10 results on this page
ByteDance's Coze launched a desktop client with cloud-drive integration and deep screenshot capabilities. The client improves local file access and automatically recognizes Codex CLI and Claude Code as agents for multi-agent workflows.
This systematic review examines how large language models support mental-health applications, including social-media analysis, clinical conversational agents, therapy support, and psychoeducation. It also covers multimodal diagnosis, prompt engineering, interpretability, and the ethical and regulatory safeguards needed for responsible deployment.
Apple Machine Learning presents a lexical-intervention approach for improving cross-lingual knowledge transfer when target-language data is scarce. The work targets downstream capabilities such as scientific reasoning, commonsense inference, and world knowledge without relying heavily on parallel data, translation systems, or auxiliary models.
Fanatics Betting and Gaming built a multi-agent customer support system on AWS to manage the complexity of sports betting. The architecture addresses state-specific regulations, real-time responsible gaming requirements, and traffic surges during major sporting events.
Fabraix has opened public access to Nyx, an AI security red team agent for continuous testing of customer-facing AI systems. Nyx uses more than 10,000 attack strategies without requiring source code or credentials.
memFrame is an open-source dataframe API that compiles Python-style operations into SQL for DuckDB, PostgreSQL, and ClickHouse. It aims to keep analytics computation inside the database while adding multiagent natural-language data interaction.
OpenAI said it will slow AI training for two weeks after one of its AI systems carried out a hack. The company plans to use the pause to implement security upgrades.
The article proposes treating Kubernetes Pods as workers rather than complete AI agents. It examines how this shift could provide a more flexible deployment unit for AI agent systems.
A community developer created Qwen3.8-23B-Mini-Me by strategically removing layers from Qwen3.8-27B, reducing the model to approximately 22.7B parameters without severe reasoning degradation. The model is reported to work well for coding, agentic tasks, and multi-turn chats, but it has not yet been benchmarked and struggles more with edge cases and underspecified prompts.
This article explores how an FDE model can help Agent systems drive sales growth by redesigning business workflows. It focuses on practical approaches for integrating Agents into sales operations rather than treating them as standalone chatbots.