Blog Archive

Making AI Smarter with Retrieval-Augmented Generation

Large language models are quite prevalent in today’s technological world. They can answer questions, generate text, and simulate human-like conversation. But for all their power, they suffer from a well-known flaw: they don’t know what they don’t know.  Once trained, an LLM can’t access new information unless it’s retrained or fine-tuned. Both of which are costly and time-consuming processes. This is where Retrieval-Augmented Generation (RAG) comes in. RAG is an architecture that marries the reasoning power of language models with the precision of external knowledge retrieval. In plain terms: it lets AI look things up before answering. And that simple shift is a game changer. 
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How AI Helped Predict Wildfire Paths in California

In recent years, wildfires have become more frequent, intense, and unpredictable. In California alone, billions of dollars in damage and dozens of lives are lost annually due to fast-moving fires that defy traditional modeling. But now, artificial intelligence is emerging as a powerful tool in the fight against these natural disasters. It offers real-time predictions, smarter resource allocation, and a new level of situational awareness.
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How Autonomous Agents Could Support Mission-Critical Workflows

Throughout many industries, including the government, one concept is rapidly gaining traction: autonomous agents. These AI-powered systems go beyond reactive responses—they reason, plan, and act in complex environments, often without continuous human input. For organizations managing mission-critical workflows, autonomous agents represent both a transformative opportunity and a strategic frontier.
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How AI Is Changing the Everyday Lives of Software Developers

The world of software development has always been defined by evolution and innovation. From assembly languages to cloud-native services, developers have ridden successive waves of innovation. But few waves have been as transformative as the rise of artificial intelligence. Today, AI is not just augmenting the work of software developers; it's actively reshaping how they think, code, and collaborate. And this revolution is not limited to the private sector either; federal agencies and contractors are already feeling the effects.
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AI Hardware Innovation: Beyond GPUs and TPUs

As artificial intelligence continues to grow in complexity and influence, the demand for more specialized hardware is rapidly increasing. While GPUs (Graphics Processing Units) and TPUs (Tensor Processing Units) have dominated the AI landscape, a new wave of hardware innovations is emerging to push the boundaries of performance, efficiency, and capability.
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Neuromorphic Computing: Mimicking the Brain Beyond Neural Networks 

As you may be aware, artificial intelligence has made rapid progress. But as we push the limits of traditional architectures, researchers are exploring fundamentally new ways to build intelligent systems, ones that go beyond software simulations of the brain and instead reimagine the hardware itself. Welcome to the world of neuromorphic computing, where machines are designed to operate more like our brains: fast, efficient, adaptive, and capable of complex learning. 
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