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Open vs Closed-source AI
Open-source and closed-source AI represent two different approaches to the development and distribution of artificial intelligence technologies. Here are the key differences between them: Open-source AI Accessibility: Open-source AI software is freely available to anyone. Users can access, modify, and distribute the source code without restrictions. Collaboration: It typically involves a community-based development model. Developers…
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Synthetic data generation in AI
Synthetic data generation in AI is a crucial technique that plays a pivotal role in various domains and applications. It involves the creation of artificial data that closely resembles real-world data, even though it is not derived from actual observations or measurements. This synthetic data is generated using a range of sophisticated algorithms, statistical models,…
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AI agents: description and examples
AI agents are diverse and sophisticated tools in the field of artificial intelligence, each with unique characteristics and applications. Reactive agents operate based on current inputs without learning from past experiences, making them suitable for simple tasks like basic robotics or video game decision-making. Model-based agents, equipped with an internal model of the environment, excel…
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LLM Models: A Closer Look
We revisit the topic of Large Language Models (LLM), which is a critical subject for understanding the foundation of artificial intelligence (AI), and we examine it in more technical detail without exceeding a basic level of understanding. Large Language Models (LLM) are advanced artificial intelligence systems created to understand and generate text in a manner…
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Multimodal AI
Multimodal AI is a branch of artificial intelligence (AI) that deals with the handling and analysis of data from multiple modalities or sources, such as text, images, sound, video, tactile sensations, and more, to develop more complex and interconnected machine learning models and systems. The concept of multimodality focuses on integrating and concurrently understanding information…
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Other AI models and architectures
In the field of artificial intelligence, in addition to Large Language Models (LLMs), there are various other types of models and architectures used for different purposes. Here are a few examples: Convolutional Neural Networks (CNNs): These models are specialized in processing images and are often used in computer vision applications. CNNs have been effective in…
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Large Language Models
Large Language Models (LLMs) represent a distinct category of artificial intelligence models specialized in natural language processing. These models are built on the transformer architecture, a significant innovation in the field of neural networks. A representative example of an LLM is GPT-3/3.5/4, developed by OpenAI. The training process of an LLM involves exposing the model…
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Disruptive Innovation in the Era of Artificial Intelligence
In the field of business theory, disruptive innovation represents the process of introducing a new technology, product, or service that can create a new market or penetrate an existing market at the bottom segment, ultimately affecting and transforming established companies, products, and alliances. This concept, popularized by American scholar Clayton Christensen and his collaborators starting…
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The Retrospective of 2023 in AI
2023 was the year when artificial intelligence continued to expand its influence across various aspects of our lives, proving to be a captivating period full of innovation. In a dynamic landscape, we witnessed an explosion of significant events and remarkable technological advancements, impacting sectors such as technology, AI art, chatbots, and more. This content aims…
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Artificial General Intelligence: Defining Features and the Future
The concept of Artificial General Intelligence (AGI) has long been a staple in science fiction literature, often portrayed as a super intelligent artificial intelligence (AI) capable of significantly surpassing human abilities. While AGI remains a futuristic idea, recent developments in generative AI have sparked discussions about how close we may be to achieving it. AGI…



