In contrast, traditional AI requires ongoing human input to function, whether it’s to provide data, set parameters or provide instructions. The ability of agentic AI to work independently is what sets it apart, enabling it to perform more complex, multi-step tasks on its own....
Artificial intelligence (AI) has become a hot-button topic in recent months because of its potential to revolutionize how we live and work. Because of this, there is much to learn about it. In this post, we’ll explore the basics of artificial intelligence, including the different types of...
Stop-button problem.An AGI system will actively resist being stopped or shut off to achieve its programmed objective. This is like reward hacking because it prioritizes the reward from the literal goal over the preferred outcome. For example, if an AI system's primary objective is to make pap...
Agentic AI is an AI system that acts autonomously, adapts in real time, and solves multi-step problems based on context and objectives. They are built of multiple AI agents that leverage large language models (LLMs) and complex reasoning. This enables them to have enhanced decision-making ...
In machine learning, an epoch is a complete iteration through the entire training dataset during model training. It’s a critical component in the training process as it enables the model to update its parameters based on the optimization algorithm and loss function used to minimize the error. ...
What Is AI Model Training? At its core,an AI modelis both a set of selected algorithms and the data used to train those algorithms so that they can make the most accurate predictions. In some cases, a simple model uses only a single algorithm, so the two terms may overlap, but the ...
What is machine learning (ML)? ML is a focus area of AI that uses data and algorithms to imitate the way humans learn, improving the accuracy of its answers over time. ML relies on a decision process to make a prediction or classify information, an error function that evaluates the accura...
Continuous Improvement– Over time, the AI becomes better at achieving its objective through exploration and exploitation. Reinforcement learning is commonly used in robotics, self-driving cars, game-playing AI (e.g., AlphaGo), and financial trading systems, where decision-making under uncertainty is...
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A field of AI that focuses on the interaction between computers and humans through natural language. The ultimate objective of NLP is to enable computers to understand, interpret, and generate human languages in a way that is both meaningful and useful. Check out our Introduction to Natural Langu...