3 posts tagged with "llm"

✨ What you'll learn (tl;dr) In ~12 minutes you'll see how to deploy Microsoft's BitNet 1.58-bit quantized LLM on AWS Lambda, the container-based architecture, and performance benchmarks across different memory configurations using the microsoft/bitnet-b1.58-2B-4T model.

Big idea: 1.58-bit quantization enables LLM deployment on Lambda's CPU infrastructure. At ~1.1GB, the model fits within Lambda's constraints for serverless AI inference.

As large language models (LLMs) evolve from passive responders into autonomous agents that can reason, plan, and act—welcome to the age of Agentic AI. These systems don't just generate answers; they browse the web, execute scripts, send emails, and even orchestrate other agents. And with that autonomy comes an entirely new class of cybersecurity threats.

The OWASP Agentic AI: Threats and Mitigations report is the first of its kind to lay out a structured threat model tailored to the unique risks introduced by LLM-powered agents. From memory poisoning and cascading hallucinations to identity spoofing and rogue agents—this is the new frontline of AI security.

The Emergence of Generative AI and Large Language Models​

The world has witnessed a meteoric rise in the use of artificial intelligence (AI) technologies over the past few years, with generative AI and large language models (LLMs) standing at the forefront. Generative AI, which includes the likes of LLMs, can generate creative and unique content, ranging from artwork to complex textual narratives. The idea of AI systems autonomously producing human-like content has transformed the AI landscape, opening up a plethora of possibilities.