The human sciences are shifting: for the first time, core research tasks can be handed off to machines. AI chatbots increasingly contribute to scientific research, including in the most prestigious publications and in the social sciences. This has spurred optimism that AI could boost research productivity—while also stoking fears about overloaded peer review and a deluge of academic AI slop. But while turn-taking AI chatbots have primarily been used for writing assistance, coding agents could restructure social science research more radically. Agentic coding platforms like Claude Code and Code
Coding agents in the social sciencesUsing the toolkit for this specific use case provides multiple benefits: Config-driven workflows The toolkit helps shift the project from a rigid script to a flexible research platform. Instead of hard-coding the interactions between agents, you define the system’s logic—including personas, tools, and constraints—entirely within a YAML configuration. This modularity makes it trivial to swap models for different tasks. For example, you can assign a high-reasoning model to handle hypothesis generation while using a faster, more cost-effective model for the code agent without modifying the underl
Automating and Optimizing Financial Signal Discovery with Multi-Agent Systems | NVIDIA Technical Blog…For details, see Simultaneous Discovery of Quantum Error Correction Codes and Encoders with a Noise-Aware Reinforcement Learning Agent . The decoding step is another promising target for AI, exemplified by Google’s…
…to 1 million tokens Available precision BF16 and NVFP4, with additional quantized formats Reasoning mode Configurable on or off Primary use Local agents, customization and specialized workflows License OpenMDW 1.1 Release…
…OrbitQuant instead quantizes in a normalized, rotated basis: a randomized permuted block-Hadamard (RPBH) rotation concentrates each coordinate around one fixed, known marginal regardless of input, so a single Lloyd–Max codebook…
…agent performance and outperforms strong single-agent and multi-agent baselines, and higher attribution quality is associated with greater optimization effectiveness. Code is available at: https://github.com/yxc-cyber/AgentChord. View…
…Quantum Gate Synthesis via Stochastic Commutator Decomposition (2026) Universal Quantum Transformer (2026) Toward General Quantum Control with Physics-Informed Large Language Models (2026) Learning Logical Operations for Arbitrary Quantum Error Correction Codes…
…The ASUS ProArt system with an AMD Ryzen™ AI Max+ processor delivered up to 6X the CPU throughput of a four-year-old laptop in this multi-agent, heavy developer CODEX workflow…
…We’ve partnered with Replit, a leading AI coding agent platform where devs turn natural language into running apps. Build in Replit, deploy with Rayfin and the app, data and services stay…
In medium reasoning mode, it both scores higher than the 3.6 version, AND is very much more efficient (almost half requests needed, and a third less tokens generated) - at DeepSeek v4 Flash 3107 MXFP4 level The xhigh mod…
Following up on my previous post about my budget server setup (Intel N100 + RTX 5060 Ti 16GB), a few of you asked for a deeper dive into my actual inference config and real-world agentic performance. Like many of you, I …
TL;DR: I spent 9 days developing a new quantization method for MLX models and measured 18 variants against each other on a single M5 Max MacBook Pro (128 GB). The result is the best-measuring MLX quant of Qwen3.5-122B-A1…
I used LM Studio Bionic with Qwen 3.8 27B Q3_K_S with 57k context. It took a staggering 63 hours to finish coding. After the first prompt "Create a beautiful, relaxing flight simulator in a single HTML page" taking 47.8 …
I have been using local models on/off for like 2 years or so but never really used them extensively because the closed ones were always much better. Once Qwen 3.8 27B was released I decided to give it another serious try…
…explanations from coding agents. ExplainBench is based on the intuition that informative explanations should enable an LLM to correctly answer questions, allowing quantitative comparison of explanation quality between agents. With this observation…
…tasks through to completion with greater reliability. Qwen3.8 features the following enhancements: Core Capabilities: Comprehensive improvements across coding, professional work, research, and long-horizon agentic tasks. Agent Execution: Stronger autonomous planning…
…OpenCode Use an open-source coding agent with a supported local model provider for code-aware development workflows. OpenClaw Run OpenClaw autonomous agents with NVIDIA NemoClaw to move from prototype to safer…
