Tech News
Mapping Europe’s AI Workforce Opportunity
A new OpenAI report maps how AI could reshape jobs across the EU, highlighting which occupations may face automation, growth, or workflow changes.
Ask an AI expert: What exactly is the full stack?
An illustration depicting a full-stack AI infrastructure against a dark background.
Multi-tenant LLM analytics with row-level security: How we built a secure agent on AWS
In this post, we show you how PAR built a production-ready multi-tenant LLM analytics system that enforces row-level security through a three-layer architecture: cryptographic request signing with AWS SigV4, semantic.
Pair Nova 2 Lite with Claude for cost-optimized document processing
In this post, we show how pairing Amazon Nova 2 Lite with Anthropic’s Claude Sonnet 4.6 delivers an efficient solution for digitizing scanned documents at scale. We built a two-model pipeline on Amazon Bedrock for dig.
How to Govern Autonomous Agents in Enterprise AI Factories
AI agents are quickly moving beyond chat. They inspect code, run tests, read documents, search knowledge bases, query internal systems, and operate for hours.
GitHub Repos
generalaction/emdash
Emdash is the Open-Source Agentic Development Environment (🧡 YC W26).
# TypeScript# agenticdevelopment# agenticdevelopmentenvironmentMemPalace/mempalace
The best-benchmarked open-source AI memory system.
# Python# ai# chromadbusewhale/Whale
Whale — blazingly fast, terminal-first AI coding agent for DeepSeek.
# Go# coding agent# deepseekResearch Papers
OpenCUA: Open Foundations for Computer-Use Agents
This work proposes OpenCUA, a comprehensive open-source framework for scaling CUA data and foundation models and releases the annotation tool, datasets, code, and models to build open foundations for further CUA research.
Diversity-Aware Policy Optimization for Large Language Model Reasoning
A systematic investigation into the impact of diversity in RL-based training for LLM reasoning, and a novel diversity-aware policy optimization method that achieves a 3.5 percent average improvement across four mathematical reasoning benchmarks, while generating more diverse...
KLASS: KL-Guided Fast Inference in Masked Diffusion Models
KL-Adaptive Stability Sampling (KLASS), a fast yet effective sampling method that exploits token-level KL divergence to identify stable, high-confidence predictions that speeds up generation significantly while maintaining sample quality is introduced.