Coding in public: with filament and the tall stack If you’re interested to take part in open source, coding in public is naturally something we do. Here is an opportunity to come along with me on my own path to do the same. n n I’ve been looking for a way to share what I’ve learnt in my time and for that to be useful, not just for you the reader, but also for me. At the beginning […]
We introduce Parallel Coordinated Reasoning (PaCoRe), a training-and-inference framework designed to overcome a central limitation of contemporary language models: their inability to scale test-time compute (TTC) far beyond sequential reasoning under a fixed context window. PaCoRe departs from the traditional sequential paradigm by driving TTC through massive parallel exploration coordinated via a message-passing architecture in multiple rounds. Each round launches many parallel reasoning trajectories, compacts their findings into context-bounded messages, and synthesizes these messages to guide the next […]
The promise of Artificial Intelligence has long been restricted by a single, critical challenge: connecting powerful Large Language Models (LLMs) to the messy, secure, and constantly evolving world of enterprise data and tools. Traditional methods relying on hardcoded integrations and proprietary plugins have proven to be fragile, difficult to scale, and rife with security risks. These limitations have kept AI systems locked in a “walled garden,” preventing them from becoming the truly context-aware, autonomous digital workers we envision. […]
Published on December 26, 2025 4:37 PM GMT A key risk factor for scheming (and misalignment more generally) is opaque reasoning ability. One proxy for this is how good AIs are at solving math problems immediately without any chain-of-thought (CoT) (as in, in a single forward pass). I’ve measured this on a dataset of easy math problems and used this to estimate 50% reliability no-CoT time horizon using the same methodology introduced in Measuring AI Ability to Complete […]
This is not an article delving into the details of AWS Secrets Manager or SSM Parameter Store, but a quick overview of how to use them to store secrets like API keys as I did in this project. https://github.com/avr2002/files-api/tree/main?embedable=true AWS Secrets Manager AWS Secrets Manager helps you to securely store, rotate, and manage sensitive information like API keys, database credentials, OAuth tokens, and other secrets. Instead of hardcoding credentials in your application code, you can store them in […]
The Jordan-Kinderlehrer-Otto (JKO) scheme provides a stable variational framework for computing Wasserstein gradient flows, but its practical use is often limited by the high computational cost of repeatedly solving the JKO subproblems. We propose a self-supervised approach for learning a JKO solution operator without requiring numerical solutions of any JKO trajectories. The learned operator maps an input density directly to the minimizer of the corresponding JKO subproblem, and can be iteratively applied to efficiently generate the gradient-flow evolution. […]
How are you, hacker? 🪐Want to know what’s trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. ## A Developer’s Guide to Building Next-Gen Smart Wallets With ERC-4337 — Part 2: Bundlers By @hacker39947670 [ 15 Min read ] Bundlers are the bridge between account abstraction and the execution layer. Read More. How Crypto Can Protect People from Currency Wars By @chris127 […]
Disclaimer While working as a project manager, I often heard comments like: “Why do we even need PMs? What do they actually do? They only talk and nothing more.” It’s a fairly common opinion. So I prepared an article about what PM can actually do (together with their team) and how impactful that work can be for a project. As we PMs and producers love — with numbers, tables and charts. There are three part about Art Pipeline, […]
Traditional methods for determining critical parameters are often influenced by human factors. This research introduces a physics-inspired adaptive reinforcement learning framework that enables agents to autonomously interact with physical environments, simultaneously identifying both the critical temperature and various types of critical exponents in the Ising model with precision. Interestingly, our algorithm exhibits search behavior reminiscent of phase transitions, efficiently converging to target parameters regardless of initial conditions. Experimental results demonstrate that this method significantly outperforms traditional approaches, particularly […]
1. Introduction: Beyond the Hype The rise of AI agents represents a seismic shift in technology. We’re moving beyond basic chatbots that simply respond to prompts, into an era of autonomous systems capable of independent planning, logical reasoning, and executing complex tasks. These advances promise to revolutionize how businesses operate. However, beneath the surface of polished demonstrations and enthusiastic predictions, real-world implementation tells a more nuanced story. This deep dive cuts through the speculation to reveal crucial insights […]