A Beginner-Friendly Guide to NLP Token Classification: NER, POS Tagging & Chunking Explained
In today’s world, computers need to understand human language to perform tasks like chatbots, search engines, and text analysis. This is… Continue reading on Medium »
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EU AI Act compliance checklist for AI engineering teams
The EU AI Act deadline for high-risk AI systems is August 2, 2026. If you are building AI agents, here is what your engineering team needs to do. I put together a practical checklist based on Articles 9-15. Full version with checkboxes on GitHub: eu-ai-act-checklist The Articles That Matter for Engineers Article 9 - Risk Management You need a documented risk management system. Not a PDF that sits in a drawer - an active process that identifies risks, tests mitigations, and updates as the system evolves. Article 10 - Data Governance Training data needs documentation: sources, preparation methods, bias analysis. If your agent accesses external data at runtime, you need to document that too. Article 11 - Technical Documentation Annex IV lists everything you need to document. Architecture, alg
From isolated alerts to contextual intelligence: Agentic maritime anomaly analysis with generative AI
This blog post demonstrates how Windward helps enhance and accelerate alert investigation processes by combining geospatial intelligence with generative AI, enabling analysts to focus on decision-making rather than data collection.
AI Is Insatiable
While browsing our website a few weeks ago, I stumbled upon “ How and When the Memory Chip Shortage Will End ” by Senior Editor Samuel K. Moore. His analysis focuses on the current DRAM shortage caused by AI hyperscalers’ ravenous appetite for memory, a major constraint on the speed at which large language models run. Moore provides a clear explanation of the shortage, particularly for high bandwidth memory (HBM). As we and the rest of the tech media have documented, AI is a resource hog. AI electricity consumption could account for up to 12 percent of all U.S. power by 2028. Generative AI queries consumed 15 terawatt-hours in 2025 and are projected to consume 347 TWh by 2030. Water consumption for cooling AI data centers is predicted to double or even quadruple by 2028 compared to 2023. B
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HP’s flagship Omen Max 45L with an RTX 5090 is on sale for $1,000 off — get a top-shelf 4K gaming PC with 64GB DDR5 and 4TB SSD for $5,499
HP’s flagship Omen Max 45L with an RTX 5090 is on sale for $1,000 off — get a top-shelf 4K gaming PC with 64GB DDR5 and 4TB SSD for $5,499
Inside Omega
This is a philosophical thought experiment which aims to explore what I consider to be the crux of many alignment problems: That of the unrescuability of moral internalism , which basically says we have not been able to rescue the philosophical view that a necessary, intrinsic connection exists between moral judgments and motivation. If one could rescue moral internalism, in theory, they would have a perfectly good argument for any rational self-interested intelligence to not engage in broad scale moral harm. Therefore I think it is a linchpin meta-philosophical challenge. I don't claim to have a theorem, but I believe that one potential domain worth investigating is arguments which induce indexical uncertainty in an agent. Essentially, forms of leveraging undecidability to cause an agent
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