DDD Blog

Our thoughts and insights on machine learning and artificial intelligence applications

Welcome to Digital Divide Data’s (DDD) blog, fully dedicated to Machine Learning trends and resources, new data technologies, data training experiences, and the latest news in the areas of Deep Learning, Optical Character Recognition, Computer Vision, Natural Learning Processing, and more.

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Best Practices for Synthetic Data Generation in Generative AI
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Best Practices for Synthetic Data Generation in Generative AI

In this blog, we’ll break down the best practices for synthetic data generation in generative AI and dive into the challenges and best practices that define its responsible use. We’ll also examine real-world use cases across industries to illustrate how synthetic data is being leveraged today. 

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Prompt Engineering for Defense Tech: Building Mission-Aware GenAI Agents
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Prompt Engineering for Defense Tech: Building Mission-Aware GenAI Agents

This blog explores how prompt engineering for defense tech is becoming the foundation of national security. It offers a deep dive into techniques for embedding context, aligning behavior, deploying robust prompt architectures, and ensuring outputs remain safe, explainable, and operationally useful, and discusses real-world case studies.

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Semantic vs. Instance Segmentation for Autonomous Vehicles
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Semantic vs. Instance Segmentation for Autonomous Vehicles

This blog explores the role of Semantic and Instance Segmentation for Autonomous Vehicles, examining how each technique contributes to vehicle perception, the unique challenges they face in urban settings, and how integrating both can lead to safer and more intelligent navigation systems.

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Real-World Use Cases of RLHF in Generative AI
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Real-World Use Cases of RLHF in Generative AI

This blog explores real-world use cases of RLHF in generative AI, highlighting how businesses across industries are leveraging human feedback to improve model usefulness, safety, and alignment with user intent. We will also examine its critical role in developing effective and reliable generative AI systems and discuss the key challenges of implementing RLHF.

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How to Conduct Robust ODD Analysis for Autonomous Systems
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How to Conduct Robust ODD Analysis for Autonomous Systems

This blog provides a technical guide to conducting robust ODD analysis for autonomous driving, detailing how to define, structure, validate, and evolve an Operational Design Domain using formal taxonomies, scenario-based testing, coverage metrics, and integration to ensure the safe and scalable deployment.

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Bias in Generative AI: How Can We Make AI Models Truly Unbiased?
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Bias in Generative AI: How Can We Make AI Models Truly Unbiased?

This blog explores how bias manifests in generative AI systems, why it matters at both technical and societal levels, and what methods can be used to detect, measure, and mitigate these biases. It also examines what organizations can do to mitigate bias in Gen AI and build more ethical and responsible AI models.

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How GenAI is Transforming Administrative Workflows in Defense Tech

How GenAI is Transforming Administrative Workflows in Defense Tech

In this article, we explore how GenAI is transforming administrative operations in defense tech, We’ll also examine the key challenges it addresses, the critical role of secure AI components like RAG and red teaming, and how organizations provide the data infrastructure that powers this new era of defense innovation.

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Scaling Generative AI Projects: How Model Size Affects Performance & Cost 
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Scaling Generative AI Projects: How Model Size Affects Performance & Cost 

This blog breaks down how generative AI models differ in capability, how they scale in enterprise environments, and what trade-offs organizations must consider. We’ll also examine how modern approaches such as Retrieval-Augmented Generation (RAG), fine-tuning, and Reinforcement Learning with Human Feedback (RLHF) influence the overall performance and cost. 

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