📌 Technical Origin of OpenML - A Quantum Physics Problem
2026-01-26
2026-02-04
The conceptual foundation of OpenML dates all the way back to 2013 when a college boy in Physics major was reading and implementing the Matrix Numerov Method for Solving Schrödinger Equation
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PyTorch
To install PyTorch on ny Apple Silicon Mac, e.g. M5, we don’t need a special version. PyTorch natively supports Apple’s GPU acceleration out of the box using Metal Performance Shaders (MPS).
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Structured Outputs
"Structured Outputs" itself has largely become the standard industry-wide term adopted by open-source libraries, academic papers, and competing cloud providers (such as Google Cloud Vertex AI, Anthropic integrations, and AWS Bedrock). It refers broadly to the developer pattern of supplying a schema (e.g., JSON Schema, Pydantic model, or Zod schema) to guarantee an API or local runner returns valid, structured data instead of free-form text.
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Extensibility Ecosystems
2026-09-05
2026-09-06
Systems such as ChatGPT Plugins and Gemini Extensions allows OpenAI and Gemini to connect to external apps and services to retrieve real-time information and perform actions, allowing them to interact directly with Google Workspace (Docs, Drive, Gmail), Google Maps, Google Flights, Google Hotels, and YouTube.
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Why is AI Deeply-Seated with Philosophy and Language?
2025-05-29
2026-09-04
AI is not just a consumer of linguistic data; it is a producer of new philosophical questions. It forces us to be more precise about what we mean by "meaning," "understanding," and "thought," turning centuries of abstract debate into a pressing, practical challenge.
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KV Cache
Specifically created to solve the massive memory bottleneck and inefficiency of serving Large Language Models in production, vLLM at its core resolves the problem of LLM serving and inferencing. Before vLLM, the bottleneck in serving LLMs wasn't just the model weights themselves, but the KV Cache (Key-Value Cache) - the memory required to store the attention context for generating tokens sequentially. This posts helps us systematically learn KV cache.
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MQTT Essentials
In the rapidly evolving landscape of IoT, MQTT has emerged as the de facto standard protocol for data exchange. This post on MQTT is designed to equip decision-makers, solution architects, and IoT professionals with a strategic and practical understanding of MQTT and how to execute it for scalable, reliable, and seamless data movement. Delve into how MQTT can help organization overcome the challenges other IoT protocols cannot address with features such as persistent sessions, retained messages, Last Will and Testament (LWT), Quality of Service (QoS) levels, and more. After reading this guide, you'll be ready to use MQTT to optimize connectivity and lay the proper data foundation to enable any IoT or IIoT use case.
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Introduction to Audio Data
In signal processing, sampling is the reduction of a continuous-time signal to a discrete-time signal. A common example is the conversion of a sound wave to a sequence of “samples”. A sample is a value of the signal at a point in time and/or space; this definition differs from the term’s usage in statistics, which refers to a set of such values
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