Artificial Intelligence uye Sarudzo Systems

Webhusaiti Webhusaiti anoita tsvakiridzo nebudiriro pa Uchenjeri hunobatsira uye masisitimu ekuita sarudzo: “machine learning, data analytics, optimization matekiniki, yakaoma masisitimu, uye nzira dzeBayesian”.

Webhusaiti Webhusaiti ine chigadzirwa hunyanzvi hunyanzvi pa Uchenjeri hunobatsira uye masisitimu ekuita sarudzo: “machine learning, data analytics, optimization maitiro, yakaoma masisitimu, uye nzira dzeBayesian” ed Webhusaiti Webhusaiti ine hunyanzvi mubhizinesi process ruzivo kuvaka tsika software iri modular pa Uchenjeri hunobatsira uye masisitimu ekuita sarudzo: “machine learning, data analytics, optimization matekiniki, yakaoma masisitimu, uye nzira dzeBayesian”.

Webhusaiti Webhusaiti ine hunyanzvi hwechigadzirwa hunyanzvi uye ruzivo mubhizinesi process ruzivo kugadzira tsika software iri modular pa Uchenjeri hunobatsira uye masisitimu ekuita sarudzo: “machine learning, data analytics, optimization matekiniki, yakaoma masisitimu, uye nzira dzeBayesian”.

Webhusaiti Webhusaiti ine chigadzirwa hunyanzvi hunyanzvi pa Uchenjeri hunobatsira uye masisitimu ekuita sarudzo: “machine learning, data analytics, optimization matekiniki, yakaoma masisitimu, uye nzira dzeBayesian” uye inotamisa tsika yekambani uye pamusoro pezvese ruzivo rwekufambisa.

nhoroondo yeArtificial Intelligence (AI) uye Decision Systems yakareba uye yakabatana. Heino mhedziso yenguva dzakakosha uye hukama hwavo:

Matanho Ekutanga (50s-60s)

• Kuberekwa kweAI: Pfungwa yemichina yakangwara inodzokera kumashure zvakanyanya, asi izwi rekuti "Artificial Intelligence” inogadzirwa kuDartmouth Summer Research Project pa chakagadzirwa Intelligence mu 1956.
• Nzira dzekutanga dzekufananidzira: Masisitimu ekutanga akavakirwa pamirau yakatarwa uye kugadzirisa kwekufananidzira kwakazvarwa, ine chinangwa chekudzokorora maitiro ekufunga kwevanhu.

70s nekutanga 80s: Nguva dzekufarira uye kudzikama "AI Winters"

• Nyanzvi Systems: Masisitimu enyanzvi anogadzirwa kune mamwe mashoma minda (semuenzaniso diagnostics yekurapa), zvichiratidza kuti michina inogona kuita fungidziro pahwaro hweruzivo.
• Miganhu yemaitiro ekufananidzira: Iyo scalability uye kuchinjika miganho yeane musoro uye mutemo-yakavakirwa nzira inodzika pasi kufarira kune imwe AI tsvagiridzo.

Kuzvarwa patsva ndatenda kuna machine learning uye masisitimu akavakirwa pa dati (80s - kutanga kwema2000s)

• Machine Kudzidza Algorithms: Tsvagiridzo pane artificial neural network, kutsigira vector michina, sarudzo miti inosuma nzira dzakavakirwa pa dati uye pamienzaniso yekudzidzira uchishandisa mienzaniso.
• Wedzera mukati simba kuverenga: Hardware nyowani inoita kuti zvive nyore kumhanya yakaoma algorithms.
• Hybrid Systems: AI uye Sarudzo Systems dziri kutanga kubatanidza, ine algorithms yekudzidza mitemo yesarudzo uye optimization pane zvebhizinesi mamiriro.

Kuputika kweAI yemazuva ano (2010s - ikozvino)

• Kudzidza Kwakadzika: Yakadzika (multilevel) neural network inova inovhiringidza kuminda senge komputa kuona, nzwisiso yemutauro wechisikigo uye zvimwe zvakawanda.
• Huge uwandu dati: Kuwanikwa kweseti dze dati yehukuru husingaenzaniswi, huchiita kuti iwe udzidzise semuenzaniso-nzara algorithms.
• AI-inotungamirwa Sarudzo Systems: AI inova kiyi pakuita otomatiki maitiro ekuita sarudzo ane humbowo husati hwamboitika uye scalability, semuenzaniso mukuongorora njodzi yechikwereti, kuongororwa kwekurapa, uye zano remunhu muchikamu chekutengesa.

Maitiro uye matambudziko

• Tsanangudzo: Nyaya yepakati ine chekuita nekuita sarudzo dzakaitwa neAI masisitimu dzinotsanangurwa uye dzisina rusaruro, kudzikisira kushandiswa kwavo se "mabhokisi matema."
• Ethics uye mutoro: Ita shuwa kushandiswa kwetsika kweAI-based masisitimu, kuderedza kusarura uye kungangoita rusarura kana kusarurama kukanganisa.
• Kudyidzana Kwevanhu-Muchina: Mamodheru ekuita sarudzo anoshandisa hunyanzvi hwakasiyana hweAI uye nyanzvi dzevanhu dzinopa hukuru hukuru, kunyanya mundima umo kunzwisiswa kwekududzira kwevanhu kwakakosha (semuenzaniso ndima yemutemo, zvimwe zvinhu zvehutano).

mhedziso

Nhoroondo yeAI uye Decision Systems inoenderera mberi co-evolution. Kubva pakuedza kwekutanga kusvika pakudzidza kwakadzama kwemazuva ano, mhedzisiro yekutsvagisa yeAI inopa maturusi matsva ekuita otomatiki uye kutsigira maitiro ekuita sarudzo munzvimbo dzakasiyana siyana. Nekudaro, kufambira mberi uku kunofanirwa kuongororwa tandem nekufunga nezvehutsika, kutsanangurika kwesarudzo uye kuenzana kwakaringana mukubatana pakati pemuchina nenyanzvi dzevanhu zvichibva pane yega dura rekushandisa.

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