{"id":6571,"date":"2023-07-16T14:55:00","date_gmt":"2023-07-16T11:55:00","guid":{"rendered":"https:\/\/www.hitexis.com\/?p=6571"},"modified":"2025-06-30T16:37:38","modified_gmt":"2025-06-30T13:37:38","slug":"data-science-trends-2023-ai-adoption-and-market-growth","status":"publish","type":"post","link":"https:\/\/www.hitexis.com\/lv\/data-science-trends-2023-ai-adoption-and-market-growth\/","title":{"rendered":"Datu zin\u0101tnes tendences 2023: m\u0101ksl\u012bg\u0101 intelekta ievie\u0161ana un tirgus izaugsme"},"content":{"rendered":"
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Datu zin\u0101tne ir karst\u0101ka nek\u0101 jebkad. 2023. gad\u0101 Eiropas datu anal\u012btikas tirgus jau bija milz\u012bgs \u2014 aptuveni 75,45 miljardi ASV dol\u0101ru, un tiek prognoz\u0113ts, ka tas sasniegs 219,76 miljardus l\u012bdz 2031. gadam (vid\u0113jais gada pieauguma temps \u2014 14,3%). Uz\u0146\u0113mumi akt\u012bvi invest\u0113 anal\u012btik\u0101 un m\u0101ksl\u012bgaj\u0101 intelekt\u0101, lai ieg\u016btu konkurences priek\u0161roc\u012bbas. \u0160ogad v\u0113rojams strauj\u0161 \u0123enerat\u012bv\u0101 MI pieaugums \u2014 piem\u0113ram, ChatGPT l\u012bdz 2023.\u202fgada janv\u0101rim sasniedza aptuveni 100 miljonus akt\u012bvu lietot\u0101ju m\u0113nes\u012b, k\u013c\u016bstot par visstrauj\u0101k augo\u0161o lietotni v\u0113stur\u0113. Tas nor\u0101da uz milz\u012bgu interesi par MI r\u012bkiem.<\/p>

\u00a0<\/p>

Tom\u0113r komerci\u0101l\u0101 MI ievie\u0161ana v\u0113l joproj\u0101m atrodas att\u012bst\u012bbas stadij\u0101. Jaun\u0101kie dati liecina, ka tikai aptuveni 8% ES uz\u0146\u0113mumu (ar \u226510 darbiniekiem) 2023. gad\u0101 izmantoja k\u0101du no MI tehnolo\u0123ij\u0101m. Vado\u0161\u0101s valstis (D\u0101nija, Somija) zi\u0146o par aptuveni 15% lietojumu, bet daudz\u0101s cit\u0101s valst\u012bs \u0161ie r\u0101d\u012bt\u0101ji ir iev\u0113rojami zem\u0101ki. \u0160\u012b plaisa nor\u0101da uz lielu izaugsmes potenci\u0101lu, uz\u0146\u0113mumiem turpinot digitaliz\u0101ciju. Ar\u012b pati Eiropas Savien\u012bba akt\u012bvi fokus\u0113jas uz MI un saist\u012bto p\u0113tniec\u012bbu un izstr\u0101di: 2025. gada zi\u0146ojums uzsver ES l\u012bder\u012bbu t\u0101d\u0101s jom\u0101s k\u0101 m\u0101ksl\u012bgais intelekts, digit\u0101lie dv\u012b\u0146i un biotehnolo\u0123ijas.<\/p>

Galven\u0101s tendences<\/p>

  • \u0122enerat\u012bvais MI un lielie valodas mode\u013ci (LLM): Tekstu un att\u0113lu \u0123ener\u0113jo\u0161ie mode\u013ci b\u016btiski maina anal\u012bti\u0137u darba veidu. GPT tipa r\u012bki pal\u012bdz sagatavot atskaites, veikt datu vaic\u0101jumus dabiskaj\u0101 valod\u0101 un izveidot mode\u013cu prototipus. Agr\u012bnie \u0161o r\u012bku lietot\u0101ji zi\u0146o par \u0101tr\u0101ku darba pl\u016bsmu un inovat\u012bv\u0101m lietojuma iesp\u0113j\u0101m (piem\u0113ram, personaliz\u0113ti ieteikumi, autom\u0101tiska satura \u0123ener\u0113\u0161ana).<\/li>
  • Automatiz\u0113t\u0101 ma\u0161\u012bnm\u0101c\u012b\u0161an\u0101s (AutoML): Ma\u0161\u012bnm\u0101c\u012b\u0161an\u0101s demokr\u0101tiz\u0101cija noz\u012bm\u0113 vair\u0101k r\u012bku automatiz\u0113tai mode\u013cu izveidei. Platformas, piem\u0113ram, Azure ML un Google AutoML, \u013cauj ar\u012b neekspertiem izstr\u0101d\u0101t prognoz\u0113jo\u0161us mode\u013cus. Tas papla\u0161ina anal\u012btikas iesp\u0113jas ar\u012b \u0101rpus datu zin\u0101tnes noda\u013c\u0101m un dod iesp\u0113ju biznesa lietot\u0101jiem pa\u0161iem izmantot MI r\u012bkus.<\/li>
  • Datu platformas m\u0101kon\u012b: Uz\u0146\u0113mumi turpina p\u0101rvietot datus uz m\u0101koni, lai veiktu lielapjoma datu anal\u012bzi. Par standartu k\u013c\u016bst datu ezera-noliktavu (lakehouse) un p\u0101rvald\u012btu datu noliktavu risin\u0101jumi, piem\u0113ram, Databricks, Snowflake un BigQuery, kas nodro\u0161ina m\u0113rogojamu apstr\u0101di. Aug ar\u012b re\u0101llaika datu straum\u0113\u0161ana (piem\u0113ram, Kafka, Flink), kas \u013cauj ieg\u016bt t\u016bl\u012bt\u0113ju ieskatu datos.<\/li>
  • Atbild\u012bgs MI un p\u0101rvald\u012bba: L\u012bdz ar pieaugo\u0161u datu izmanto\u0161anu pieaug ar\u012b regul\u0113jums. GDPR iev\u0113ro\u0161ana un topo\u0161\u0101 ES M\u0101ksl\u012bg\u0101 intelekta regula (AI Act) liek datu priv\u0101tumam un \u0113tikai k\u013c\u016bt par priorit\u0101ti. Pieaug tendence uz izskaidrojamu MI (explainable AI) un sp\u0113c\u012bgu datu p\u0101rvald\u012bbu, lai veidotu uztic\u0113\u0161anos.<\/li>
  • Perif\u0113r\u0101 anal\u012btika un IoT dati: Sensoru izplat\u012bba (industri\u0101lais IoT, telemetrija) veicina piepras\u012bjumu p\u0113c perif\u0113r\u0101s (edge) anal\u012btikas. Dati arvien bie\u017e\u0101k tiek apstr\u0101d\u0101ti lok\u0101li uz ier\u012bc\u0113m, samazinot aizturi (latency). T\u0101pat tiek p\u0113t\u012btas datu re\u017e\u0123a (data mesh) arhitekt\u016bras, kas \u013cauj komand\u0101m pa\u0161\u0101m p\u0101rvald\u012bt savas datu pl\u016bsmas un atbild\u0113t par t\u0101m.<\/li><\/ul>

    Kopsavilkum\u0101 \u2013 2023. gada datu zin\u0101tni raksturo strauja izaugsme un entuziasms par m\u0101ksl\u012bgo intelektu. Nozare ir uz papla\u0161in\u0101\u0161an\u0101s sliek\u0161\u0146a: glob\u0101las aptaujas liecina, ka aptuveni 78% uz\u0146\u0113mumu jau izmanto MI k\u0101d\u0101 form\u0101, un Eiropa virz\u0101s uz priek\u0161u inov\u0101ciju jom\u0101. Uz\u0146\u0113mumi, kas invest\u0113 datu infrastrukt\u016br\u0101, att\u012bsta komandu prasmes un ievie\u0161 \u0161\u012bs tendences, sp\u0113s p\u0101rv\u0113rst ieskatus konkurences priek\u0161roc\u012bb\u0101.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

    Data science is hotter than ever. In 2023, Europe\u2019s data analytics market was already vast \u2013 around\u00a0$75.45 billion\u00a0\u2013 and is projected to reach $219.76B by 2031 (14.3% CAGR). Businesses are investing heavily in analytics and AI for competitive insight. This year saw the explosive growth of generative AI: for example,\u00a0ChatGPT\u00a0reached an estimated\u00a0100\u202fmillion monthly active users […]<\/p>\n","protected":false},"author":10,"featured_media":6127,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[31],"tags":[],"class_list":["post-6571","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"_links":{"self":[{"href":"https:\/\/www.hitexis.com\/lv\/wp-json\/wp\/v2\/posts\/6571","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.hitexis.com\/lv\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.hitexis.com\/lv\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.hitexis.com\/lv\/wp-json\/wp\/v2\/users\/10"}],"replies":[{"embeddable":true,"href":"https:\/\/www.hitexis.com\/lv\/wp-json\/wp\/v2\/comments?post=6571"}],"version-history":[{"count":7,"href":"https:\/\/www.hitexis.com\/lv\/wp-json\/wp\/v2\/posts\/6571\/revisions"}],"predecessor-version":[{"id":6752,"href":"https:\/\/www.hitexis.com\/lv\/wp-json\/wp\/v2\/posts\/6571\/revisions\/6752"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.hitexis.com\/lv\/wp-json\/wp\/v2\/media\/6127"}],"wp:attachment":[{"href":"https:\/\/www.hitexis.com\/lv\/wp-json\/wp\/v2\/media?parent=6571"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.hitexis.com\/lv\/wp-json\/wp\/v2\/categories?post=6571"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.hitexis.com\/lv\/wp-json\/wp\/v2\/tags?post=6571"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}