nafyi.

A TOPIC, IN CONTEXT

interface generalization

Judgments in this source concerning interface generalization. Explore 1 viewpoint with evidence from 1 source.

0 people · 1 sources · 1 viewpoints

Content updated:

Explore connections ↗

Viewpoint map

0 people · 1 sources · 1 viewpoints

Maxime Theillard, Frederic Renard, Vincent Coyette, Emrick Sinitambirivoutin, Avshalom Manevich, Antonio Loison, Antoine Bonnet, Maxime Langevin, Aleix Cambray (H-AI), Léonard Benedetti, Tony Wu, Mats L. Richter, Michael Eickenberg, Sławek Mucha, Matthias Brunel, Daniel Beechey

Unified model for GUI, code, MCP, and API interfaces

Holo4 interacts with software through any available interface—GUIs, code, MCP, and APIs—and selects the most suitable interface per task, unlike most agentic models trained for only one interface type.

Holo4: powering generalist computer-use agents

Supporting evidence

Maxime Theillard, Frederic Renard, Vincent Coyette, Emrick Sinitambirivoutin, Avshalom Manevich, Antonio Loison, Antoine Bonnet, Maxime Langevin, Aleix Cambray (H-AI), Léonard Benedetti, Tony Wu, Mats L. Richter, Michael Eickenberg, Sławek Mucha, Matthias Brunel, Daniel Beechey·

Holo4: powering generalist computer-use agents

Original excerpt

Holo4 clicks and types on a screen, writes and runs its own code, and calls MCP or API tools. It uses whichever fits the task. Most agentic models are trained for one interface only: GUI-focused models are blind without a screen, while models that prefer tool calling are stuck in front of an application that has no API. Real work is not siloed that way, and a single business task can require combining these different approaches.
Open original · Paragraph 9 (opens in a new tab)Original text source (opens in a new tab)

These findings reflect the available sources, not an exhaustive or current view.

Original conversations1

ARTICLE

Holo4: powering generalist computer-use agents

Hugging Face Blog