March 2026

Concept learning is a form of supervised machine learning that operates on knowledge bases in description logics. State-of-the-art concept learners often rely on an iterative search through a countably infinite concept space. In each iteration, they retrieve instances of candidate solutions to select the best concept for the next iteration. While simple learning problems might require a few dozen instance retrieval calls to find a fitting solution, complex learning problems might necessitate thousands of calls. We alleviate the […]

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Activation steering methods enable inference-time control of large language model (LLM) behavior without retraining, but current approaches face a fundamental trade-off: sample-efficient methods suboptimally capture steering signals from labeled examples, while methods that better extract these signals require hundreds to thousands of examples. We introduce COLD-Steer, a training-free framework that steers LLM activations by approximating the representational changes that would result from gradient descent on in-context examples. Our key insight is that the effect of fine-tuning on a […]

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Anthropic and the Pentagon This piece by Bruce Schneier and Nathan E. Sanders is the most thoughtful and grounded coverage I’ve seen of the recent and ongoing Pentagon/OpenAI/Anthropic contract situation. AI models are increasingly commodified. The top-tier offerings have about the same performance, and there is little to differentiate one from the other. The latest models from Anthropic, OpenAI and Google, in particular, tend to leapfrog each other with minor hops forward in quality every few months. […] […]

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Welcome to HackerNoon’s Projects of the Week, where we spotlight standout projects from the Proof of Usefulness Hackathon, HackerNoon’s competition designed to measure what actually matters: real utility over hype. n n Each week, we’ll highlight projects that demonstrate clear usefulness, technical execution, and real-world impact – backed by data, not buzzwords. This week, we’re excited to share three projects that have proven their utility by solving concrete problems for real users: Black Market SSP, CutePetPal, and SudoDocs. :::tip […]

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How are you, hacker? 🪐 What’s happening in tech today, March 6, 2026? The HackerNoon Newsletter brings the HackerNoon homepage straight to your inbox. On this day, Michelangelo Strikes in 1992, and we present you with these top quality stories. From Prompt Injection Still Beats Production LLMs to I Gave 5 Teams the Same Dashboard – Only 1 Made a Decision With It, let’s dive right in. Your AI Designer Has Never Disagreed With You By @tanyadonska [ […]

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The surge in reinforcement learning (RL) applications gave rise to diverse supporting technology, such as RL frameworks. However, the architectural patterns of these frameworks are inconsistent across implementations and there exists no reference architecture (RA) to form a common basis of comparison, evaluation, and integration. To address this gap, we propose an RA of RL frameworks. Through a grounded theory approach, we analyze 18 state-of-the-practice RL frameworks and, by that, we identify recurring architectural components and their relationships, […]

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