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Finding a Needle in the Haystack: Querying Physical AI Data with Daft

This article explores how to use the Daft framework to query Apple's EgoDex dataset efficiently. By combining frame-level semantic embeddings (like SigLIP) with geometric features, researchers can use natural language to search video clips, such as 'find every clip where a writing-gripped hand lifts chopsticks.' Daft enables discoverability in large-scale, unstructured robotic datasets.

Hacker News AIAgents / ChipsIn-site article
Teaching AI to Reason About Software

A team at AWS trained a small language model on Soteria's symbolic execution traces, beating a model four times its size at catching bugs in C. We explore what they did and why it matters for the future of AI-assisted software engineering.

Hacker News AIAgents / PolicyIn-site article
'It's like having a dumb friend': Young San Franciscans hate AI

Despite San Francisco being seen as an AI hub, many young residents resent AI for eroding community culture, threatening jobs, and widening inequality. Grassroots group 'Stop AI' protests, polls show Gen Z skepticism, and individuals share disillusionment with AI tools.

Hacker News AIPolicy / StartupsIn-site article
Show HN: Simulate what AI agents do to an engineering org (no signup)

Meridian is a free simulator that models the impact of AI agents in a 35-person SaaS engineering org. Adjust assumptions, see real-time changes in cost, capacity, and coordination. Share scenarios as links or export as OrgSpec.

Hacker News AIAgents / ResearchIn-site article
Using Lift to Turn Research PDFs into Structured JSON with Controlled, Schema-Guided Field-Level Evaluation

This tutorial builds a full PDF-to-structured-data extraction workflow around Lift, focused on controlled evaluation rather than a one-off demo. We prepare a Colab GPU environment, load Lift in 4-bit NF4, generate synthetic research reports with deliberate distractors, run schema-guided extraction, score every field against ground truth, and assemble results into a queryable knowledge base. The outcome is a repeatable extraction benchmark, not just raw model outputs.

MarkTechPostAgents / ChipsIn-site article
OpenClaw’s new app doesn’t run AI on your phone. That’s the whole point.

OpenClaw released iOS and Android apps this week, allowing users to directly interact with a personal AI agent that runs remotely, not on the device. The phone acts as a window with voice, notifications, and camera access. This trend, also seen in Anthropic’s Claude Cowork and OpenAI’s Codex, shifts engineering focus from mobile constraints to distributed systems, identity, and security.

The New Stack AIAgents / PolicyIn-site article
Show HN: An AI agent that applies to jobs for me (Playwright, GPT-5.4 form filling)

This project is an AI agent that automates the entire job application loop: discovers open roles, tailors your resume, generates a PDF, and fills out ATS application forms (Greenhouse, Ashby, Lever, etc.), but stops before submitting to let you review and click Submit. It's an assistant, not a spam cannon.

Hacker News AIModels / AgentsIn-site article
MIT in the media: Innovating and educating for the next 250 years of America

During a "Washington Post Live" panel discussion with ASU President Michael Crow, President Sally Kornbluth explored how universities are preparing the next generation of scientists to lead in America’s rapidly changing technological landscape.

MIT News AIPolicy / Research / StartupsIn-site article
Godot says bye bye AI, bans vibe-coded contributions

The open-source Godot engine team is rewriting its contribution policy to ban nearly all AI-generated contributions, citing demoralizing and unmanageable pull requests. New contributors must obtain explicit permission for significant changes, and AI agents are barred from communication channels.

The Register AI + MLAgents / Policy / RoboticsIn-site article
Agentic design patterns, read through a healthcare AI lens

The author revisits common agentic engineering patterns from Anthropic's guide, applying them to healthcare. The key insight is that verifiability determines autonomy: structured data like FHIR makes tasks verifiable, allowing higher autonomy, while clinical judgment remains human-supervised. The piece emphasizes simplicity, transparency, and the importance of evals in defining 'good enough.'

Hacker News AIAgents / PolicyIn-site article
PieterPost MCP

PieterPost MCP connects AI agents to postal mail, allowing agents like ChatGPT and Claude to prepare letters, postcards, manage contacts, upload attachments, create checkout links, and track orders. It's a feature of PieterPost, enabling physical mail from AI workflows.

Product Hunt AIAgentsIn-site article
In AI-exposed jobs, only the youngest workers are losing ground

Since ChatGPT launched, employment for 22-25-year-olds in AI-exposed jobs fell about 12%, while older age groups held steady or grew. The decline stems from reduced hiring in entry-level roles that rely on codified knowledge, sparing experienced workers who benefit from tacit knowledge.

Hacker News AIAgents / ResearchIn-site article
Cloudflare wants to build the economic layer of the AI web

As AI reshapes search, Cloudflare announces new tools to help publishers monetize in an AI-driven web. New features include a shift from Pay Per Crawl to Pay Per Use, AI crawler classification, analytics dashboards, and Answer Engine Optimization.

The New Stack AIAgents / PolicyIn-site article
HN: Goat 2.0 – proactive episodic memory for AI agents

Goat 2.0 is a Telegram-based AI agent built around a proactive layered memory system. Unlike standard RAG, it retrieves memory before every turn, independent of query content. It features three independent backends (Redis, ChromaDB, Letta), adaptive token scaling, priority-inverted L2/L3 split, and write-through archiving. This project demonstrates how to build an AI assistant with complex memory mechanisms.

Hacker News AIAgents / ResearchIn-site article
ZCode: Claude Code from the Makers of GLM

An AI Gomoku game built from scratch with heuristic strategy, featuring a 15x15 board, win detection, and AI opponent that scores moves based on attack, defense, and center preference.

Hacker News AIModelsIn-site article
How Cursor deploys AI inside the enterprise

Pauline Brunet, VP of Forward Deployed Engineering at Cursor, explains how her team helps organizations implement AI agents across the software development lifecycle, aiming for an 'AI software factory.' She discusses challenges in scaling adoption, the evolution of the FDE role, and advice for engineers aspiring to enter the field.

Latent SpaceAgents / ChipsIn-site article
Japan plans sovereign AI model and 10M robots

Japan plans to develop a homegrown artificial intelligence model and have 10 million AI-equipped robots operating in more than a dozen sectors by 2040, the government said. The country will reportedly invest around $6 billion in the homemade AI model, which will be developed by Noetra, a consortium of firms including SoftBank and Sony. Countries around the world are seeking to develop sovereign AI models to reduce a potentially dangerous over-reliance on technology from the United States and China.

Hacker News AIModels / Startups / RoboticsIn-site article
Anthropic is hiring someone to protect democracy from its own AI

Anthropic posted a job opening for a Research Engineer on a team called Rule of Law, aiming to study and mitigate the potential impacts of its AI systems on democratic institutions. The role sits within the newly formed Anthropic Institute, which has insider access to assess how the company's AI affects the economy, democracy, and society. The work involves three areas: ensuring AI agents obey the law, studying how AI may reshape government, and using AI to enrich democratic life. The ideal candidate must have deep expertise in AI and substantive knowledge of law, political science, or public policy.

Hacker News AIAgents / Policy / ResearchIn-site article
The hard part of AI root cause analysis is no longer the model

The article argues that the real challenge in AI root cause analysis (RCA) is not the model's reasoning capability but the harness—the data preparation and tooling. Through an experiment, the author shows deterministic preprocessing pipelines matter more than the model. Different models' performances are evaluated, highlighting the importance of focused context over raw telemetry.

Hacker News AIAgents / ResearchIn-site article
Don't let AI fill in all the important blanks

The article argues that while AI excels at 'filling in the blanks,' this leads to generic output. The author advocates for specificity in prompts, treating LLMs as pair programmers rather than black boxes, and avoiding abdication of decision-making. Key points include anchoring prompts with concrete decisions, reducing non-determinism, and improving prompting skills to get personalized results.

Hacker News AIToolsIn-site article
Run NVIDIA Nemotron and OpenAI GPT OSS models on Amazon Bedrock in AWS GovCloud (US)

AWS GovCloud (US) now supports OpenAI's open-weight GPT OSS models (120B and 20B) and NVIDIA Nemotron models (Nano 9B v2, Nano 12B v2, Nano 30B, Super 120B) via Amazon Bedrock. Inference runs entirely within the US on infrastructure operated by US citizens, meeting FedRAMP, DoD SRG, and other compliance frameworks.

AWS Machine Learning BlogModels / Agents / ChipsIn-site article
Structured memory filtering with metadata in AgentCore Memory

Learn how metadata filtering in Amazon Bedrock AgentCore Memory enhances retrieval precision. By adding attribute-based filters on top of namespace isolation, agents can scope searches by business dimensions like priority, department, or time range. The article details the three-phase lifecycle of metadata (configuration, ingestion, retrieval), highlights strictly-consistent extraction, and provides best practices for multi-agent and multi-tenant architectures.

AWS Machine Learning BlogAgents / ResearchIn-site article
HippoRAG: Neurobiologically inspired RAG using Amazon Bedrock, Amazon Neptune, and personalized PageRank

In this post, we demonstrate how to implement HippoRAG using a comprehensive AWS stack. We use Amazon Bedrock for LLM capabilities, Amazon Neptune for graph database functionality, Amazon Neptune Analytics for advanced graph algorithms including Personalized PageRank, and Amazon Titan Embeddings for vector representations. This implementation showcases how to build and deploy HippoRAG within AWS infrastructure for enterprise-scale applications.

AWS Machine Learning BlogModels / ResearchIn-site article