February 28, 2024 - AI JetTech

AI and Society

How does AI affect the society? Artificial intelligence (AI) has woven its threads through the fabric of society, subtly altering the canvas upon which our lives are painted. Its influence extends far beyond mere technological advancement, shaping the very structure of our job market, societal norms, and ethical responsibilities. Impact of AI on employment The advent of AI has sparked a transformation in employment, a metamorphosis that is both promising and challenging. On one hand, AI automates mundane tasks, liberates human intellect for more creative pursuits, and pioneers new professions. Imagine a world where the tedium

Interpretability and Explainability

In the realm of artificial intelligence (AI), two terms frequently surface, often used interchangeably yet distinct in their nuances: interpretability and explainability. These concepts serve as the bridge connecting human comprehension and machine decision-making, ensuring that AI’s logic isn’t locked away in an impenetrable black box. What is Interpretability? Imagine you’re a detective, and each AI model is a suspect with an alibi. Interpretability is the clarity of that alibi. It’s about how easily one can comprehend why the model made a particular decision. This does not necessarily mean knowing the exact mathematical operations (though that

Model Deployment

Deploying AI Models in Production Deploying an AI model into production is the process of transitioning the model from a development or testing phase to a live environment where it can start providing value by making predictions or decisions based on new data. This step is crucial for realizing the practical benefits of the model’s capabilities. Key Considerations for Successful Deployment Successful deployment hinges on meticulous planning and execution. Some crucial things to keep in mind are as follows: Integration with Existing Systems Integrating an AI model with existing systems can be seen as a bridge-building

Policy Gradient Methods

Policy Gradient Methods Reinforcement Learning Delving into the realm of reinforcement learning, policy gradient methods stand out as a strategy that directly tweaks the policy, mapping states to actions, to enhance performance. Unlike methods that estimate value functions, policy gradient methods adjust the policy parameters (θ) by ascending along the gradient of the expected reward. This approach can be likened to climbing a mountain, feeling the slope underfoot and taking steps upwards, always aiming for the peak where the reward is maximized. Unveiling Policy Optimization At the core of policy gradient methods lies policy optimization, aiming

Day: February 28, 2024

AI and Society

Interpretability and Explainability

Model Deployment

Policy Gradient Methods

AI JetTech