Artificial Intelligence Agents: Intelligent Systems Shaping the Future

 

Hello everyone. One of the topics that I am most interested in these days, that I want to research and share with you is artificial intelligence and other concepts that come into our lives with it. When I looked at the artificial intelligence trends that we will hear a lot about in 2025, the first title I saw was “Artificial Intelligence Agents”. And I was very curious about what it was, I researched, compiled and brought it here. Here are the artificial intelligence agents…

Artificial intelligence is revolutionizing many fields today and spreading to every corner of our lives, it is something we talk about and encounter all the time. One of the most important elements of this technology is “artificial intelligence agents”, which I heard for the first time. So, what are these artificial intelligence agents, how do they work and why are they so important? In this article, I have tried to explain in detail the basic principles of artificial intelligence agents, their usage areas and how they will affect us in the future.

What is an Artificial Intelligence Agent? (AI Agent)

In simple terms, an AI agent is software that performs specific tasks in a given environment by collecting data, analyzing and making decisions in that environment. These agents work based on specific rules and learning algorithms. Unlike humans, an AI agent can analyze data very quickly, recognize patterns and make automated decisions.

Characteristics:

1. Sensing: It can collect information from its environment through sensors or data sources.
2. Decision Making: Analyze the collected data and create an action plan.
3. Learning: It can learn from its past experiences and make better decisions.
4. Autonomy: It can perform certain tasks without the need for human intervention, i.e. it can start the process of automatization.
5. Interaction: It can work more efficiently by communicating with users or other systems.

Types of Artificial Intelligence Agents

AI agents fall into different categories according to their tasks and operating principles. Here are the most common types of AI agents:

Simple Reflex Agents
These agents produce specific outputs to specific inputs. So when a situation arises, they respond directly with a predefined response. For example, a thermostat turns the heating on or off when it reaches a set temperature value. You can think of it like the systems used in smart homes. If you want to get more detailed information about this, I share the link below.

SmythOS - Autonomous Agents in Home Automation

Imagine walking into a home that knows exactly what you need before you do. Welcome to the world of autonomous agents…

smythos.com

Situational Reflex Agents
These agents make decisions based not only on the current input, but also on their previous state. For example, autonomous vehicles navigate based not only on current traffic data but also on past navigation information. If you want to get more detailed information about this, I share the link below.

AI Agents in Autonomous Vehicles: Enhancing Safety & Efficiency

Learn how AI agents in autonomous vehicles boost safety, efficiency with real-time decisions, and reduce human error.

www.allaboutai.com

Target Oriented Agents
These agents aim to achieve a specific goal. For example, a chess AI tries to win the game by determining the best move. For example
Chessus. If you want to get more detailed information about it, I share the link below.

GitHub - masonleon/ai-chess-agent: A chess playing AI agent that can rationally pick moves and win…

A chess playing AI agent that can rationally pick moves and win a reasonable number of times using the Minimax and…

github.com

Learning Agents
Such agents become smarter as they learn from their environment. Using machine learning and deep learning algorithms, they can make better decisions over time. For example, voice assistants (Siri, Google Assistant) offer suggestions by analyzing user habits.

Multi-Agent Systems
They are systems designed for multiple AI agents to work together to solve complex problems. For example, a network of autonomous drones can work together to explore a large area.

Usage Areas of Artificial Intelligence Agents

So far, I have talked about what artificial intelligence agents are, their types and some examples. But where are these agents mostly used, in which areas are they needed? Here are the most important areas of use:

Health Sector
In the healthcare sector, AI agents can analyze medical images to diagnose diseases, monitor patients’ health data to provide early warning systems and speed up drug development.

Finance and Economics
These agents can guide investors by making stock forecasts, perform fraud detection for banks, and speed up transactions by providing automated customer service.

Autonomous Vehicles
In autonomous vehicles, AI agents can act in accordance with traffic rules, provide safe driving by recognizing objects in the environment and optimize navigation systems.

Education Technologies
AI agents in education can deliver personalized instruction based on students’ learning speed and provide feedback by analyzing student performance.

Customer Service
In customer support processes, services can be managed using chatbots and virtual assistants. In addition, processes can be accelerated with automated email responses and call forwarding systems.

Security and Defense
AI agents can detect and prevent cybersecurity threats and be used in military strategies.

Smart Home and Internet of Things (IoT)
In smart home systems, AI agents can make smart thermostats, lighting and security systems work more efficiently.

What about the Disadvantages?

I have explained where and what kind of jobs AI agents are useful for. They offer advantages such as optimizing business processes, minimizing errors and accelerating decision-making processes. While I will list them again below, another question that came to my mind was the disadvantages. While it works so well, doesn’t it also have its challenges? Here is the answer:

Advantages:
- Reduces human errors.
- Increases productivity.
- Reduces costs.
- Provides personalized services.

Challenges and Ethical Issues:
- Data privacy and security risks.
- Automation that may lead to loss of labor.
- Bias in artificial intelligence algorithms.

Artificial Intelligence Agents in the Future

The development of artificial intelligence agents continues unabated. In the future, these systems are expected to become more independent and intelligent. They are also expected to be able to interact with humans in a more natural way and have a more ethical structure.

However, it is critical to set ethical rules and legal regulations so that AI agents do not harm society. Artificial intelligence agents developed in line with transparency, security and ethical principles can make our lives easier in the future.

As a result, as far as I understand from my research, artificial intelligence agents are one of the most exciting technologies of our time, enabling major transformations in many sectors and are likely to do much more. As individual users, we already benefit from these systems in many areas from health to transportation, education to security. However, I think it is also important to consider the ethical and security dimensions of these developments. Nevertheless, when used correctly, AI agents can help create a more efficient and safer world that makes human life easier. I look forward to seeing how this technology evolves in the coming years.

I hope you found this article useful! If you appreciate the information provided, you have the option to support me by Buying Me A Coffee! Your gesture would be greatly appreciated!

Thank you so much for reading.

If you found it valuable, hit the clap button 👏 and consider following me for more such content.

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Selin.

Yapay Zeka Ajanları: Geleceği Şekillendiren Akıllı Sistemleri

 

Herkese merhaba. Bu aralar en çok ilgimi çeken, araştırmak ve sizlerle paylaşmak istediğim konuların başında yapay zeka ve onunla birlikte hayatımıza giren diğer kavramlar geliyor. 2025'te çok duyacağımız yapay zeka trendlerine baktığımda ise ilk gördüğüm başlık “Yapay Zeka Ajanları” oldu. Ve ne olduğunu çok merak ettim, araştırdım, derleyip buraya taşıdım. İşte yapay zeka ajanları…

Yapay zeka günümüzde birçok alanda devrim yaratıyor ve hayatımızın her köşesine yayılıyor, bu hep konuştuğumuz, karşılaştığımız bir şey. Bu teknolojinin en önemli unsurlarından biri de “yapay zeka ajanları” imiş, ben de ilk kez duydum. Peki, nedir bu yapay zeka ajanları, nasıl çalışırlar ve neden bu kadar önemlidirler? Bu yazımda, yapay zeka ajanlarının temel prensiplerini, kullanım alanlarını ve gelecekte bizleri nasıl etkileyeceklerini detaylı bir şekilde anlatmaya çalıştım.

Yapay Zeka Ajanı Nedir?

Basit bir ifadeyle yapay zeka ajanı, belirli bir ortamda veri toplayarak, analiz yaparak ve karar vererek o ortamda belirli görevleri yerine getiren bir yazılımdır. Bu ajanlar, belirli kurallara ve öğrenme algoritmalarına dayanarak çalışır. İnsanlardan farklı olarak, bir yapay zeka ajanı verileri çok hızlı analiz edebilir, örüntüleri tanıyabilir ve otomatik kararlar alabilir.

Özellikleri:

1. Algılama: Sensörler veya veri kaynakları aracılığıyla çevresinden bilgi toplayabilir.
2. Karar Verme: Topladığı verileri analiz ederek bir aksiyon planı oluşturabilir.
3. Öğrenme: Geçmiş deneyimlerinden ders çıkararak daha iyi kararlar alabilir.
4. Otonomluk: İnsan müdahalesine ihtiyaç duymadan belirli görevleri yerine getirebilir yani otomatizasyon sürecini başlatabilir.
5. Etkileşim: Kullanıcılarla veya diğer sistemlerle iletişim kurarak daha verimli çalışabilir.

Yapay Zeka Ajanlarının Çeşitleri

Yapay zeka ajanları, görevlerine ve çalışma prensiplerine göre farklı kategorilere ayrılır. İşte en yaygın yapay zeka ajan türleri:

1. Basit Refleks Ajanları
Bu ajanlar, belirli girdilere belirli çıktılar üretir. Yani bir durum ortaya çıktığında, doğrudan önceden tanımlanmış bir yanıt verirler. Örneğin, bir termostat, belirlenen sıcaklık değerine ulaştığında ısıtmayı açar veya kapatır. Akıllı evlerde kullanılan sistemler gibi düşünebilirsiniz. Bununla ilgili daha detaylı bilgi almak isterseniz aşağıda linkini paylaşıyorum.

Yapay zekânın kullanıldığı "Akıllı ev sistem projeleri..." - TOSYÖV Girişimcinin Gücü

Türkiye Küçük ve Orta Ölçekli İşletmeler, Serbest Meslek Mensupları ve Yöneticiler Vakfı

tosyov.org.tr

2. Durumsal Refleks Ajanları
Bu ajanlar, yalnızca mevcut girdiye değil, aynı zamanda önceki durumlarına da bakarak karar alır. Örneğin, otonom araçlar, yalnızca anlık trafik verilerine değil, geçmiş seyir bilgilerine de dayanarak yol alırlar. Bununla ilgili daha detaylı bilgi almak isterseniz aşağıda linkini paylaşıyorum.

Yapay Zeka Otonom Araçlarda Nasıl Çalışır?

Yapay zeka ile otomobil teknolojisini buluşturan otonom araçlar yakın geçmişte hayal gibi gözükürken, yakın gelecekte…

www.yapayzekatr.com

3. Hedef Odaklı Ajanlar
Bu ajanlar, belirli bir hedefe ulaşmayı amaçlar. Mesela, bir satranç yapay zekası en iyi hamleyi belirleyerek oyunu kazanmaya çalışır. Örneğin 
Chessus. Bununla ilgili daha detaylı bilgi almak isterseniz aşağıda linkini paylaşıyorum.

Yapay Zeka Satranç Motoru - AI Exploration

Chessus, yapay zeka satranç motorudur. En iyi hamleyi bulmak için 3 seviyeli derin arama, minimax ve alfa-beta budama…

aix.web.tr

4. Öğrenen Ajanlar
Bu tür ajanlar, çevrelerinden öğrendikçe daha akıllı hale gelirler. Makine öğrenmesi ve derin öğrenme algoritmaları kullanarak zamanla daha iyi kararlar alabilirler. Örneğin, sesli asistanlar (Siri, Google Assistant) kullanıcı alışkanlıklarını analiz ederek öneriler sunar.

5. Çoklu Ajan Sistemleri
Birden fazla yapay zeka ajanının bir arada çalışarak karmaşık problemleri çözmesi için tasarlanmış sistemlerdir. Örneğin, bir otonom drone ağı, birlikte çalışarak geniş bir alanı keşfedebilir.

Yapay Zeka Ajanlarının Kullanım Alanları

Buraya kadar yapay zeka ajanlarının ne olduğundan, çeşitlerinden ve bazı örneklerden bahsettim. Peki bu ajanlar en çok nerelerde kullanılır, hangi alanlarda kendilerine ihtiyaç duyulur? İşte en önemli kullanım alanları:

1. Sağlık Sektörü
Yapay zeka ajanları, sağlık sektöründe hastalık teşhisi koymak için tıbbi görüntü analizi yapabilir, hastaların sağlık verilerini izleyerek erken uyarı sistemleri sunabilir ve ilaç geliştirme süreçlerini hızlandırabilir.

2. Finans ve Ekonomi
Bu ajanlar, hisse senedi tahminleri yaparak yatırımcıları yönlendirebilir, bankalar için dolandırıcılık tespiti gerçekleştirebilir ve otomatik müşteri hizmetleri sağlayarak işlemleri hızlandırabilir.

3. Otonom Araçlar
Otonom araçlarda yapay zeka ajanları, trafik kurallarına uygun şekilde hareket edebilir, çevredeki nesneleri tanıyarak güvenli bir sürüş sağlayabilir ve navigasyon sistemlerini optimize edebilir.

4. Eğitim Teknolojileri
Eğitimde yapay zeka ajanları, öğrencilerin öğrenme hızına göre kişiselleştirilmiş eğitim sunabilir ve öğrenci performansını analiz ederek geri bildirim sağlayabilir.

5. Müşteri Hizmetleri
Müşteri destek süreçlerinde, chatbot’lar ve sanal asistanlar kullanılarak hizmetler yönetilebilir. Ayrıca, otomatik e-posta yanıtları ve çağrı yönlendirme sistemleriyle süreçler hızlandırılabilir.

6. Güvenlik ve Savunma
Yapay zeka ajanları, siber güvenlik tehditlerini tespit edip önleyebilir ve askeri stratejilerde kullanılabilir.

7. Akıllı Ev ve Nesnelerin İnterneti (IoT)
Akıllı ev sistemlerinde, yapay zeka ajanları sayesinde akıllı termostatlar, aydınlatmalar ve güvenlik sistemleri daha verimli çalışabilir.

Peki ya Dezavantajları?

Yapay zeka ajanlarının nerelerde, ne türden işlere yaradığını anlattım. İş süreçlerini optimize etmek, hataları minimize etmek ve karar alma süreçlerini hızlandırmak gibi avantajlar sunuyor. Bunları aşağıda yeniden maddeler halinde sıralamak ile birlikte aklıma gelen bir diğer soru dezavantajları oldu. Bu kadar işe yararken zorlukları da yok mu? İşte cevabı:

Avantajlar:
- İnsan hatalarını azaltır.
- Verimliliği artırır.
- Maliyetleri düşürür.
- Kişiselleştirilmiş hizmetler sunar.

Zorluklar ve Etik Sorunlar:
- Veri gizliliği ve güvenliği riskleri.
- İş gücü kaybına yol açabilecek otomasyon.
- Yapay zeka algoritmalarında yanlılık (bias) sorunu.

Gelecekte Yapay Zeka Ajanları

Yapay zeka ajanlarının gelişimi hız kesmeden devam ediyor. Gelecekte, bu sistemlerin daha bağımsız ve akıllı hale gelmesi bekleniyor. Ayrıca, insanlarla daha doğal bir şekilde etkileşime girebilecekleri ve daha etik bir yapıya sahip olacakları düşünülüyor.

Bununla birlikte, yapay zeka ajanlarının topluma zarar vermemesi için etik kuralların ve yasal düzenlemelerin belirlenmesi kritik önem taşıyor. Şeffaflık, güvenlik ve etik ilkeler doğrultusunda geliştirilen yapay zeka ajanları, gelecekte hayatımızı daha da kolaylaştırabilir.

Sonuç olarak araştırmalarımdan anladığım kadarıyla yapay zeka ajanları, günümüzün en heyecan verici teknolojilerinden biri olarak birçok sektörde büyük dönüşümler sağlıyor ve daha ötesini de yapacak gibi. Sağlıktan ulaşıma, eğitimden güvenliğe kadar birçok alanda bu sistemlerden bireysel kullanıcılar olarak zaten yararlanıyormuşuz. Ancak bu gelişmelerin etik ve güvenlik boyutları da göz önünde bulundurulmakta fayda olduğunu düşünüyorum. Yine de doğru kullanıldığında, yapay zeka ajanları insan hayatını kolaylaştıran, daha verimli ve güvenli bir dünya yaratmaya yardımcı olabilir. Önümüzdeki yıllarda, bu teknolojinin nasıl evrileceğini görmek için sabırsızlanıyorum.

Buraya kadar okuduğun için teşekkürler.

Bunu beğendiysen ve diğer içeriklerimden de haberdar olmak istersen clap butonuna tıklamayı ve abone olmayı unutma.

Teşekkür ederim.

Selin.

Artificial Intelligence and Energy Consumption: The Hidden Cost of Smart Technology

 

You can think of artificial intelligence (AI) like a human brain, but a super powerful one! Like a child learning something new, AI processes large amounts of data, analyzes it and learns certain patterns. There’s a lot of math, statistics and complex algorithms involved. In particular, what we call deep learning improves itself by repeatedly performing calculations on huge data sets. This process requires very large and powerful computers.

For example, when you ask an AI model, “Is this a cat?”, the model has analyzed thousands or even millions of cat photos and learned every detail. It guesses by looking at things like the shape of an eye, an ear, the length of a whisker. But here’s the magic: It takes a lot of computing power to do this!

Artificial intelligence (AI) is entering more and more into our lives every day. From voice assistants on phones to the shows Netflix recommends to us, from Google’s search results to Tesla’s self-driving cars, AI is everywhere. But does having this incredible technology come at a price? Yes, it comes at a big price: Energy consumption!

Although we don’t realize it in everyday life, AI models consume huge amounts of energy when they run. But why is there such a huge energy demand? Where does it come from and what steps are being taken to reduce consumption? Let’s explore this topic in its simplest yet detailed form.

How Does Artificial Intelligence Work?

I mentioned that we can think of AI as a human brain, but it’s actually a much faster version that can do big calculations. AI is actually a set of algorithms that analyze data and try to learn certain patterns. This is done through methods such as machine learning and deep learning.

• Machine learning: The process of teaching computers to make decisions by showing them examples.
• Deep learning: A more sophisticated version uses artificial neural networks that mimic the neural networks in the human brain.

Real Life Examples:

• Google Photos automatically separates “tree” photos from the images in the album.
• Spotify gives you new recommendations based on the songs you listen to.
• Tesla’s autopilot system makes instant decisions by detecting traffic signs and pedestrians.

Why does it consume so much energy?

AI’s energy consumption is based on several reasons:

1. Big Data and Big Computing: AI models process millions or even billions of parameters. To do this, specialized hardware such as GPUs (Graphics Processors) or TPUs (Tensor Processors) are used. But these devices consume significant power while continuously computing.
2. Model Training is Very Difficult: Training an AI model is a process that sometimes takes thousands of hours. Google’s GPT-3, a language model, consumed about 10 gigawatt hours of energy to train. This is equivalent to the electricity consumed by a European city for several days!
3. Data Centers: There are huge data centers running behind AI. The huge server farms of companies such as Facebook and Google run millions of computers that consume significant amounts of electricity. And because these machines overheat, extra energy is needed to cool them down.

Where, How and Through What Means Is This Energy Sourced?

So, where does AI get this energy?

1. Fossil Fuels: Unfortunately, most of the world’s electricity still comes from fossil fuels such as coal, natural gas and oil. These emit carbon, contributing to climate change.
2. Renewable Energy: Giant companies such as Google and Microsoft have started to power their data centers with wind and solar energy. However, this is not yet enough to power all systems.
3. Private Electricity Infrastructures: Big tech companies sometimes build their own private power plants or make deals directly with green energy suppliers.
4. Alternative Cooling Technologies: Data centers are sometimes built near the poles or underwater to reduce cooling costs.

What is being done to reduce energy consumption?

The answer to this question actually depends on work in several different areas:

1. More Efficient Artificial Intelligence Algorithms: Scientists are looking for ways to make AI work with less computation. Building small but smart models is an important goal.
2. Hardware Improvements: A new generation of chips (e.g. Apple’s M-series chips or Google’s specialized TPUs) can do the same job with less energy consumption.
3. Green Data Centers: Data centers are trying to use less energy by improving cooling technologies. Microsoft even tested the idea of placing its data centers under the ocean! Because water has a natural cooling effect.
4. Edge Computing: Normally, for an AI process, data has to travel to and from large data centers. But now solutions are being developed for AI to work on the device. For example, some commands from Apple’s Siri or Google Assistant are run entirely on the phone, so there is no need to go back and forth to the data center.

Who is Taking What Steps?

Big tech companies, universities and researchers are working to solve this problem. Here are a few examples:

• Google: Since 2017, it has been running the “AI for Good” program to make its AI models more efficient and is working towards 100% renewable energy in its data centers.
• Microsoft: aims to be carbon negative by 2030, meaning it will remove more carbon from the atmosphere than it produces.
• Tesla: Autonomous vehicles drive using artificial intelligence. Tesla has developed its special “Dojo” chip to make these processes more efficient.
• Research Institutes: Universities such as MIT and Stanford are working on AI models that consume less energy.

The Most Common Artificial Intelligence Models and Their Uses

There are many models of AI used in different fields. Here are some of the most common ones and their uses:

GPT (Generative Pre-trained Transformer) Series

• Where Used: Chatbots, copywriting, translation, code generation
• Example: ChatGPT, Google Bard

CNN (Convolutional Neural Networks)

• Where Used: Image recognition, face recognition, x-ray analysis in healthcare
• Example: Facebook’s face recognition system, anomaly detection in MRI scans

RNN (Recurrent Neural Networks) & LSTM (Long Short-Term Memory)

• Where Used: Voice recognition, language modeling, prediction systems
• Example: Siri, Google Assistant, music recommendation systems

DQN (Deep Q-Networks) and Reinforcement Learning

• Where Used: Game playing AIs, robotic systems
• Example: AlphaGo, Tesla’s self-driving car system

Transformers

• Where Used: Natural language processing, large-scale data analytics
• Example: Google Translate, text summarization systems

Artificial intelligence is a tremendous technology, but energy consumption is a big problem. Fortunately, thanks to more efficient algorithms, renewable energy and hardware advancements, we are working to overcome these problems. It is very likely that we will see greener, more energy-efficient AI systems in the coming years. But still, like any technology, AI comes at a price — both in terms of energy and environmental impact!

So, do you think AI is really worth spending so much energy on? I’d love to hear your opinion in the comments.

I hope you found this article useful! If you appreciate the information provided, you have the option to support me by Buying Me A Coffee! Your gesture would be greatly appreciated!

Thank you so much for reading.

If you found it valuable, hit the clap button 👏 and consider following me for more such content.

Selin.