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OpenMOSS-Team's MOSS-VL-Realtime is a real-time multimodal AI model that combines vision and language capabilities for live processing and understanding of visual information. The system is designed to handle dynamic visual input with low-latency responses for practical applications.

Pazi is an AI team for that idea you keep coming back to — a book, a shop, an app, a skill you want to sell. Tell Pazi what you're trying to do and it builds a team of agents around your idea and starts making things happen: a website, first outreach, content, the next step. Every time you come back, something has moved. You stay in control; your team does the rest alongside you, one real step at a time. Like vibe coding but for business operations.

ClawTeams is an AI employee platform for e-commerce sellers. Instead of hiring specialists—or doing everything yourself—you get a coordinated AI team that thinks, plans, and executes like real employees. One goal. One team. Zero micromanagement. Tell your team lead what you want—"Increase Q4 revenue by 20%"—and they break it down, assign specialists, and run the plan. You get updates in Slack or Discord. High-stakes decisions wait for your approval. Everything else just happens.

The winning ads in your niche reveal what works: hooks, offers, copy structures, layouts. Goose learns those patterns and creates new ads for your brand with your real logo, product images, and messaging in minutes. First 10 ads free.

Give your AI agent a debit card. Issue single-use cards funded from your wallet with a fixed budget so your agents can buy things online.

A developer successfully trained a reinforcement learning agent that learns to train other models using RL, achieving this with a profit of $1,300 through cost optimization. The project demonstrates the feasibility of using RL agents to autonomously improve machine learning model training processes.

Claude Overlay is a frameless, always-on-top chat window for Claude Code that floats over everything you do. Summon it with a hotkey, ask about whatever's on screen, and Claude captures and reads your monitors before answering. It runs the full Claude Code agent on your own subscription - no API key - so it can edit files and run commands, not just chat. Open source (MIT), Windows.

Branda turns any website URL into scroll-stopping, on-brand ads in seconds. Paste a link and Branda pulls the brand's real logo, colors, and campaign imagery via Context.dev's Brand API, reads the homepage so the copy sounds like the brand, and generates ready-to-ship creatives for LinkedIn and X. No login, no design skills, no assets to upload. Open-source and self-hostable.

Codex has implemented encryption for sub-agent prompts to enhance security and privacy in its AI systems. This update protects sensitive instructions and data passed between agent components from unauthorized access.

This article explores various alternatives and methods for running CUDA applications on non-Nvidia hardware, enabling developers to leverage GPU acceleration without being locked into Nvidia's ecosystem. The alternatives discussed include platform-agnostic frameworks and compatibility layers.

A developer successfully implemented a functional neural network entirely using SQL queries, demonstrating that complex machine learning computations can be performed within relational database systems. This project showcases an unconventional but technically feasible approach to running neural networks.

This PDF explores the economic implications and feasibility of recursive self-improvement in AI systems, analyzing how systems that improve themselves could impact resource allocation and economic value. The paper provides theoretical frameworks for understanding the economics of exponential AI capability growth.

Coding agents have developed the capability to engage in lookahead planning before executing code, enabling more strategic problem-solving. This advancement allows agents to better anticipate consequences and optimize their approach prior to implementation.

Jul 14, 2026Economic ResearchHow Canada uses Claude: Findings from the Anthropic Economic Index

Large language models (LLMs) have achieved remarkable performance on high-school and olympiad-style mathematics, yet their capabilities on advanced mathematics remain poorly understood. Existing benchmarks, however, fall short in both scope and evaluation granularity: they provide limited disciplinary coverage and often rely on final-answer correctness or coarse judgments, leaving the validity of the reasoning process inadequately assessed. To bridge this gap, we introduce AdvancedMathBench, a b...

Post-training is essential for refining the domain-specific capabilities of large language models (LLMs), yet existing reward optimization and distribution matching methods tightly couple policy exploration with distribution alignment. This coupling forces expensive exploration directly on the policy model and severely hinders the asynchronous generation, reuse, and cross-model transfer of optimization signals. In this paper, we propose Proxy-guided Update Signal Transfer (PUST), a novel post-tr...

Recent foundation image and video generation models offer strong generalization and controllability, but their direct application to embodied scenarios is limited by requirements for multi-view consistency, geometric coherence, and robot embodiment constraints. Existing methods typically adapt foundation models with limited robot data, often sacrificing visual knowledge acquired during large-scale pre-training. We present Xiaomi-Robotics-U0, a 38-billion-parameter multimodal autoregressive model...

This work explores the motion transfer from one video to another, which is crucial in animation for diverse characters. Previously, video motion transfer has been largely explored between human and human-like characters, enabling a lot of applications in digital creation. However, these approaches encounter a main limitation. Specifically, related technical pipelines heavily rely on a predefined human skeleton structure and accordingly require skeleton-conditional model training. On the one hand...

Personal AI assistants on mobile and wearable devices continuously perceive users' daily lives through visual and audio streams. However, answering queries about past experiences requires lightweight multimodal memory that can continuously accumulate, organize, and retrieve long-term experiences, which remains challenging. To address this challenge, we present LightMem-Ego, a lightweight streaming multimodal memory system for everyday-life assistance. The system continuously captures egocentric ...

Language models are increasingly used for moral decision-making across diverse linguistic and cultural contexts, yet existing work overlooks multilinguality on three aspects: 1) multilingual evaluation benchmarks use direct translation, failing to adapt culture-specific items; 2) inference-time methods for moral reasoning rely on static, English-centric scaffolds and lack grounding in moral theory; 3) training methods for moral decision-making typically require expensive supervision from stronge...

Metacognition is a foundational component of intelligence critical to effective learning, problem solving, decision-making, communication, and more. In recent years, it has become increasingly recognized as a cornerstone of capable, transparent AI systems. Yet while LLMs have made significant progress across diverse real-world tasks, it is not yet clear when, how, or to what extent they can exhibit or be endowed with effective metacognitive abilities, nor how such abilities can be adapted to adv...

Generating and editing a person's face demands high precision, as even minor modifications can significantly alter a subject's perceived identity. Current personalization and editing methods built on general-purpose text-to-image models, however, often lack the precision required for fine-grained facial edits. We present a method for fine-grained identity tuning in text-to-image personalization models. Unlike standard image editing, which operates on a given image, identity tuning modifies the l...

Demis Hassabis, CEO of DeepMind, presents a strategic plan for developing and deploying AI systems in a manner that prioritizes safety and alignment with human values. His approach focuses on responsible AI development practices to mitigate potential risks.

Microsoft is rolling out Claude Code and GitHub Copilot CLI in early 2026, expanding AI coding assistant capabilities across its development tools. This integration aims to enhance developer productivity by combining multiple advanced AI models for code generation and command-line operations.

Samsung's Health app is threatening to delete user data for those who opt out of AI training, raising concerns about coercive data practices and user privacy. This approach forces users to choose between participating in AI model training or losing access to their health information.

This article explores the emerging role of Forward Deployed Engineers in the AI industry and examines why companies are increasingly seeking these specialized professionals in 2025. These engineers bridge the gap between AI development and real-world deployment challenges.

OpenAI's advertising business is projected to miss its own revenue forecast by 90%, according to analyst estimates, indicating significant shortfalls in monetizing its AI platform. The underperformance suggests challenges in converting user traffic into profitable advertising revenue.

The article explores concerns about job displacement and human relevance as AI systems become increasingly capable of performing traditional work tasks. It questions what meaningful roles and responsibilities will remain for human workers in an AI-dominated landscape.

Codex scraped the ICM (International Congress of Mathematicians) website and unexpectedly extracted what appears to be a list of 2026 Fields Medal winners. This raises concerns about data scraping practices and the unintended leakage of potentially confidential information.

See how data science teams can use ChatGPT Work to build root-cause briefs, impact readouts, KPI memos, scoped analyses, and dashboard specs from real work inputs.

See how sales teams can use ChatGPT Work to create pipeline briefs, meeting prep packets, forecast reviews, account plans, and stalled-deal diagnoses from real work inputs.

Learn how enterprises can manage AI investments in the agentic era by measuring useful work per dollar, improving efficiency, and scaling high-value workflows.