MarkTechPost@AI 06月05日 13:55
H Company Releases Runner H Public Beta Alongside Holo-1 and Tester H for Developers
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H公司推出Runner H的公开测试版,旨在通过Agentic AI技术革新数字任务管理。Runner H能够协调多个子代理执行复杂的多步骤任务,例如提取数据、更新CRM系统等。同时,H公司还发布了视觉模型Holo-1的开源版本,以及用于测试的Tester H平台,共同构建了多代理系统在日常工程中的应用蓝图。这些举措为开发者提供了更强大的工具,推动了AI技术在实际工作中的应用,预示着2025年AI代理将成为工具链的重要组成部分。

🤖 Runner H:作为H公司的旗舰产品,Runner H是一个先进的AI代理,允许用户通过简单的提示自动化复杂、多步骤的任务,无需重复的手动输入。

👁️ Holo-1:H公司开源了视觉模型Holo-1,这是一个30亿和70亿参数的动作视觉语言模型,与Surfer H配合使用,在WebVoyager基准测试中UI定位准确率达到92.2%。

🧪 Tester H:H公司推出了Tester H,一个用于企业用户的私有测试平台,能够将简单的英文用户故事转化为可执行的端到端测试,从而缩短回归周期,提高信心。

🔗 功能集成:Runner H集成了记忆、任务编排、执行能力,并与其他软件深度连接,通过单一界面实现Agent Orchestration、App Integration和Knowledge Uploads等功能。

The idea behind Agentic AI is that many small, task-focused agents can cooperate to finish real work; however, this particular idea has felt more like a promise than a product. Fortunately, the Paris-based H Company wants to change that, announcing 3 major steps forward in bringing our vision of Agentic AI to life, starting with putting their flagship runner on the start line.

Runner H by the H Company is now in public beta, inviting anyone to fire off a single prompt and watch a cascade of sub-agents fill spreadsheets, scrape sites, ping Slack, or even settle an invoice while you scan the results.

The Runner H release comes alongside two more announcements: open-sourcing the visual model that guides Runner H’s browser cousin, Surfer H, and launching a private-beta test platform called Tester H. Together, these three announcements sketch a practical roadmap for bringing multi-agent systems into day-to-day engineering.

What is Runner H?

According to the H Company, Runner H is a state-of-the-art AI agent that lets anyone automate complex, cumbersome, multi-step tasks without repetitive and manual input.

In simple words, Runner H is a coordinator for your digital workload:

You provide a high-level goal, and the internal orchestration system breaks that down. This system intelligently assigns tasks to specialized sub-agents, including their Browse agent, Surfer H, and other connected applications. This allows Runner H to:

Runner H’s design answers the two frustrations developers mention most with large language models (LLMs): Fragmented context and weak execution.

Instead of returning a paragraph of advice, Runner H allocates tasks to mini-agents that can plan, call APIs, click through the UI, and keep track of what happened last time. H Company calls the approach “memory + orchestration + execution.” In practice, that means tasks that used to bounce between a shell script, Zapier, and a human checker can live in one chat thread.

Runner H integrates memory, task orchestration, execution capabilities, and deep connections with other software into a single interface.

Here are the key capabilities:

According to H Company, Runner H is designed to redefine interaction with AI by creating a more intuitive and potent way to manage digital tasks.

How to use Runner H:

Step 1: Visit the Runner H web page on the H Company’s website and click on Try Now.

Step 2: Sign up to get started. Enter your prompt and submit.

Step 3: Runner H will take a few minutes to complete the task, depending on the task’s complexity. You can see and track everything from start to end.

Holo-1: Open weights for visual navigation

Automating the browser means seeing the browser. To make that reliable and cheaper, H Company has released Holo-1, a family of 3-billion- and 7-billion-parameter action vision-language models.

Paired with Surfer H, Holo-1 scores 92.2% on the WebVoyager benchmark for UI localization while staying small enough to run on a single GPU. Both the weights and a 1,639-scenario WebClick dataset are now live on Hugging Face, giving academics and startups fresh material for training agents that can read and click.

Tester H: Closing the QA gap

If AI cranks out code in seconds, quality assurance cannot rely on weekly manual test plans. Tester H, now in private beta for enterprises, turns plain-English user stories into executable end-to-end tests. ‘

Agents would step through the interface like a real customer and start clicking buttons, opening modals, checking text and layout, and reporting any deviation.

Early tests say they have cut regression cycles while raising confidence in each push. Requests to join the beta are open on H Company’s site.

Conclusion

H Company’s recent announcements, particularly the launch of Runner H into public beta, is the first wide-open playground that points to a future where AI agents play a more active role in both personal and professional productivity. Adding an open-source visual model like Holo-1 and a testing agent like Tester H contributes a valuable resource to the broader AI community, aiming directly at DevOps pain points.

H Company is betting that 2025 will be the year agents stop being a demo and start being part of the toolchain. For now, the introduction of more sophisticated agentic AI capabilities is an interesting development to watch in the growing tech story.

The post H Company Releases Runner H Public Beta Alongside Holo-1 and Tester H for Developers appeared first on MarkTechPost.

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