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Users flock to open source Moltbot for always-on AI, despite major risks

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI assistants, AI security, AI sycophancy, anthropic, Artificial Intelligence, Biz & IT, chatbots, Machine Learning, Open Source, Peter Steinberger

An open source AI assistant called Moltbot (formerly “Clawdbot”) recently crossed 69,000 stars on GitHub after a month, making it one of the fastest-growing AI projects of 2026. Created by Austrian developer Peter Steinberger, the tool lets users run a personal AI assistant and control it through messaging apps they already use. While some say […]

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Moonshot AI Releases Kimi K2.5: An Open Source Visual Agentic Intelligence Model with Native Swarm Execution

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine Learning, New Releases, Open Source, Tech News, Technology, Uncategorized

Moonshot AI has released Kimi K2.5 as an open source visual agentic intelligence model. It combines a large Mixture of Experts language backbone, a native vision encoder, and a parallel multi agent system called Agent Swarm. The model targets coding, multimodal reasoning, and deep web research with strong benchmark results on agentic, vision, and coding

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DSGym Offers a Reusable Container Based Substrate for Building and Benchmarking Data Science Agents

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine Learning, New Releases, Open Source, Staff, Tech News, Technology

Data science agents should inspect datasets, design workflows, run code, and return verifiable answers, not just autocomplete Pandas code. DSGym, introduced by researchers from Stanford University, Together AI, Duke University, and Harvard University, is a framework that evaluates and trains such agents across more than 1,000 data science challenges with expert curated ground truth and

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Databricks: Enterprise AI adoption shifts to agentic systems

adoption, agentic ai, agents, ai, AI (Artificial Intelligence), AI and Us, AI Business Strategy, AI Market Trends, Artificial Intelligence, automation, databricks, enterprise, Features, governance, Governance, Regulation & Policy, infrastructure, Inside AI, Special Reports & Series, strategy, World of Work

According to Databricks, enterprise AI adoption is shifting to agentic systems as organisations embrace intelligent workflows. Generative AI’s first wave promised business transformation but often delivered little more than isolated chatbots and stalled pilot programmes. Technology leaders found themselves managing high expectations with limited operational utility. However, new telemetry from Databricks suggests the market has

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Anthropic selected to build government AI assistant pilot

agentic ai, agents, ai, AI (Artificial Intelligence), AI and Us, AI in Action, anthropic, Artificial Intelligence, assistants, claude, Governance, Regulation & Policy, government, Government & Public Sector AI, Inside AI, integration, public sector, World of Work

Anthropic has been selected to build government AI assistant capabilities to modernise how citizens interact with complex state services. For both public and private sector technology leaders, the integration of LLMs into customer-facing platforms often stalls at the proof-of-concept stage. The UK’s Department for Science, Innovation, and Technology (DSIT) aims to bypass this common hurdle

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Building Resilient and Autonomous Enterprises 

agentic ai, ai, AI (Artificial Intelligence), Artificial Intelligence, digital transformation, Enterprise AI, Human-in-the-Loop, Observability, Responsible AI

From Always-On Intelligence to Enterprise Control Just ahead of 2025, I had predicted that artificial intelligence would move decisively from experimentation to enterprise reality. That shift has now played out. Over the past year, AI has moved out of isolated pilots and into early production across core enterprise workflows. Agentic systems began executing multi-step tasks. Domain-specific intelligence started outperforming general models

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How a Haystack-Powered Multi-Agent System Detects Incidents, Investigates Metrics and Logs, and Produces Production-Grade Incident Reviews End-to-End

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Infrastructure, Artificial Intelligence, Editors Pick, Staff, Technology, Tutorials

In this tutorial, we design this implementation to demonstrate how Haystack enables building advanced, agentic AI systems that go far beyond toy examples while remaining fully runnable. We focus on a cohesive, end-to-end setup that highlights orchestration, stateful decision-making, tool execution, and structured control flow, demonstrating how complex agent behavior can be cleanly expressed. We

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How Formula E uses Google Cloud AI to meet net zero targets

agentic ai, agents, ai, AI (Artificial Intelligence), AI and Us, AI Business Strategy, AI in Action, Artificial Intelligence, cloud, digital twins, enterprise, Entertainment & Media, Environment & Sustainability, formula e, google cloud, Inside AI, net zero, strategy, Sustainability

Formula E is using Google Cloud AI to meet its net zero targets by driving efficiency across its global logistics and commercial operations. As part of an expanded multi-year agreement, the electric racing series will integrate Gemini models into its ecosystem to support performance analysis, back-office workflows, and event logistics. The collaboration demonstrates how sports

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What is Clawdbot? How a Local First Agent Stack Turns Chats into Real Automations

agentic ai, ai, AI (Artificial Intelligence), AI Agents, Artificial Intelligence, Editors Pick, New Releases, Open Source, Staff, Tech News, Technology

Clawdbot is an open source personal AI assistant that you run on your own hardware. It connects large language models from providers such as Anthropic and OpenAI to real tools such as messaging apps, files, shell, browser and smart home devices, while keeping the orchestration layer under your control. The interesting part is not that

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StepFun AI Introduce Step-DeepResearch: A Cost-Effective Deep Research Agent Model Built Around Atomic Capabilities

StepFun has introduced Step-DeepResearch, a 32B parameter end to end deep research agent that aims to turn web search into actual research workflows with long horizon reasoning, tool use and structured reporting. The model is built on Qwen2.5 32B-Base and is trained to act as a single agent that plans, explores sources, verifies evidence and

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