarl Marx, othile owayehlala ku-1818- 1883 futhi lokhu kubonisa ukuthi bonke ubuchwepheshe emhlabeni abuyithathi indawo yokucabanga okujulile nokuhlakanipha kwe-erudite.

Izinguquko zomphakathi zihambisana nezinguquko zobuchwepheshe. Manje sibona amamodeli webhizinisi ontanga agxile emthelela wenhlalo (isibonelo iLemonade) esikhundleni sokwenza abacebile bacebe. Umnotho wokwabelana ukhulisa ukusetshenziswa kobuchwepheshe njengoba kunikeza ukufinyelela (kodwa hhayi ubunikazi) kithi ngokwesidingo. Isizukulwane seminyaka eyinkulungwane naso sihluke kakhulu ezizukulwaneni ezedlule futhi sesiqale ukuvuka kulokho esikufunayo nendlela esifuna ukubumba ngayo umhlaba osizungezile. Umnotho wokwabelana ungasho ukuthi imishini enezikhwama zayo ingenza izinsizakalo ngokufunwa ngabantu futhi isebenze ngokuzimela.

Ukuthengiswa kwezimali kwe-M2M

Amakhasimende ethu akusasa azoba yimishini enezikhwama zemali. I-cryptocurrency ebizwa ngokuthi “i-IOTA (Isicelo Se-inthanethi Sezinto)” ihlose ukuthuthukisa umnotho wemishini ibe ngokoqobo yethu yansuku zonke ngokuvumela imishini ye-IoT ukuthi isebenze kweminye imishini ngokuqondile nangokuzenzakalelayo futhi lokhu kuzoholela ekuveleni okusheshayo kwamamodeli ebhizinisi agxile emshinini. 

I-IOTA ikwenza lokhu ngokususa i-blockchain futhi esikhundleni salokho isebenzise ileja esabalalisiwe ethi ‘tangle’ engakala, engasindi futhi enezimali ezikhokhiswayo eziyiziro okusho ukuthi ukuthengiselana okuncane kuyasebenza okokuqala ngqa. Izinzuzo ezibalulekile ze-IOTA ngaphezu kwezinhlelo zamanje ze-blockchain yilezi:

1. Ukuze uvumele umbono ocacile, i-blockchain ifana nesitolo sokudlela esinabolindi abazinikele (abavukuzi) abakulethela ukudla kwakho. E-Tangle, indawo yokudlela yokuzisiza lapho wonke umuntu ezisebenzela khona. I-Tangle yenza lokhu ngephrothokholi lowo muntu okufanele aqinisekise imisebenzi yakhe emibili yangaphambilini lapho enza umsebenzi omusha. Ngakho-ke abavukuzi, i-middleman entsha eyakha amandla amakhulu kumanethiwekhi e-blockchain, benziwe bangabi namsebenzi nge-Tangle. Isethembiso se-blockchain ukuthi osozimboni bayasixhaphaza noma ngabe banguhulumeni, amabhange anyathelisa imali, izikhungo ezihlukahlukene kodwa esinye isigaba sabavukuzi 'abaphakathi' seba namandla kakhulu, ikakhulukazi abavukuzi baseShayina okuholela ekuhlanganisweni kwamandla amakhulu endaweni encane. inombolo yezandla. Ukumbiwa kwe-Bitcoin kuthatha amandla alingana nogesi okhiqizwa amazwe angaphezu kuka-159 ngakho kuwukumosha okukhulu kwezinsiza zikagesi futhi ngoba i-hardware enkulu yekhompyutha iyadingeka ukuze kukhishwe amakhodi ezibalo ayinkimbinkimbi e-crypto ukuze kuqinisekiswe umsebenzi.
2. Njengoba izimayini kudla isikhathi futhi zibiza, akunangqondo ukwenza ukuthengiselana okuncane noma kwe-nano. I-Tangle ledger ivumela ukuthengiselana ukuthi kuqinisekiswe ngokufana futhi akudingi imali yezimayini ukuze ivumele umhlaba we-IoT ukuthi wenze i-nano kanye ne-microtransactions.
3. Imishini ‘iyimithombo engafakwanga ebhange’ esikhathini sanamuhla kodwa nge-IOTA, imishini ingakwazi ukukhiqiza imali futhi ibe iyunithi ezimele ezisebenza ngokwezomnotho ezingathenga umshwalense, amandla, ukugcinwa nokunye. I-IOTA ihlinzeka ngokuthi “Yazi Umshini Wakho (KYM)” ngobunikazi obuvikelekile obufana nokuthi amabhange akwazi manje i-Know Your Customer (KYC).

I-IOTA iwuhlobo olusha lwe-cryptocurrencies oluhlose ukuxazulula izinkinga ama-cryptos wangaphambilini abengakwazi ukuzixazulula. I-“Tangle” ileja esabalalisiwe iyigama lesiteketiso le-Directed Acyclic Graph njengoba kuboniswe ngezansi: 

I-Directed Acyclic Graph iyinethiwekhi ehlukaniselwe i-cryptographic okucatshangwa ukuthi iyakhula kuze kube phakade futhi imelana nokuhlaselwa okuvela kumakhompyutha we-quantum (asazothuthukiswa ngokugcwele ngokwezentengiselwano futhi asetshenziswe empilweni evamile) ngokusebenzisa uhlobo oluhlukile lokubethela kwamasiginesha asuselwa ku-hash.  

Esikhundleni sokuba nzima ukukala, i-Tangle empeleni iyasheshisa ngokuthengiselana okwengeziwe futhi iba ngcono njengoba ikhula esikhundleni sokuwohloka. Wonke amadivayisi asebenzisa i-IOTA enziwa ingxenye ye-Node ye-Tangle. Kukho konke okwenziwa yi-node, i-node 2 kufanele iqinisekise okunye ukuthengiselana. Ngale ndlela kukhona umthamo ophindwe kabili otholakalayo kunesidingo sokuqinisekisa ukuthengiselana. Le ndawo ephikisana nobuthaka lapho i-tangle ithuthuka ngenxa yesiphithiphithi esikhundleni sokuba sibe sibi kakhulu ngenxa yesiphithiphithi iyinzuzo enkulu ye-Tangle. 

Ngokomlando ngisho namanje, sikhuthaza ukwethenjwa kokwenzekayo ngokurekhoda umkhondo wazo ukuze kufakazele umsuka wokwenziwe, indawo okuyiwa kuyo, inani nomlando. Lokhu kudinga isikhathi esikhulu nemizamo engxenyeni yemisebenzi eminingi efana nabameli, abacwaningi mabhuku, abahloli bekhwalithi kanye nemisebenzi eminingi yokwesekwa. Lokhu, bese kubangela ukuthi abantu babulale ubuhlakani babo ngokuba abaqaphi bezinombolo benza ukuqinisekiswa mathupha kuya le nale, kubangela ukuthi okwenziwayo kubize, kunganembile futhi kubize. Ukuhlupheka kwabantu okuningi kakhulu futhi u-Dukkha ubhekane nabantu abaningi abenza imisebenzi ephindaphindayo ukuze nje bakhe ukwethenjwa kulokhu kuthengiselana. Njengoba ulwazi lungamandla, ukwaziswa okubalulekile kufihlwa yilabo abaphethe ukuze kuvinjwe uquqaba. I-blockchain isivumela ukuthi sikwazi 'ukunqamula konke lokhu kukhohlisa' kwabaphakathi futhi sinikeze amandla kubantu ngobuchwepheshe esikhundleni senhloso eyinhloko yenguquko yesine yezimboni.

Kodwa-ke, i-blockchain yamanje inesethi yayo yemikhawulo mayelana nokulinganisa, izimali zokuthengiselana kanye nezinsiza zekhompuyutha ezidingekayo kumayini. I-IOTA iyiqeda nya i-blockchain ngokuyishintsha ifake ileja esabalalisiwe ethi 'Tangle' ukuze idale futhi iqinisekise okwenziwayo. Inhloso ye-IOTA iwukuba yisinikezeli esibalulekile soMnotho Womshini, okuze kube manje, esibekelwe imingcele ngenxa yemikhawulo yama-cryptos amanje.

Kungabikezelwa ngokunengqondo ukuthi izinhlelo eziningi ze-cyber-physical zizovela futhi zisekelwe ku-Artificial Intelligence kanye ne-IoT njengamaketanga okuhlinzeka, amadolobha ahlakaniphile, igridi ehlakaniphile, ikhompyutha eyabiwe, ukubusa okuhlakaniphile kanye nezinhlelo zokunakekelwa kwezempilo. Izwe elilodwa elinezinhlelo zokuvelela kakhulu nezinolaka ukuze laziwe kakhulu ku-AI ngaphandle kweziqhwaga ezivamile zase-USA naseChina yi-UAE. I-UAE inezinhlelo eziningi ze-AI njengoba ibonise amaphoyisa e-drone, izinhlelo zezimoto ezingashayeli kanye nama-hyperloops, ukubusa okusekelwe ku-blockchain futhi inongqongqoshe wokuqala wezwe emhlabeni we-Artificial Intelligence.

Ukufuna ukusebenza kahle kwakuwukufuna okwaqala kwaqhuba ubunxiwankulu futhi manje wona kanye lo mkhankaso ususebenzela ukuqeda ubunxiwankulu. Umnotho wokuphrinta we-3D nokwabelana wehlisa kakhulu izindleko kanye nokuthuthukisa amazinga okusebenza kahle futhi ‘Umnotho Womshini’ onemishini enezikhwama zedijithali isinyathelo esilandelayo esinengqondo sokusebenza kahle kakhulu. Ngokokuqala ngqa, umshini uzoba iyunithi ezimele ngokwezomnotho ezuza imali engenayo ngamasevisi aphathekayo noma edatha kanye nokuchitha amandla, umshwalense nokunakekela konke ngokwakho. Umnotho odingeka kakhulu uzokhula ngenxa yalokhu kuthenjwa okusabalalisiwe. Ukuphrinta kwe-3D kuzokwehlisa kakhulu izindleko zokwenza izinto zokwakha namarobhothi futhi amarobhothi azimele ngokwezomnotho maduzane azoqala ukunikeza izinsizakalo ngokufunwa ngabantu.

Ukuze ubone ukuqhuma okungaba nawo, zicabange ushintsha imakethe yomshwalense kaLloyd wamakhulu eminyaka. Isiqalo, i-TrustToken izama ukudala umnotho wokuthembana ukuze yenze imisebenzi engu-USD 256 trillion, okuyinani lawo wonke amafa omhlaba wangempela emhlabeni. Ukuthengiselana kwamanje kwenzeka kumamodeli aphelelwe yisikhathi anokungafihli lutho okulinganiselwe, ukuswela imali, ukwethenjwa kanye nezinkinga eziningi. Ukwenza lokhu kuthengiselana usebenzisa amaleja edijithali afana ne-blockchain kunenzuzo enkulu kakhulu ngokusebenzisa amandla okwenza amathokheni. I-Tokenization inqubo lapho izimpahla zomhlaba wangempela ziguqulwa zibe amathokheni edijithali. I-TrustToken yenza ibhuloho phakathi kwedijithali nomhlaba wangempela ngokwenza amathokheni kwezimpahla zomhlaba wangempela ngendlela eyamukelekayo nasemhlabeni wangempela futhi 'iphoqelelwa ngokomthetho, ihlolwe futhi ifakwe umshwalense'. Lokhu kwenziwa ngokudalwa kwenkontileka ye-‘SmartTrust’ eqinisekisa ubunikazi neziphathimandla zezomthetho emhlabeni wangempela, futhi isebenzisa noma yisiphi isenzo esidingekayo lapho inkontileka yephulwa, okuhlanganisa ukuhoxiswa kabusha, ukukhokhisa izinhlawulo zobugebengu nokunye okuningi. I-TrustMarket emisiwe iyatholakala kubo bonke ababambiqhaza ukuthi baqoqe futhi baxoxisane ngezintengo, izinsizakalo kanye ne-TrustTokens iyizimpawu nemiklomelo amaqembu ayitholayo ngokuziphatha okuthembekile, ukudala umkhondo wokucwaninga nokuqinisekisa izimpahla.

Ukuthi i-TrustTokens iyakwazi ukwenza umshwalense ozwakalayo kuyinkulumo-mpikiswano kodwa sesingabona lokhu emakethe kaLloyd yamakhulu eminyaka. Emakethe kaLloyd, abathengi nabathengisi bomshwalense nababhala ngaphansi bahlangana ndawonye ukuze benze umshwalense. Abaphathi bezimali zika-Lloyd baqapha ama-syndicates abo ahlukahlukene futhi banikeze imali eyanele ukuze bathole ukushaqeka okuvela ekufakeni umshwalense. I-TrustMarket inamandla okuba inguqulo yesimanje yemakethe ka-Lloyd kodwa kusesekuseni kakhulu ukunquma impumelelo yayo enembile. I-TrustToken ingavula umnotho futhi idale inani elingcono kanye nezindleko ezincane kanye nenkohlakalo ezimpahleni zangempela zomhlaba, ikakhulukazi ezithengiswayo, umshwalense kanye nempahla edala amandla amaningi kakhulu ezandleni zabambalwa kakhulu.

Ingxenye ye-AI yesibalo se-M2M

Uyinki omningi ubhalwe ku-AI kanye namamodeli ayo okufunda emishini angu-10,000+ anamandla nobuthakathaka bawo futhi asivumela ukuba sembule imininingwane ebifihliwe kithi ngaphambili ukuze sithuthukise kakhulu izimpilo zethu. Ngeke sikuchaze ngokuningiliziwe lokhu kodwa sigxile emikhakheni emibili yokufundisa ngomshini kanye ne-Automated Machine Intelligence (AML) njengoba lezi zizovumela i-IoT ukuthi iguquke isuke kumabhithi ahlukene wehadiwe iye kubathwali abahlanganisiwe bedatha nobuhlakani.

Ukufundisa ngomshini

Ukufundisa ngomshini, mhlawumbe ukuthambekela okukhulu kakhulu esikubonayo okungavumela umnotho we-M2M ukuthi uthuthuke kakhulu kusukela ekuqaleni okuphansi ukuze ube isici esivelele ezimpilweni zethu zansuku zonke. Cabanga nje! Imishini ayisebenzi nje kuphela yodwa namanye amapulatifomu njengamaseva nabantu kodwa futhi iyafundisana. Lokhu sekuvele kwenzekile ngesici se-autopilot se-Tesla Model S. Umshayeli ongumuntu usebenza njengothisha onguchwepheshe emotweni kodwa izimoto zabelana ngale datha futhi zifunde phakathi kwazo zithuthukisa kakhulu ulwazi lwazo ngesikhathi esifushane kakhulu. Manje idivayisi eyodwa ye-IoT akuyona idivayisi eyedwa okuzodingeka ifunde yonke into kusukela ekuqaleni ngokwayo; ingathuthukisa ukufunda ngobuningi okufundwe ngamanye amadivaysi e-IoT afanayo emhlabeni jikelele. Lokhu kusho ukuthi izinhlelo ezihlakaniphile ze-IoT eziqeqeshwe ngokufunda ngomshini azigcini nje ngokuhlakanipha; bahlakanipha ngokushesha ngokuhamba kwesikhathi kumathrendi e-exponential.

Lokhu ‘Kufundisa Ngomshini’ kunezinzuzo ezinkulu ngoba kwehlisa isikhathi sokuqeqeshwa esidingekayo, kudlule isidingo sokuba nedatha enkulu yokuqeqeshwa futhi kuvumela imishini ukuthi izifundele yodwa ukuze ithuthukise ulwazi lomsebenzisi. Lokhu kufundisa ngomshini ngezinye izikhathi kungaba yiqoqo njengezimoto ezizishayelayo zabelana nokufunda ndawonye njengomqondo ohlangene we-hive, noma kungase kube okuphikisayo njengemishini emibili edlala i-chess ngokumelene nayo, umshini owodwa usebenze njengokukhwabanisa omunye umshini njengokukhwabanisa. umtshina nokunye. Umshini ungazifundisa wona ngokudlala izifaniso nemidlalo ngokumelene nawo ngaphandle kwesidingo sanoma yimuphi omunye umshini. I-AlphaGoZero yenze lokho kanye. I-AlphaGoZero ayizange isebenzise noma iyiphi idatha yokuqeqesha futhi yadlala ngokumelene nayo yabe isinqoba i-AlphaGo okwakuyi-AI eyayinqobe abadlali be-Go abahle kakhulu emhlabeni (Go inguqulo edumile ye-Chinese chess). Umuzwa ogogo be-chess ababenawo wokubuka i-AlphaGoZero idlala wawufana nomjaho othuthuke kakhulu we-alien ohlakaniphe kakhulu odlala i-chess.

Izicelo ezivela kulokhu ziyamangalisa; i-hyperloop (isitimela esishesha kakhulu) ama-pods asekelwe kumhubhe axhumana wodwa, imikhumbi ezimele, amaloli, wonke ama-drones agijima ku-swarm intelligence kanye nedolobha eliphilayo lifunda kulo ngokwalo ngokusebenzisana kwegridi ehlakaniphile. Lokhu kanye nezinye izinto ezintsha ezenzeka kuguquko lwesine lwezimboni ze-Artificial Intelligence kungaqeda izinkinga zezempilo zamanje, izinkinga eziningi zomphakathi ezifana nobumpofu obuphelele futhi kusivumele ukuthi sihlanganise iNyanga neMars.

Ngaphandle kwe-IOTA, kukhona nama-Dagcoins nama-byteballs angadingi i-blockchain. Kokubili ama-Dagcoins nama-byteballs aphinde asuselwa ku-DAG Directed Acrelic Graph njengoba nje 'i-tangle' ye-IOTA injalo. Izinzuzo ezifanayo ze-IOTA zisebenza cishe kuma-Dagcoins nama-byteballs njengoba konke lokhu kunqoba imikhawulo yamanje ye-blockhain. 

Ukufundwa komshini okuzenzakalelayo

Kunomongo obanzi wokuzenzakalelayo lapho cishe yonke insimu isolwa futhi akekho okhululekile kulokhu kwesaba kwe-AI apocalypse. Kukhona nohlangothi olukhanyayo lwe-automation lapho kuzovumela abantu ukuthi bahlole 'ukudlala' esikhundleni somsebenzi kuphela. Ukuze uthole ukufakwa okuphelele, bheka lesi sihloko ku-futurism.com

Naphezu kwesasasa nenkazimulo ehlotshaniswa namamodeli amaningi afana nososayensi bedatha, izazi zezibalo, amanani, nabanye abaningi, babhekene nendida ubuhlakani bemishini ezenzakalelayo obuzimisele ukuyixazulula. I-conundrum yigebe phakathi kokuqeqeshwa kwabo nalokho okufanele ngabe bayakwenza uma kuqhathaniswa nalokho abakwenzayo empeleni. Iqiniso elidabukisayo isikhathi esiningi lithathwa umsebenzi wezinkawu (umsebenzi ongenziwa noma iyiphi inkawu esikhundleni somuntu oqeqeshwe ngokomqondo futhi onekhono) njengemisebenzi ephindaphindwayo, ukuhlanganisa izinombolo, ukuhlela idatha, ukuhlanza idatha, ukuyiqonda, ukubhala amamodeli. nokusebenzisa izinhlelo eziphindaphindayo (ukuba yimishini yesipredishithi nakho) kanye nenkumbulo enhle ukuze uhlale uxhumene nazo zonke lezo zibalo. Okufanele ngabe bayakwenza ukwakha, ukukhiqiza ukuqonda okubambekayo, ukukhuluma nabanye ababambiqhaza ukuze balethe imiphumela ebambekayo eqhutshwa yidatha, ukuhlaziya nokuqhamuka nezixazululo ezintsha ‘zezibalo’ ezinkingeni ezikhona.

I-Automated machine intelligence (AML) iyaqikelela ukwehlisa leli gebe elikhulu. Esikhundleni sokuqasha ithimba lososayensi bedatha abangu-200, ososayensi bedatha eyodwa noma abambalwa abasebenzisa i-AML bangasebenzisa ukumodela okusheshayo kwamamodeli amaningi ngesikhathi esisodwa ngoba umsebenzi omningi wokufunda ngomshini usuvele wenziwa ngokuzenzekelayo yi-AML njengokuhlaziywa kwedatha yokuhlola, ukuguqulwa kwezici, Ukukhethwa kwe-algorithm, ukulungiswa kwepharamitha ye-hyper kanye nokuxilongwa kwemodeli. Kunenqwaba yamapulatifomu atholakalayo njengeDataRobot, iGoogle AutoML, Driverless AI ye-H20, IBNR Robot, Nutonian, TPOT, Auto-Sklearn, Auto-Weka, Machine-JS, Big ML, Trifacta, nePure Predictive nokunye kwe-AML hlanganisa inqwaba yama-algorithms afanelekile ngesikhathi esifanayo ukuze uthole amamodeli alungile ngokuya ngemibandela echazwe ngaphambilini. Kungakhathaliseki ukuthi ama-algorithms okufunda ajulile noma ama-algorithms okusakaza-bukhoma, konke kuzenzakalela ngobunono ukuze kutholwe isisombululo esihle okuyilokho esikuthakaselayo ngempela.

Ngale ndlela, i-AML ikhulula ososayensi bedatha ukuthi babe abantu abaningi futhi bangabi nezibali ze-cyborg-Vulcan-human. Imishini ijutshwe kulokho ekwenza kahle kakhulu (imisebenzi ephindaphindwayo, ukumodela) futhi abantu baphathiswe lokho abakwenza kangcono kakhulu (ukuba nobuciko, ukukhiqiza imininingwane ebambekayo ukuze uqhubekisele phambili izinjongo zebhizinisi, ukudala izixazululo ezintsha nokuyithinta). Ngeke ngisho manje ukuthi ‘linda kuqala ngivumele ngibe yi-phD noma uchwepheshe wokufunda ngomshini eminyakeni eyi-10 bese ngizosebenzisa lawa mamodeli; umhlaba uhamba ngokushesha kakhulu manje futhi lokho manje okubalulekile kuphelelwa yisikhathi ngokushesha okukhulu. Isifundo esisheshayo esisekelwe ku-MOOC nokufunda ku-inthanethi kwenza umqondo owengeziwe manje emphakathini wanamuhla obonisa ulwazi esikhundleni somsebenzi owodwa-engaguquki ekuphileni osetshenziswa izizukulwane ezedlule.

I-AML iyadingeka emnothweni we-M2M ngoba ama-algorithms adinga ukuthuthukiswa futhi asetshenziswe kalula ngesikhathi esincane. Esikhundleni sokuthi ama-algorithms adinga ochwepheshe abaningi futhi athatha izinyanga ukuthuthukisa amamodeli abo, i-AML ivala igebe lesikhathi futhi ivumela ukukhiqiza okuthuthukisiwe ekusebenziseni i-AI ezimweni obekungacatshangwa ukuthi ngaphambili.

I-Insuretechs yesikhathi esizayo

Ukwenza inqubo iqhubeke ingenamthungo, ishesha, iqine, ingabonakali futhi ibe lula njengengane edlalayo, ubuchwepheshe be-blockchain busetshenziswa nezinkontileka ezihlakaniphile ezizenza ngokwazo lapho izimo zihlangabezana. Le modeli yomshwalense entsha ye-P2P iqeda inkokhelo ye-premium evamile kusetshenziswa isikhwama semali esidijithali lapho ilungu ngalinye lifaka khona inkokhelo yalo ku-akhawunti yohlobo lwe-escrow kuphela ukuze lisetshenziswe uma kwenziwa isimangalo. Kule modeli, awekho kumalungu aphethe ukuvezwa okukhulu kunenani alifake kumawallet awo edijithali. Uma kungekho zicelo ezenziwayo zonke izikhwama zedijithali zigcina imali yazo. Zonke izinkokhelo kule modeli zenziwa kusetshenziswa i-bitcoin yokunciphisa izindleko zokuthengiselana. I-Teambrella ithi ingumshwalense wokuqala osebenzisa le modeli ngokusekelwe ku-bitcoin. Ngempela, iTeambrella ayiyedwa. Kuneziqalo eziningi ezisekelwe kuma-blockchains eziqondiswe kontanga kumshwalense kontanga nezinye izindawo zemisebenzi yabantu. Ezinye zazo yilezi:

1. I-Etherisc
2. I-Insurepal
3. AIgang
4. Rega Life
5. I-Bit Life and Trust
6. I-Unity Matrix Commons

Ngakho-ke, kusetshenziswe ukuhlakanipha okuningi kwesixuku kulokhu njengomshwalense '.Ufunda kubantu, izinhlelo nabantu, Iqala ngalokho abanakho Futhi Yakha kulokho abakwaziyo’ (Lao Tze).

Esikhundleni se-actuary yokukhulisa inzuzo kubanikazi bamasheya, ukuhlala bebodwa ezintweni ezingokoqobo, ukuntula isikhumba emdlalweni, futhi banokufinyelela okuncane kakhulu ekuqwashiseni (okungukuthi, idatha) yabantu abahlobene nontanga yabo, lo ntanga ukuya kontanga kunika isixuku amandla futhi uthephe. ekuhlakanipheni kwabo (esikhundleni sokuhlakanipha okuvela ezincwadini) okungcono kakhulu. Azikho futhi izinqubo zentengo ezingalungile lapha njengokulinganisa okusekelwe kubulili, ukuthuthukiswa kwentengo okukukhokhisa kakhulu uma mancane amathuba okuthi ushintshele komunye umshwalense futhi okuphambene nalokho. Umshwalense omkhulu akakwazi ukukwazi ngaphezu kontanga yakho, kulula kanjalo.

Lo mshwalense ofanayo wontanga ukuya kontanga ungenziwa kumaleja asabalalisiwe angewona awe-blockchain afana ne-IOTA, i-Dagcoins nama-Byteballs ngezinzuzo ezengeziwe zobuchwepheshe zalawa maleja amasha ngaphezu kwe-blockchain yamanje. Lezi ziqalo zamathokheni edijithali zinesithembiso sokusungula kabusha amamodeli ebhizinisi lapho ukuthengiselana, ukuhlanganisa ndawonye kanye nanoma yini nje yenzelwa umphakathi kanye nomphakathi ngendlela ezenzakalelayo yokwethembeka ngokugcwele ngaphandle kwabaphakathi abacindezelayo njengohulumeni, amabhizinisi onxiwankulu, izikhungo zomphakathi nokunye. I-Peer to Peer Insurance iyingxenye eyodwa nje yalo lonke uhlelo.

Izinkontileka ezihlakaniphile zinezimo ezakhelwe ngaphakathi kuzo eziqalwa ngokuzenzakalelayo lapho kwenzeka isimo esiphuthumayo futhi izimangalo zikhokhelwa ngokushesha. Isidingo esikhulu sabasebenzi abaneziqu eziphezulu kodwa empeleni ukwenza umsebenzi wobufundisi sisuswa ngokuphelele ukuze kwakhiwe inhlangano eshelelayo ezimele yekusasa. Abacindezeli abaphakathi ‘babanikazi bamasheya’ bayagwenywa okusho ukuthi izithakazelo zabathengi zenziwa ngokuhlinzeka ngokunethezeka, amanani aphansi kanye nokwesekwa okuhle kwamakhasimende. Kulesi silungiselelo sontanga kuya kontanga, izinzuzo ziya emphakathini esikhundleni somninimasheya. I-IoT ihlinzeka ngomthombo oyinhloko wedatha kulawa machibi ukuze kuthuthukiswe izivumelwano lapho kukhishwa inkokhelo yesimangalo nalapho kungakhululwa. I-tokenization efanayo isho ukuthi noma ubani noma yikuphi angakwazi ukufinyelela echibini lomshwalense esikhundleni sokukhawulwa yi-geography nemithethonqubo.