applications

across industries. Traditional engineering domains are not any exception. Previously two years, I’ve been constructing LLM-powered tools with engineering domain experts. Those are process engineers, reliability engineers, cybersecurity analysts, etc., who spend most of...

with a little bit of control and assurance of security. Guardrails provide that for AI applications. But how can those be built into applications? A couple of guardrails are established even before application coding...

have entered the world of computer science at a record pace. LLMs are powerful models able to effectively performing a wide selection of tasks. Nonetheless, LLM outputs are stochastic, making them unreliable. In...

I that almost all corporations would have built or implemented their very own Rag agents by now. An AI knowledge agent can dig through internal documentation — web sites, PDFs, random docs — and...

Table of Contents Introduction It’s infrequently that you simply hear the Ruby language mentioned when discussing AI. Python, after all, is the king on this world, and for good reason. The community has coalesced across the language....

AI still seems like a cutting-edge breakthrough, despite the fact that it’s been around for many years. Machine learning has quietly powered serps, suggestion algorithms, and speech recognition for years – but only recently has...

Imagine a future where drones operate with incredible precision, battlefield strategies adapt in real-time, and military decisions are powered by AI systems that repeatedly learn from each mission. This future isn't any longer a...

Artificial intelligence (AI) fundamentally transforms how we live, work, and communicate. Large language models (LLMs), akin to GPT-4, BERT, Llama, etc., have introduced remarkable advancements in conversational AI, delivering rapid and human-like responses. Nonetheless,...