March 2026

When X open-sourced their recommendation algorithm, most people skimmed the announcement and moved on. That was a mistake. I’ve been building XPilot, a tool that automates X growth for founders, which means I’ve spent a lot of time inside this codebase trying to understand what the platform actually rewards. And the code tells you, with unusual clarity, what’s going on under the hood. For founders trying to build an organic presence, it changes the calculus on almost every […]

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AI is dominating everybody’s consciousness in 2026 more than it did in 2025 and the year before that. With people fearing for their future livelihoods and technology behemoths salivating at the prospects of future super profits that make today’s immense earnings seem like peanuts, the world appears to be waiting with bated breath for something hugely extraordinary to occur and change their lives in ways they can’t even begin to imagine. On the ground, however, AI is a […]

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Most crypto founders treat compliance as a cost or a constraint, but in regulated markets it functions as a competitive capability. Companies that build compliance into product architecture from day one scale faster across jurisdictions and onboard institutional partners more easily. Regulatory frameworks like MiCA, the FATF Travel Rule, and licensing regimes in Singapore or the Gulf are acting as selection mechanisms that filter out poorly structured operators. Compliance built as infrastructure compresses timelines for expansion, integration, and […]

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LM-based agents excel when given high-level action APIs but struggle to ground language into low-level control. Prior work has LLMs generate skills or reward functions for RL, but these one-shot approaches lack feedback to correct specification errors. We introduce SCALAR, a bidirectional framework coupling LLM planning with RL through a learned skill library. The LLM proposes skills with preconditions and effects; RL trains policies for each skill and feeds back execution results to iteratively refine specifications, improving robustness […]

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Scientific machine learning (SciML) is increasingly applied to in-field processing, controlling, and monitoring; however, wide-area sensing, real-time demands, and strict energy and reliability constraints make centralized SciML implementation impractical. Most SciML models assume raw data aggregation at a central node, incurring prohibitively high communication latency and energy costs; yet, distributing models developed for general-purpose ML often breaks essential physical principles, resulting in degraded performance. To address these challenges, we introduce EPIC, a hardware- and physics-co-guided distributed SciML framework, […]

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Early AI development relied heavily on scaling neural networks without fully understanding how they worked internally. Researchers are now turning to the spectral properties of linear algebra—particularly eigenvalues and eigenvectors—to better interpret how neural networks process information. By studying the geometry of latent space and identifying meaningful circuits inside transformer models, scientists can isolate and enhance specific capabilities such as reasoning or coding. Hardware innovations are also emerging to accelerate these complex calculations. Ultimately, spectral techniques like normalization […]

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As developers, we often need to tweak screenshots – blur out sensitive info, add annotations, or even change the text. But have you ever wanted to replace a word in a screenshot, and have it look exactly like the original? Same font, same size, same color, same style? I did, and that’s why I built Screenshot Editor – a free, open-source web app that does exactly that. In this article, I’ll walk you through the journey, the challenges, and the […]

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