Blog Posts

Feature processing has moved from explicit to latent to implicit. Hand‑engineered descriptors → supervised deep latents → implicit functions that are the scene/program (e.g., NeRFs, world models, in‑context learners).

In today’s world, our fast-paced lives rarely allow us the luxury of remembering every detail from important meetings—or those long Dungeons & Dragons sessions. As a multi-tasker with a notoriously poor memory when it comes to meetings and collaborative gaming sessions, I set out to build a system that not only captures audio on a per-process basis but also transforms it into structured, actionable insights. This post outlines our progress in building a native Windows audio capture engine using Rust and wasapi‑rs, and how it feeds into a real-time streaming pipeline for transcription, summarization, and even diarization.

Below is a comprehensive blog post that covers the release of Llama 4 on SageMaker JumpStart, structured with an overview of implementation details, key features, and best practices. This blog builds on information provided in the AWS Blog and insights from the Meta Blog.

The digital assistants we interact with today—like Alexa and Google Assistant—offer a glimpse into a convenient, automated future. However, their capabilities remain limited by rigid command structures and a shallow repository of pre-approved skills. What if these assistants were empowered to install their own plugins? Imagine a system where your voice assistant not only understands your requests but also autonomously expands its range of abilities by tapping into a marketplace of dynamic, modular plugins. In this post, we explore why current voice assistants fall short and how large language models (LLMs) can transform them into truly agentic AI entities.

A comprehensive conceptual blueprint for a blog post that combines practical guidance on developing an agent that intelligently generates Terraform code with insights into leveraging your AWS account’s structure and integrating Model Context Protocol (MCP) servers to supply up-to-date tooling data.