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Every major economy is staring at the same problem right now. Artificial intelligence is consuming electricity at a pace that grids were never designed to handle. In the US, capacity market prices in PJM, the country’s largest grid operator, have risen more than tenfold in two years, with data-centre growth identified as a primary driver. […]
Training large language models on long sequences has a well-known problem: attention is expensive. The scaled dot-product attention (SDPA) at the core of every transformer scales quadratically Θ(N²) in both compute and memory with sequence length N. FlashAttention addressed this through IO-aware tiling that avoids materializing the full N×N attention matrix in high-bandwidth memory, reducing
There’s a pattern playing out inside almost every engineering organization right now. A developer installs GitHub Copilot to ship code faster. A data analyst starts querying a new LLM tool for reporting. A product team quietly embeds a third-party model into a feature branch. By the time the security team hears about any of it,
There’s a pattern playing out inside almost every engineering organization right now. A developer installs GitHub Copilot to ship code faster. A data analyst starts querying a new LLM tool for reporting. A product team quietly embeds a third-party model into a feature branch. By the time the security team hears about any of it,
In this tutorial, we explore Equinox, a lightweight and elegant neural network library built on JAX, and show how to use it. We begin by understanding how eqx.Module treats models as PyTrees, which makes parameter handling, transformation, and serialization feel simple and explicit. As we move forward, we work through static fields, filtered transformations such
In this tutorial, we implement an advanced Bayesian hyperparameter optimization workflow using Hyperopt and the Tree-structured Parzen Estimator (TPE) algorithm. We construct a conditional search space that dynamically switches between different model families, demonstrating how Hyperopt handles hierarchical and structured parameter graphs. We build a production-grade objective function using cross-validation inside a scikit-learn pipeline, enabling
In this tutorial, we build a pipeline on Phi-4-mini to explore how a compact yet highly capable language model can handle a full range of modern LLM workflows within a single notebook. We begin by setting up a stable environment, loading Microsoft’s Phi-4-mini-instruct in efficient 4-bit quantization, and then move step by step through streaming
Cybersecurity has always had a dual-use problem: the same technical knowledge that helps defenders find vulnerabilities can also help attackers exploit them. For AI systems, that tension is sharper than ever. Restrictions intended to prevent harm have historically created friction for good-faith security work, and it can be genuinely difficult to tell whether any particular
In this tutorial, we explore how to build a fully functional background task processing system using Huey directly, without relying on Redis. We configure a SQLite-backed Huey instance, start a real consumer in the notebook, and implement advanced task patterns, including retries, priorities, scheduling, pipelines, locking, and monitoring via signals. As we move step by
Drug discovery is one of the most expensive and time-consuming endeavors in human history. It takes roughly 10 to 15 years to go from target discovery to regulatory approval for a new drug in the United States. Most of that time is spent not in breakthrough moments, but in painstaking analytical work — sifting through
