{"id":991362,"date":"2024-12-09T10:06:34","date_gmt":"2024-12-09T07:06:34","guid":{"rendered":"https:\/\/www.wayanatapas.com\/?p=991362"},"modified":"2026-07-09T17:52:50","modified_gmt":"2026-07-09T14:52:50","slug":"sarap-dunyasinda-yapay-zekanin-yeri","status":"publish","type":"post","link":"https:\/\/www.wayanatapas.com\/en\/sarap-dunyasinda-yapay-zekanin-yeri\/","title":{"rendered":"The Role of Artificial Intelligence in the World of Wine"},"content":{"rendered":"
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A project in Germany, involving participants from both the private and public sectors, has conducted a series of important studies on the use of Artificial Intelligence (AI) for evaluating wine. The initial findings indicate that the project holds great promise for the future.<\/p>\r\n\r\n\r\n\r\n

2019 y\u0131l\u0131nda Genie adl\u0131 kurulu\u015f bir \u2018Yapay Zek\u00e2 Sommelier\u2019 geli\u015ftirmek i\u00e7in \u00d6noloji Profes\u00f6r\u00fc Dominik Durner\u2019la ba\u011flant\u0131ya ge\u00e7er. O tarihlerde yava\u015f yava\u015f kafas\u0131n\u0131 kald\u0131rmaya ba\u015flayan yapay zek\u00e2 \u00e7al\u0131\u015fmalar\u0131n\u0131n aromalar\u0131n tan\u0131mlanmas\u0131nda nas\u0131l kullan\u0131labilece\u011fi konusunda Prof. Durner\u2019a dan\u0131\u015f\u0131rlar. Bu konunun ara\u015ft\u0131rmaya de\u011fer oldu\u011funu d\u00fc\u015f\u00fcnen Durner, Trier \u00dcniversitesi ve Fraunhofer Enstit\u00fcs\u00fc\u00a0 gibi iki akademik kurum ve \u00fc\u00e7 \u00f6zel \u015firketle i\u015fbirli\u011fi yapar ve sonradan Alman Tar\u0131m Bakanl\u0131\u011f\u0131 da projeyi \u2018Tar\u0131mda Yapay Zek\u00e2\u2019 kapsam\u0131na alarak destekler.<\/p>\r\n\r\n\r\n\r\n

\"Zeka\"<\/figure>\r\n\r\n\r\n\r\n

The initial goal was to determine which aromas could be detected by electromagnetic sensors and whether these sensors could achieve a level comparable to the human sense of smell. Early results were disappointing, as ethanol interfered with the measurement tools. As a result, the project's framework was adjusted to task the sensors with detecting wine faults. To achieve this, researchers selected 100 wines with a common fault: the sulfur effect commonly referred to as \"rotten egg smell.\" After identifying the fault, the sensors were exposed to fault-free wines to determine differences. Prof. Durner likens this process to the myth of Sisyphus, in which the condemned figure endlessly rolls a boulder uphill, only for it to roll back down each time. Similarly, training AI involves repeated measurements over years. Despite this, Prof. Durner finds the progress of the three-year study promising, emphasizing that the application could extend beyond wine. \"The human nose cannot always assess consistently, which is one of its major flaws. However, an AI system trained to interpret scent data from sensors can evaluate consistently with the same performance every time,\" he notes.<\/p>\r\n\r\n\r\n\r\n

At its current stage, the AI system has achieved sensitivity equal to about one-tenth that of the human nose. However, the system can already detect sulfur faults, such as the \"rotten egg smell,\" even before they are noticeable to human noses. The research team is confident that the system will achieve highly reliable results in the future. Once that level is reached, warnings provided by the system during the early stages of fermentation could enable much healthier production planning. They are optimistic that fingerprint-like evaluations of wine will provide effective insights when compared to its performance at later stages. However, it is clear that it will take much longer for AI to match the nuanced quality assessments of professional wine experts.<\/p>\r\n\r\n\r\n\r\n

The most critical requirement for AI is data. Therefore, collecting not hundreds but hundreds of thousands of data points is essential for reliable results. To achieve this, the team partnered with UC Davis in California to involve American researchers in the project, thereby enriching the data pool.<\/p>\r\n

Tahmine Dayal\u0131 Analizler ve Mikro-Teruar\u0131n Dijital \u0130kizi<\/h2>\r\n

Yapay zek\u00e2n\u0131n ba\u011fc\u0131l\u0131k d\u00fcnyas\u0131ndaki en devrimsel dokunu\u015fu, do\u011fan\u0131n o kaotik ve \u00f6ng\u00f6r\u00fclemez de\u011fi\u015fkenlerini matematiksel bir kesinli\u011fe d\u00f6n\u00fc\u015ft\u00fcren tahmine dayal\u0131 analiz modelleridir. Ba\u011f s\u0131ralar\u0131na yerle\u015ftirilen IoT sens\u00f6rlerinden, dronlardan ve meteorolojik uydulardan saniyede akan milyonlarca veri par\u00e7ac\u0131\u011f\u0131 (nem, r\u00fczgar, toprak \u0131s\u0131s\u0131, yaprak stresi), yapay zeka algoritmalar\u0131 taraf\u0131ndan i\u015flenerek ba\u011f\u0131n adeta dijital bir ikizini (digital twin) yarat\u0131r. Bu devasa veri i\u015fleme kapasitesi sayesinde \u00fcreticiler; mildiy\u00f6 veya k\u00fclleme gibi \u00f6l\u00fcmc\u00fcl mantar hastal\u0131klar\u0131n\u0131n ba\u015flama an\u0131n\u0131 g\u00fcnler \u00f6ncesinden tespit edebilir, hasat zamanlamas\u0131n\u0131 milimetrik olarak optimize edebilir ve iklim krizinin yarataca\u011f\u0131 kurakl\u0131k stresine kar\u015f\u0131 asman\u0131n su ihtiyac\u0131n\u0131 yapay zek\u00e2 destekli damlama sistemleriyle otonom olarak y\u00f6netebilir. Topra\u011f\u0131n haf\u0131zas\u0131, art\u0131k dijital bulut sistemlerinde korunmaktad\u0131r.<\/p>\r\n

Algoritmik Harmanlama ve T\u00fcketici Duyusunun Modellenmesi<\/h2>\r\n

Yapay zek\u00e2n\u0131n etki alan\u0131 sadece ba\u011f s\u0131ralar\u0131yla s\u0131n\u0131rl\u0131 kalmay\u0131p, mahzenin kalbine, yani o en kutsal enolojik s\u00fcre\u00e7 olan harmanlama (blending) a\u015famas\u0131na da uzanmaktad\u0131r. Eskiden yaln\u0131zca ba\u015f \u00f6nolo\u011fun y\u0131llara dayanan ki\u015fisel tecr\u00fcbesine ve damak haf\u0131zas\u0131na emanet edilen harmanlama i\u015flemi, bug\u00fcn “Machine Learning” (Makine \u00d6\u011frenimi) algoritmalar\u0131yla yeniden tasarlanmaktad\u0131r. Yapay zek\u00e2, farkl\u0131 f\u0131\u00e7\u0131lardaki \u015faraplar\u0131n asidite, tanen, pH ve u\u00e7ucu bile\u015fen matrislerini analiz ederek, hangi f\u0131\u00e7\u0131lar\u0131n y\u00fczde ka\u00e7 oran\u0131nda kar\u0131\u015ft\u0131r\u0131ld\u0131\u011f\u0131nda hedeflenen o kusursuz rekolte profilini yakalayaca\u011f\u0131n\u0131 binlerce farkl\u0131 senaryo \u00fczerinden saniyeler i\u00e7inde sim\u00fcle eder. Dahas\u0131, k\u00fcresel pazar\u0131n de\u011fi\u015fen tat tercihlerini (\u00f6rne\u011fin daha d\u00fc\u015f\u00fck alkoll\u00fc, daha meyvemsi trendleri) veri madencili\u011fiyle okuyan yapay zek\u00e2, \u00fcreticiye do\u011frudan hedef kitlenin damak zevkine uygun “algoritmik re\u00e7eteler” sunabilmektedir. Enoloji, sanat ve bilimin ard\u0131ndan \u015fimdi de kod yaz\u0131m\u0131yla \u015fekilleniyor.<\/p>\r\n\r\n\r\n\r\n

Projenin ortaya \u00e7\u0131karmay\u0131 ama\u00e7lad\u0131\u011f\u0131 ta\u015f\u0131nabilir bir cihazla \u00fcretim esnas\u0131nda yap\u0131lacak \u00f6l\u00e7\u00fcmlerin an\u0131nda sonu\u00e7 vermesi, b\u00f6ylelikle laboratuvar sonu\u00e7lar\u0131n\u0131n beklenmesi s\u00fcrecinin ortadan kald\u0131r\u0131lmas\u0131 hedefleniyor. Projenin \u015farap d\u0131\u015f\u0131na ta\u015facak uygulamalar\u0131ndan birisinin g\u00fcn\u00fcm\u00fczde e\u011fitimli k\u00f6peklerin kullan\u0131ld\u0131\u011f\u0131 uyu\u015fturucu ve patlay\u0131c\u0131lar\u0131n tespit edilmesi uygulamas\u0131nda k\u00f6peklerin yerini yapay zek\u00e2 sistemlerinin almas\u0131 oldu\u011funu s\u00f6yl\u00fcyor ara\u015ft\u0131rma ekibindekiler. \u00d6te yandan Prof. Durner bu ara\u015ft\u0131rmalarla ortaya \u00e7\u0131kacak de\u011ferlendirme ara\u00e7lar\u0131n\u0131n \u015faraplar\u0131n standartla\u015fmas\u0131na sebep olaca\u011f\u0131 endi\u015fesini ta\u015f\u0131mad\u0131\u011f\u0131n\u0131, \u015faraplar\u0131n terzi usul\u00fc kimliklerinin gerektirdi\u011fi bi\u00e7imde kullan\u0131m\u0131n hep m\u00fcmk\u00fcn olaca\u011f\u0131na inand\u0131\u011f\u0131n\u0131 belirtiyor.<\/p>\r\n\r\n\r\n\r\n

Meanwhile, Prof. Durner dismisses concerns that the tools developed from this research will standardize wine, emphasizing his belief that wines will always retain their tailored, bespoke identities.<\/p>\r\n

Ba\u011f s\u0131ralar\u0131ndaki otonom veri ak\u0131\u015flar\u0131 ve mahzendeki algoritmik harmanlama sim\u00fclasyonlar\u0131yla \u015fekillenen bu f\u00fct\u00fcristik yapay zeka devrimi ilginizi \u00e7ekiyorsa, blogumuzdaki di\u011fer nitelikli teknoloji ve end\u00fcstri ara\u015ft\u0131rmalar\u0131m\u0131za da g\u00f6z atabilirsiniz:<\/p>\r\n