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ليس تقنية واحدة. بل هو مصطلح شامل يتضمن أي نوع من البرامج أو مكونات الأجهزة التي تدعم</span><a href="https://www-techopedia-com.translate.goog/ar/definition/8181/machine-learning-ml?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=en-GB"> <span style="font-weight: 400;">التعلم الآلي</span></a><span style="font-weight: 400;"> والأنظمة الخبيرة</span><a href="https://www-techopedia-com.translate.goog/ar/definition/generative-ai?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=en-GB"> <span style="font-weight: 400;">والذكاء الاصطناعي </span></a>التوليدي <span style="font-weight: 400;">وأنواع معينة من الروبوتات.</span></p> <p><span style="font-weight: 400;">يعمل الذكاء الاصطناعي اليوم في الغالب على أجهزة تقليدية</span> <span style="font-weight: 400;">قائمة على CMOS</span><span style="font-weight: 400;"> ويتضمن مزيجاً من</span> <span style="font-weight: 400;">الخوارزميات</span><span style="font-weight: 400;"> التقليدية ونماذج التعلم الآلي القائمة على البيانات.</span></p> <p><span style="font-weight: 400;">ومع ازدياد دمج هذه التكنولوجيا في التطبيقات اليومية، كان هناك اهتمام متزايد</span> <span style="font-weight: 400;">بهندسة ا</span><span style="font-weight: 400;">لتشكيل العصبي</span><a href="https://www-techopedia-com.translate.goog/definition/32953/neuromorphic-computing?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=en-GB" target="_blank"><span style="font-weight: 400;">،</span></a><span style="font-weight: 400;"> وهو مجال بحثي يسعى إلى محاكاة بنية الدماغ البشري من خلال تصميم أجهزة وخوارزميات متخصصة تم تحسينها لانخفاض استهلاك الطاقة ومعالجتها في الوقت الحقيقي.</span></p> <h2><span id="i">حالات استخدام الذكاء الاصطناعي في الأعمال</span></h2> <p><span style="font-weight: 400;">يُطبَّق الذكاء الاصطناعي حاليًا على مجموعة من الوظائف في المختبر وفي البيئات التجارية/الاستهلاكية، بما في ذلك التقنيات التالية:</span></p> <ul> <li style="font-weight: 400;"><span style="font-weight: 400;">الشبكات</span> <span style="font-weight: 400;">ال</span><span style="font-weight: 400;">عصبونية الاصطناعية</span><span style="font-weight: 400;"> هي نماذج حسابية مستوحاة من بنية الدماغ البشري وعمله. وهي تتألف من عقد مترابطة</span><span style="font-weight: 400;">(خلايا عصبية</span><span style="font-weight: 400;">) تعالج المعلومات وتنقلها، مما يمكّن الشبكة من تعلم الأنماط والعلاقات من البيانات من خلال التدريب.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">التعلُّم</span><a href="https://www-techopedia-com.translate.goog/ar/definition/30325/deep-learning?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=en-GB"> <span style="font-weight: 400;">العميق</span></a><span style="font-weight: 400;"> هو نهج تكراري للذكاء الاصطناعي يقوم على تكديس خوارزميات التعلُّم الآلي في تسلسل هرمي متزايد التعقيد والتجريد. ويُعد التعلّم العميق حالياً أكثر هياكل الذكاء الاصطناعي تطوراً في الوقت الحالي.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">التمييز الصوتي</span><span style="font-weight: 400;"> هو نظام ذكي يسمح بتحويل الكلام البشري إلى نص أو رمز.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">توليد اللغة الطبيعية</span><span style="font-weight: 400;"> هو تمكين التفاعل التخاطب بين البشر والحواسيب.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">الرؤية الحاسوبية</span><span style="font-weight: 400;"> هي تسمح للآلة بمسح صورة واستخدام التحليل المقارن لتحديد الأشياء في الصورة.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">الأنظمة الخبيرة</span><span style="font-weight: 400;"> كانت من أوائل تقنيات الذكاء الاصطناعي التي تم تطويرها في السبعينيات والثمانينيات. وتهدف هذه الأنظمة إلى التقاط المعرفة وعمليات اتخاذ القرار لدى الخبراء البشريين في مجالات محددة واستخدام تلك المعرفة لتقديم التوصيات أو اتخاذ القرارات. على الرغم من أن الأنظمة الخبيرة قد لا تكون محل نقاش واسع النطاق مثل تقنيات الذكاء الاصطناعي الحديثة مثل التعلم العميق والشبكات العصبية، إلا أنها لا تزال لها تطبيقات عملية في مجالات الرعاية الصحية والتمويل والهندسة.</span></li> </ul> <h2><span id="_techopedia__ai">شرح Techopedia للذكاء الاصطناعي (AI)</span></h2> <p><span style="font-weight: 400;">في حين أن الذكاء الاصطناعي غالبًا ما يستدعي صورًا للحاسوب الواعي للخيال العلمي، فإن الواقع الحالي مختلف تمامًا. في العالم الحقيقي، أنظمة الذكاء الاصطناعي هي أدوات متخصصة مصممة لأداء مهام محددة، مثل</span> <span style="font-weight: 400;">التعرف على الصور</span><span style="font-weight: 400;"> أو ترجمة اللغة أو تحليل البيانات. وتفتقر هذه الأنظمة إلى الوعي والعواطف والوعي الذاتي. وبدلاً من ذلك، فهي تعمل بناءً على خوارزميات وأنماط مستفادة من البيانات، وقدراتها محدودة ببرمجتها وتدريبها.</span></p> <h2><span id="i-2">ما هي أنواع الذكاء الاصطناعي وكيف تختلف؟</span></h2> <p><span style="font-weight: 400;">غالبًا ما يتم الحديث عن الذكاء الاصطناعي من حيث كونه إما ضعيفًا أو قويًا. واليوم، معظم تطبيقات الذكاء الاصطناعي في مجال الأعمال هي تطبيقات للتعلم الآلي للذكاء الاصطناعي الضعيف.</span></p> <ul> <li style="font-weight: 400;"><span style="font-weight: 400;">الذكاء الاصطناعي</span> <span style="font-weight: 400;">الضيق (الضعيف</span><span style="font-weight: 400;"> ) قادر على أداء مجموعة محدودة فقط من الوظائف المحددة مسبقًا.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">الذكاء الاصطناعي</span><a href="https://www-techopedia-com.translate.goog/ar/definition/31618/artificial-general-intelligence-agi?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=en-GB"> <span style="font-weight: 400;">العام (القوي)</span></a><span style="font-weight: 400;"> يساوي قدرة العقل البشري على العمل بشكل مستقل وفقًا لمجموعة واسعة من المحفزات;</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">من المتوقع أن يتجاوز الذكاء الاصطناعي الفائق الذكاء البشري في يوم من الأيام (ومن المتوقع أن يسيطر على العالم).</span></li> </ul> <p><span style="font-weight: 400;">كما يتم الحديث عن مبادرات الذكاء الاصطناعي من حيث انتمائها إلى واحدة من أربع فئات:</span></p> <ol> <li style="font-weight: 400;"><span style="font-weight: 400;">الذكاء الاصطناعي التفاعلي يعتمد على البيانات في الوقت الحقيقي لاتخاذ القرارات.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">الذكاء الاصطناعي محدود الذاكرة يعتمد على البيانات المخزنة لاتخاذ القرارات.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">نظرية العقل يمكن للذكاء الاصطناعي أن يأخذ بعين الاعتبار عناصر ذاتية مثل نية المستخدم عند اتخاذ القرارات.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">يمتلك الذكاء الاصطناعي الواعي ذاتيًا وعيًا شبيهًا بوعي الإنسان قادرًا على تحديد الأهداف بشكل مستقل واستخدام البيانات لتحديد أفضل طريقة لتحقيق الهدف.</span></li> </ol> <p><span style="font-weight: 400;">من الطرق الجيدة لتصور هذه الفروق هي تخيل الذكاء الاصطناعي كلاعب بوكر محترف. يبني اللاعب الفعلي جميع قراراته على توزيع الورق الحالي في اللعب، في حين أن اللاعب محدود الذاكرة سيأخذ بعين الاعتبار قراراته وقرارات اللاعبين الآخرين السابقة.</span></p> <p><span style="font-weight: 400;">أما لاعب نظرية العقل فيضع في اعتباره الإشارات السلوكية للاعبين الآخرين، وأخيراً، يتوقف لاعب الذكاء الاصطناعي المحترف الواعي ذاتياً ليفكر فيما إذا كان لعب البوكر لكسب العيش هو حقاً أفضل استخدام لوقته وجهده.</span></p> <h2><span id="i-3">الفرق بين الذكاء الاصطناعي والتعلم الآلي</span></h2> <p><span style="font-weight: 400;">التعلم الآلي (ML) هو مجموعة فرعية من الذكاء الاصطناعي تركز على بناء</span><a href="https://www-techopedia-com.translate.goog/ar/7-applications-of-blockchain-in-the-supply-chain/?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=en-GB"> <span style="font-weight: 400;">نماذج</span></a><span style="font-weight: 400;"> تسمح لأجهزة الكمبيوتر بالتعلم من البيانات. بدلاً من أن تتم برمجتها بشكل صريح لأداء مهمة ما، تستخدم نماذج التعلّم الآلي البيانات لوضع توقعات أو قرارات.</span></p> <p><span style="font-weight: 400;">في الأساس، كل التعلم الآلي هو ذكاء اصطناعي، ولكن ليس كل الذكاء الاصطناعي يستخدم تقنيات التعلم الآلي. على سبيل المثال، تندرج</span> <span style="font-weight: 400;">الأنظمة الخبيرة</span><span style="font-weight: 400;"> القائمة على القواعد</span><a href="https://translate.google.com/website?sl=auto&tl=en&hl=en-GB&u=https://towardsdatascience.com/rise-and-fall-of-symbolic-ai-6b7abd2420f2" target="_blank"> <span style="font-weight: 400;">والذكاء الاصطناعي الرمزي</span></a><span style="font-weight: 400;"> تحت مظلة الذكاء الاصطناعي ولكنها لا تتضمن بالضرورة التعلم من البيانات بالطريقة التي يستخدمها التعلم الآلي.</span></p> <h2><span id="i-4">المراحل المتطورة للذكاء الاصطناعي</span></h2> <p><span style="font-weight: 400;">يمكن أن يُسمح للذكاء الاصطناعي أن يحل محل نظام بأكمله، بحيث يتخذ جميع القرارات من البداية إلى النهاية، أو يمكن استخدامه لتعزيز عملية معينة. على سبيل المثال، يمكن لنظام إدارة المستودعات القياسي أن يُظهر المستويات الحالية لمختلف المنتجات، بينما يمكن لنظام ذكي أن يحدد النقص ويحلل السبب وتأثيره على سلسلة التوريد ككل، بل ويتخذ خطوات لتصحيحه.</span></p> <p><span style="font-weight: 400;">يتزايد الطلب على معالجة المعلومات بشكل أسرع وأكثر كفاءة في استخدام الطاقة بشكل كبير مع تزايد انتشار الذكاء الاصطناعي في تطبيقات الأعمال. لا يمكن لأجهزة المعالجة الرقمية التقليدية مواكبة هذا الطلب. وهذا هو السبب في أن الباحثين يستلهمون من الدماغ ويفكرون في بنيات بديلة تقوم فيها شبكات من الخلايا العصبية الاصطناعية والشبكات العصبية بمعالجة المعلومات بسرعة عالية وقدرات تعلم تكييفية بطريقة موفرة للطاقة وقابلة للتطوير.</span></p> </div> </div> <div class="article-related-sec"> </div> <div class="article-questions"> <ul class="related_question"> <h4>قراءات ذات صلة</h4> <li><a href="https://www-techopedia-com.translate.goog/ar/the-10-best-cryptocurrency-apis-for-developers?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=en-GB">أفضل 10 واجهات لبرمجة تطبيقات العملات المشفرة APIs للمطورين</a></li> <li><a href="https://www-techopedia-com.translate.goog/ar/trends/big-data/10-big-data-dos-and-donts?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=en-GB">10 نصائح حول ما يجب وما لا يجب فعله في سجلات البيانات الضخمة</a></li> </ul> </div> <div class="tech-dictionary-sec"> <div class="tech-term-img"><img width="172" height="37" 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href="https://www-techopedia-com.translate.goog/ar/author/armargaretrouse?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=en-GB">Margaret Rouse</a></h5><span class="author-bottom-exp-mob">Editor</span> <ul> <li class="list-inline-item"><a href="https://translate.google.com/website?sl=auto&tl=en&hl=en-GB&u=https://www.linkedin.com/in/margaretrouse/" target="_blank" rel="noopener"><img width="18" height="18" src="data:image/svg+xml,%3Csvg%20xmlns='http://www.w3.org/2000/svg'%20viewBox='0%200%2018%2018'%3E%3C/svg%3E" data-lazy-src="https://www.techopedia.com/ar/wp-content/themes/twentytwenty-child/images/linkedin.svg"> <noscript> <img width="18" height="18" src="https://www.techopedia.com/ar/wp-content/themes/twentytwenty-child/images/linkedin.svg"> </noscript></a></li> <li class="list-inline-item"><a href="https://translate.google.com/website?sl=auto&tl=en&hl=en-GB&u=https://twitter.com/@techdefinitions" target="_blank" rel="noopener"><img width="22" height="22" 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2011. وتتمثل فكرة مارغريت عن اليوم الممتع في مساعدة المتخصصين في مجال تكنولوجيا المعلومات والأعمال على تعلم التحدث بلغات بعضهم البعض المتخصصة للغاية.</p> <div class="author-read-more"> <a href="https://www-techopedia-com.translate.goog/ar/author/armargaretrouse?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=en-GB" rel="author">جميع المقالات من تأليف Margaret Rouse </a> </div> </div> </div> </div> </div> </div> <div id="sidebar-wrapper" class="single-cont-right single-cont-term"> <div class="jan-dictionary sidebar-dictionary"> <h4>المصطلحات الشائعة</h4> <div class="latest-ans-inner2" data-cat="Artificial Intelligence"> <div class="latest-ans-card"> <div class="popular-wrappercl"><span><a href="https://www-techopedia-com.translate.goog/ar/artificial-intelligence?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=en-GB">الذكاء الاصطناعي</a></span> <h4><a href="https://www-techopedia-com.translate.goog/ar/definition/ai-hallucination?_x_tr_sl=auto&_x_tr_tl=en&_x_tr_hl=en-GB">هلوسة الذكاء الاصطناعي</a></h4> <p 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