5 Ways Artificial Intelligence is Changing the World

آینده هوش مصنوعی در 5 سال
  1. Healthcare: AI is being used to analyze medical images and assist with diagnoses, as well as to develop personalized treatment plans.
  2. Finance: AI is being used to detect and prevent fraud, as well as to make investment decisions.
  3. Transportation: AI is being used to improve traffic flow, optimize routes for self-driving cars, and enhance the safety of transportation systems.
  4. Manufacturing: AI is being used to improve efficiency and productivity in factories, as well as to perform tasks that are too dangerous for humans.
  5. Education: AI is being used to personalize learning experiences, provide feedback to students, and assist with administrative tasks.

The Future of AI: What to Expect in the Next 5 Years”

  1. Advancements in natural language processing (NLP) will continue to improve the ability of AI to understand and respond to human language.
  2. AI-powered virtual assistants will become even more prevalent in our daily lives, helping with tasks such as scheduling, shopping, and banking.
  3. AI will play an increasingly important role in the field of cybersecurity, helping to protect against cyber attacks.
  4. The use of AI in the field of robotics will continue to increase, leading to the development of more advanced and versatile robots.
  5. The ability of AI to learn and adapt will continue to improve, leading to the development of more intelligent and autonomous systems.
/توسط

Artificial Intelligence – Exam Questions

سوالات امتحانی هوش مصنوعیi,a lwk,ud sdlvy

Data Mining

Comming Soon!

Fuzzy Logic

Comming Soon!

Artificial neural networks and deep learning

Comming Soon!

Machine Learning

Comming Soon!

computer vision and image processing

robotics

Expert systems and knowledge representation

Planning and decision making

Game playing and decision making in adversarial environments

Reinforcement learning and decision making.

Evolutionary computation and genetic algorithms

دروس دانشگاهی ارشد هوش مصنوعی

دروس جبرانی:

  • مبانی هوش محاسباتی
  • اصول رباتیکز
  • سیگنال‌ها و سیستم‌ها
  • مبانی بینایی کامپیوتر
  • هوش مصنوعی و سیستم‌ها خبره
  • مبانی پردازش زبان و گفتار
  • طراحی الگوریتم‌ها

دروس گروه 1:

  • شناسایی الگو
  • رایانش تکاملی
  • رابت‌ها متحرک خودگردان
  • یادگیری ماشین
  • هوش مصنوعی پیشرفته
  • فرآیندهای تصادفی
  • شبکه‌های عصبی
  • سیستم‌های چند عاملی

دروس گروه 2:

  • برنامه ریزی هوشمند
  • الگوریتم‌های هوش جمعی
  • مجموعه‌ها و سیستم‌های فازی
  • یادگیری تقویتی
  • نظریه یادگیری آماری
  • مدل‌های گرافی احتمالاتی
  • تصویر پردازی رقمی
  • بینایی کامپیوتری
  • پنهان سازی اطلاعات
  • سنجش از دور
  • پردازش زبان‌های طبیعی
  • پردازش آماری زبان‌های طبیعی
  • ترجمه ماشینی
  • فهم زبان
  • پردازش سیگنال‌های رقمی
  • گفتار پردازی رقمی
  • شناسایی گفتار و گوینده
  • تبدیل متن به گفتار
  • رویکردهای هوش مصنوعی در بازی‌ها
  • رفتارهای هوشمند جمعی در بازی‌ها
  • تصمیم‌گیری، استراتژِ و مسیریابی در بازی‌ها
  • معماری بازی‌ها رایانه‌ای
  • طراحی و توسعه بازی‌های رایانه‌ای
  • سیستم‌های چند رباتی
  • یادگیری تقویتی و کنترل ربات
  • یادگیری تقویتی و کنترل ربات
  • رباتیکز شناختی
  • ریاضیات در رباتیکز
  • فیزیولوژی و آناتومی سیستم اعصاب
  • علم اعصاب سلولی
  • علوم شناختی
  • پردازش سلولی و ملکولی
  • مدل‌های رایانشی در سیستم‌های جمعی
  • نظریع بازی‌ها
  • بهینه سازی
  • داده کاوی پیشرفته
  • پردازش سیگنال آماری
  • تحلیل و پردازش زمان-فرکانس
  • شناسایی مقاوم و بهسازی گفتار

دروس گروه 3:

  • مباحث ویژه 1 در هوش مصنوعی
  • مباحث ویژه 2 در هوش مصنوعی
  • مباحث ویژه 3 در هوش مصنوعی
  • مفاهیم پیشرفته 1 در هوش مصنوعی
  • مفاهیم پیشرفته 2 در هوش مصنوعی
  • مفاهیم پیشرفته 3 در هوش مصنوعی
/توسط

Top AI topics

AI topics

Here are some of the top AI topics currently being researched and developed:

  1. Machine Learning: This is a method of teaching computers to learn from data without being explicitly programmed. It is used in a wide range of applications such as image recognition, natural language processing, and self-driving cars.
  2. Deep Learning: This is a subset of machine learning that involves training neural networks with large amounts of data. It has been used to achieve breakthroughs in areas such as image recognition, speech recognition, and natural language processing.
  3. Natural Language Processing (NLP): This is the application of AI to the understanding and manipulation of human language. It is used in applications such as speech recognition, language translation, and text-to-speech synthesis.
  4. Computer Vision: This is the application of AI to the understanding of visual data, such as images and videos. It is used in applications such as image recognition, facial recognition, and self-driving cars.
  5. Robotics: This is the application of AI to the control and movement of robots. It is used in areas such as manufacturing, healthcare, and logistics.
  6. Reinforcement Learning: This is a type of machine learning that involves training an agent to make decisions based on rewards and penalties. It is used in areas such as robotics, gaming, and finance.
  7. Generative Models: These are algorithms that can create new content, such as images, videos, or text. They have the potential to revolutionize industries such as art, design, and entertainment.
  8. Explainable AI: This is a field of study that aims to make AI models more transparent and understandable to humans. It is important for building trust in AI systems and ensuring their safe and fair use.
  9. AI in Healthcare: AI is being used to analyze medical data, assist doctors in diagnoses and treatment, and improve patient outcomes.
  10. AI in Finance: AI is being used to analyze financial data, detect fraud and make smarter investment decisions.

Here are some additional AI topics that are currently being researched and developed:

  1. Generative Adversarial Networks (GANs): These are a type of neural network architecture used for generative tasks such as image synthesis.
  2. Transfer Learning: This is a technique where a model pre-trained on one task is fine-tuned for a new task.
  3. Neural Architecture Search: This is the process of automating the design of neural network architectures.
  4. Cognitive Computing: This is a type of AI that mimics the way the human brain works, focusing on natural language understanding, machine learning, and neural networks.
  5. Multi-agent Systems: This is a field of AI that studies the behavior of multiple agents interacting in a shared environment.
  6. Human-AI Interaction: This is a field of study that focuses on designing AI systems that can communicate and interact with humans in a natural and intuitive way.
  7. AI in Agriculture: This is the application of AI to the field of agriculture, such as precision farming and crop monitoring.
  8. AI in Education: This is the application of AI to the field of education, such as personalized learning and automated grading.
  9. AI in Marketing: This is the application of AI to the field of marketing, such as customer segmentation and personalized marketing campaigns.
  10. AI in Supply Chain Management: This is the application of AI to the field of supply chain management, such as demand forecasting and inventory optimization.
  11. AI in Cybersecurity: This is the application of AI to the field of cybersecurity, such as intrusion detection and threat hunting.
  12. AI in Energy: This is the application of AI to the field of energy, such as power grid optimization and predictive maintenance.
  13. AI in Manufacturing: This is the application of AI to the field of manufacturing, such as process optimization and predictive maintenance.

These are just a few examples of the many different areas where AI is being researched and developed. The field is constantly evolving and new applications are being discovered all the time.

/توسط

Artificial intelligence (AI) is a fascinating and rapidly evolving field

Artificial intelligence (AI) is a fascinating and rapidly evolving field that has the potential to change the way we live and work in countless ways. From self-driving cars to intelligent personal assistants, AI is already being used in a wide range of applications that make our lives more convenient and efficient.

But the potential of AI goes far beyond just these examples.

One of the most exciting areas of AI research today is the field of deep learning. This is a type of machine learning that involves training neural networks with large amounts of data in order to make predictions or decisions. This approach has been used to achieve breakthroughs in areas such as image recognition, speech recognition, and natural language processing.

One of the most famous example of deep learning is AlphaGo, an AI program developed by Google DeepMind. AlphaGo was able to defeat the world champion of Go, a complex board game that is considered to be much more difficult for computers to master than chess. This accomplishment was a major milestone in the field of AI, and it demonstrated the incredible potential of deep learning to solve complex problems.

Another interesting area of AI research is the field of generative models. These are algorithms that can create new content, such as images, videos, or text. For example, a generative model could be trained on a dataset of images of faces and then generate new images of faces that have never been seen before. This technology has the potential to revolutionize industries such as art, design, and entertainment.

AI can also be used to improve our healthcare system. AI algorithms can be trained on large datasets of medical records and images to identify patterns that can be used to make earlier and more accurate diagnoses of diseases. This can help doctors to make better treatment decisions and ultimately improve patient outcomes.

As you can see, the possibilities of AI are vast and varied. It is an exciting time for this field, and we are only just beginning to scratch the surface of what is possible. With continued research and development, we can expect to see even more groundbreaking applications of AI in the future.

/توسط

It only takes three seconds for Microsoft’s new AI tool to mimic your voice

هوش مصنوعی مایکروسافت - تشخیص صدا در 3 ثانیههوش مصنوعی سیمرغ

VALL-E می تواند لحن احساسی سخنران اصلی را حفظ و حتی محیط صوتی او را شبیه سازی کند.

علیرغم اینکه پیشرفت‌های زیادی که در تولید ویدیو با هوش مصنوعی انجام شده است، هنوز هم به مقدار زیادی از داده های اولیه مانند عکس‌های سر از زوایای مختلف یا فیلم‌های ویدئویی نیاز داریم تا سیستم بتواند یک نسخه عمیق جعلی متقاعدکننده از شباهت شما ایجاد کند. وقتی صحبت از جعل کردن صدای شما به میان می آید، این داستان متفاوت است، زیرا محققان مایکروسافت اخیرا یک ابزار هوش مصنوعی جدید را معرفی کرده اند که می تواند صدای افراد
را تنها با استفاده از یک نمونه سه ثانیه ای از صحبت کردن آنها شبیه سازی کند.

/توسط