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2,348 notes and 295 topics.
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2,348 notes, page 15 of 98
Alaya-EVOKE: From Linear-Scaling Supervision to Endless World
The paper presents an interactive video world model that keeps track of a scene's state outside the model itself (an externally stored, camera-indexed memory) so it does not need to hold everything in context, aiming…
Amazon Quick for Microsoft 365: Agentic AI where you work
AWS announced general availability of Amazon Quick extensions for Word, Excel, PowerPoint, and Outlook, adding AI features that can act inside documents (not just answer questions), for existing Quick customers on paid…
Monitor on-premises and multi-cloud AI agents with AgentCore Observability
AWS published a how-to guide for sending telemetry from AI agents running outside AWS (on-premises or on another cloud) into Amazon Bedrock AgentCore Observability, using an open standard called OpenTelemetry.
Automate legacy web applications with Amazon Bedrock AgentCore Browser Tool
AWS describes a reference architecture where an AI agent uses a browser-automation tool (AgentCore Browser Tool plus Strands Agents) to operate legacy server-rendered web applications, positioned as an alternative to…
Accelerating M&A due diligence with Amazon Bedrock AgentCore
AWS describes a sample multi-agent system built on Bedrock AgentCore that automates parts of mergers-and-acquisitions due diligence: target screening, financial analysis, strategic-fit evaluation, and compliance…
How Scottish Water Made Its Capital Investment Data Conversational With Databricks Genie
Databricks published a customer case study describing how Scottish Water built "SPARK," a natural-language interface over Databricks Genie and Microsoft Teams/Copilot, to let staff query capital investment project data…
Smart Routing in Unity AI Gateway: Match frontier quality with 30%+ lower cost per task
Databricks announced a "Smart Routing" feature in Unity AI Gateway that automatically picks which AI model handles a coding task based on task complexity, claiming lower cost at similar quality versus always using a…
DreamX-Phi 1.0: Action-Conditioned Video World Model for Robotic Manipulation
The paper describes a model that, given a starting camera frame, a language instruction, and a planned sequence of robot actions, predicts what the robot's camera would see next, intended to help with robotic…
HiLS-Attention: Hierarchical Sparse Attention Done Right
Tencent's Hunyuan team released official code for HiLS-Attention, a chunk-based sparse attention method meant to make very long-context language models faster to run while keeping accuracy, learning which chunks of…
Hunyuan3D-WorldClaw: Agentic 3D Open-world Generation at Scale
Tencent's Hunyuan team released "WorldClaw," a system that uses AI agents combined with procedural generation to build large open-world 3D environments.
Intern-S2-Preview: Scientific Agentic Foundation Model
The paper introduces a family of foundation models trained specifically for multimodal scientific work, using scientific documents, interleaved image-text data, and diverse scientific corpora, with a large…
Koedinger Wins Lifetime Achievement Award
CMU announced that Ken Koedinger, a Hillman University Professor at CMU's Human-Computer Interaction Institute, received the Lifetime Achievement Award from the International Artificial Intelligence in Education…
Patterns and Problems in Emerging Multiagent Systems
Anthropic's Frontier Red Team describes patterns observed when multiple Claude agent instances interact on shared tasks: coordination breakdowns, agents converging on near-identical behavior (low variance)…
A corpus-specific clinical RAG system matches or outperforms newer frontier LLMs on HealthBench
A research study compared the performance of VITA, a specialized clinical AI tool for low- and middle-income settings, with various frontier large language models (LLMs) on the HealthBench benchmark. The study found…
A corpus-specific clinical RAG system matches or outperforms newer frontier LLMs on HealthBench
A research paper evaluates VITA, a clinical knowledge retrieval system built for low- and middle-income settings, on a medical benchmark. In comparison to various frontier large language models (LLMs), including…
AI4AI at Test-Time: Strong-to-Weak Capability Transfer via Harnesses
The study presents a new approach for transferring capabilities of large AI models to smaller ones at test time instead of during training. This method involves using a stronger model to create inference-time harnesses…
An Agentic Workflow for Legacy HPC Modernization: Converting the Two-Electron-Integral Core of GAMESS
The authors propose an agentic workflow for large-scale modernization of legacy Fortran code, specifically demonstrating it on the two-electron-integral routines of GAMESS (a 48-year old quantum chemistry software)…
An Agentic Workflow for Legacy HPC Modernization: Converting the Two-Electron-Integral Core of GAMESS
Researchers proposed an agentic workflow to modernize legacy Fortran code at a large scale. They applied this method in a case study by converting parts of GAMESS, a quantum-chemistry software package, from Fortran 77…
An Agentic Workflow for Legacy HPC Modernization: Converting the Two-Electron-Integral Core of GAMESS
Researchers propose an agentic workflow to modernize legacy Fortran code at a large scale. They apply this workflow in a case study by converting the two-electron-integral routines of GAMESS (a quantum-chemistry…
Benchmarking LLM Judges for Mobile Agent Evaluation
A benchmark study of LLM judges used to evaluate mobile-agent trajectories.
Better Slots, Better Worlds: Representation Quality & Robustness in Object-Centric World Models
The study investigates the performance of object-centric world models for visual model-predictive control, which enable agents to accomplish tasks through planning. The researchers find that these models perform better…
Better Slots, Better Worlds: Representation Quality & Robustness in Object-Centric World Models
The research focuses on object-centric world models (OCWMs) for artificial intelligence agents. The study compares OCWMs with traditional scene-centric models in terms of representation quality, planning success, and…
Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence
Researchers present the 'Agentic Self-Improvement' framework to address challenges in professional workflows with modern Image-to-Video (I2V) models. The framework uses a two-stage approach: an iterative prompt…
Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence
The researchers introduce a new framework called 'Agentic Self-Improvement' to address challenges in professional workflows related to modern black-box Image-to-Video (I2V) models. The framework optimizes the video…
An AI research agent drafts these notes from public papers and posts, and each one keeps its source link. Only the folders I choose to publish leave my Obsidian vault.
