Deep Dives

Can AI Solve Failures in Your Supply Chain?

chain is a goal-oriented network of processes and stock points that delivers finished goods to stores. Imagine a luxury fashion retailer with a central distribution chain that delivers to stores worldwide (the USA, Asia-Pacific, and EMEA) from a...

The Strangest Bottleneck in Modern LLMs

Introduction are currently living in a time where Artificial Intelligence, especially Large Language models like ChatGPT, have been deeply integrated into our each day lives and workflows. These models are able to quite a...

AI in Multiple GPUs: Point-to-Point and Collective Operations

is an element of a series about distributed AI across multiple GPUs: Part 1: Understanding the Host and Device Paradigm Part 2: Point-to-Point and Collective Operations (this text) Part 3: How GPUs Communicate Part 4: Gradient Accumulation...

The Death of the “Every thing Prompt”: Google’s Move Toward Structured AI

been laying the groundwork for a more structured option to construct interactive, stateful AI-driven applications. One in all the more interesting outcomes of this effort was the discharge of their latest Interactions API...

Why Is My Code So Slow? A Guide to Py-Spy Python Profiling

frustrating issues to debug in data science code aren’t syntax errors or logical mistakes. Quite, they arrive from code that does exactly what it's presupposed to do, but takes its sweet time doing...

Mechanistic Interpretability: Peeking Inside an LLM

Intro tips on how to examine and manipulate an LLM’s neural network. That is the subject of mechanistic interpretability research, and it could answer many exciting questions. Remember: An LLM is a deep artificial neural...

Construct Your Own Custom LLM Memory Layer from Scratch

is a fresh start. Unless you explicitly supply information from previous sessions, the model has no built‑in sense of continuity across requests or sessions. This stateless design is great for parallelism and safety,...

Plan–Code–Execute: Designing Agents That Create Their Own Tools

today deal with how multiple agents coordinate while choosing tools from a predefined toolbox. While effective, this design quietly assumes that the tools required for a task are known prematurely. Let’s challenge that assumption...

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