We Tried Google Mixboard. It Gave Us Dogs in Renaissance Paintings and a Glimpse at AI’s Future

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Today we’re breaking down Google’s latest experimental AI interface, Microsoft’s radical new cooling tech for AI chips, and OpenAI’s push for global supercompute supremacy with five new Stargate sites. Add in multilingual mode expansion and you've got one thing clear: the enterprise AI race is about who can build the most usable, scalable, and globally deployable systems first.

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Google Labs’ Mixboard and the Post-Prompt Future

First there was code. Then came prompts. Now Google is pushing us into a world where using AI feels more like remixing a playlist than writing an essay.

Mixboard, launched in Google Labs, is an experimental new interface for human-AI collaboration. No typing or prompt engineering PhD. Just modular actions you can drag, drop, and remix, like digital Legos for your creative brain.

What is Mixboard, really?

It’s an AI concept-building tool designed to help users explore and expand their ideas visually, as an interface layer between humans and machines.

Here’s what you can do with it (so far):

• Start from a text prompt or pick a pre-populated “board” with existing content ideas.

• Generate unique images with AI or upload your own assets.

• Edit visuals with natural language using Google's new image model Nano Banana (great name).

• Modify boards with tiles like “combine these images,” “change style,” or “make it more magical.”

• Quick-generate new options with one-click ideas like “regenerate” or “more like this.”

• Auto-generate contextual text based on the images already in your board

It’s fast, modular, and built for iteration, without needing to know how to prompt engineer or manipulate models under the hood.

From Midjourney to Mixboard: What Happens After the Prompt

Let’s say you prompt: “Great Danes in Renaissance Paintings.”
Both Midjourney and Mixboard can give you charmingly regal canine portraits worthy of a gilded frame.

But here’s where Mixboard breaks away:

Midjourney:

• You get four images.

• Maybe you upscale one.

• Maybe you re-roll or create a video.

• End of story (unless you bring in Photoshop or start over).

Mixboard:

• You edit the image with natural language:
  “Make the background more dramatic.”
  “Add a crown made of grapes.”
  “Change the lighting to look like Rembrandt.”

• You combine images: pull in a second board (“Corgis in a space opera”) and tell it to blend them.

• You generate text from the image:
  “Write a museum placard.”
  “Summarize the themes in 3 bullet points.”
  “Generate ad copy in a Shakespearean voice.”

• You use tiles like “More like this,” “Make it surreal,” “Add motion” to remix, layer, and evolve the idea.

• You turn your output into a collaborative workspace, not a static file.

So while Midjourney is a paintbrush, Mixboard is a modular, multimodal whiteboard built for rapid creative workflows that extend far beyond image generation.

And that’s the unlock: It offers more control over iteration. And I say that as a huge Midjourney fangirl.

And I would be remiss to exclude the two boards combined:

Enterprise teams need this kind of flexibility if they want AI to support cross-functional workflows in design, content, training, and comms.

Why this Matters for Teams

Yes, it’s fun. But the real innovation is in the interface design. Google Mixboard turns AI into a modular, visual, and explainable tool, exactly what large teams need if they want non-technical users to actually adopt AI at scale.

Let’s break it down:

1. Prompting doesn’t scale
   Your ops, marketing, HR, and compliance teams aren’t prompt engineers. They need plug-and-play options. Mixboard is built for them.

2. Workflows become composable
   Instead of manually prompting a model to tweak tone, reformat content, or translate assets, users just drop in a tile that does it.

3. Creative pipelines get faster
   Teams can create drafts, iterate visuals, and fine-tune messaging in minutes

4. Design is finally democratized
   Mixboard lets content and comms teams build usable outputs without design or dev support.

Enterprise use cases to watch:

• Internal training content that blends imagery, context-aware text, and fast iteration.

• Comms and policy drafts with editable, explainable iterations.

• Rapid prototyping for marketing assets, visuals, and presentations.

• Stakeholder feedback loops where reviewers can request edits via simple tiles.

It’s still in beta, but this could be a sneak peek at the post-prompt AI workspace.

More AI News

1. OpenAI Announces Five New Stargate Sites
   OpenAI and Microsoft are building five new “Stargate” supercomputing data centers across the US. The goal: build the infrastructure for GPT-5 and beyond, ensuring global redundancy and training scale.
   Read more →

2. Microsoft Bets on Liquid Cooling with Microfluidics
   New chips = new heat. Microsoft just unveiled microfluidic cooling tech for future AI servers, pushing liquid through channels inside the chip. More energy-efficient, better performance, and crucial for dense AI workloads.
   Read more →

3. Google AI Mode Now Supports Spanish Worldwide
   ¡Por fin! Google’s on-device AI assistant now supports Spanish globally. That means voice, camera, and multimodal commands in a massively expanded market. Enterprise teams building global-facing products, take note.
   Read more →

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TL;DR:

• Google Mixboard is a drag-and-drop AI interface that previews how teams may build with AI in 2026: visually, not textually.

• OpenAI is scaling up with five new Stargate data centers, setting the stage for next-gen model training.

• Microsoft’s new liquid cooling tech shows chip infrastructure is now an enterprise-level concern.

• Google’s AI assistant now supports Spanish globally. Global AI UX is a growth lever, not an afterthought.

• Enterprise AI is no longer just “what model should we use?” It’s “how fast can we build, scale, and support it everywhere?”

The theme this week: Interfaces, infrastructure, and internationalization.

Whether your team is deep in LLM fine-tuning or just getting your first copilot off the ground, remember: the tools that win won’t just be smart. They’ll be usable, scalable, and everywhere your team is.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow’s Tech Landscape Together