🎧 Prefer to listen?

Every AI tool you use today — ChatGPT, Claude, Gemini — belongs to a company. They set the prices, they control the data, and they can change the rules whenever they want. I’ve been thinking about this a lot lately, especially after writing about how AI agents are becoming employees — the more we depend on these systems, the more power their owners have.

A nonprofit called Current AI is trying to change that. And they’ve got $400 million to back it up.

What Current AI actually is

Current AI was founded in February 2025 by Martin Tisné with a simple premise: if AI is going to transform everyone’s life, there should be a public alternative. Like the early web — open, free, nobody’s property.

The French government seeded it with $100 million. The Ford Foundation, MacArthur Foundation, DeepMind, and Salesforce followed. Total committed funding: $400 million. Their CEO, Ayah Bdeir, joined in January after leading Mozilla’s AI strategy. She previously founded littleBits, the STEM education company that reached millions of kids before selling to Sphero.

The vision is modeled on the World Wide Web itself. When Tim Berners-Lee invented the web, he didn’t patent it. He gave it away. Current AI wants to do the same thing for AI infrastructure.

What they’re actually building

This isn’t just a think tank writing policy papers. They’re shipping real products.

Suno Sutra — a pocket-sized, offline device that runs AI in 22 Indian languages. No internet required. Built with Bhashini, the Indian government’s AI language division. Open sourced so developers can build on it.

AlphaChat — an open source chatbot assembled in seven weeks by a coalition of 10 organizations including Hugging Face, Mozilla, and MIT Media Lab. Each contributor brought a piece of the stack — language model, safety tooling, computing power. Launched at the AI for Good Global Summit in Geneva.

$3.2 million in grants across four organizations in Kenya, Lebanon, and the Brazilian Amazon. The projects include building AI datasets across 50+ African languages, digitizing Arab cultural history, building offline AI tools with Indigenous Amazon communities, and developing audit tools to hold AI systems accountable.

If you’ve been following the open source AI movement, this feels like the next logical step — not just open models, but open infrastructure.

Why this matters for solo builders

Here’s why I care about this as someone who builds with AI tools every day.

Right now, the AI landscape is a handful of companies selling access to their models through APIs. You don’t own anything. If OpenAI raises prices, you pay more. If Anthropic changes their usage policy, you adapt or leave. I wrote about this dynamic when I tested Claude’s free alternatives — the dependency is real.

Current AI is building an alternative layer. Open models, open data, community-owned infrastructure. If they succeed, it means:

  • Lower costs. Open infrastructure drives prices down for everyone. We’ve already seen this with open source coding models like NousCoder — competition makes things cheaper.
  • No lock-in. You can switch between providers without rewriting everything. The same way you can switch web browsers without losing the internet.
  • Community control. Data stays with the people who generated it. Not in some company’s training pipeline.

This is the same pattern that made the web work. Open protocols, open standards, anyone can build on top. The difference is that Current AI is doing it intentionally, from the start, before AI becomes as locked-down as social media.

The language problem nobody talks about

Half the world’s spoken languages face extinction. And the AI systems we’re building — the ones that will shape how people access information for the next generation — are almost entirely English-first.

Bdeir put it bluntly: “When a technology can’t speak your language, it can’t hold your culture either.”

Big Tech’s multilingual push isn’t solving this. As Bdeir pointed out, “Big tech builds multilingual models to expand their market, regardless of consent or context.” For Indigenous languages, missionary Bible translations become training data before communities have set any rules.

Current AI’s approach is different. They store models and data locally, bring in community experts before anything gets built, and write consent protocols into the pipeline so communities can halt the process at any point.

What’s next

Current AI struck a deal with Sakana AI, a Tokyo-based startup, to build a shared open source AI stack designed for the Japanese language and Global South communities. They’re also expanding their grant program.

The scale question is real — $3.2 million split four ways isn’t going to reshape the AI landscape overnight. But Bdeir’s answer resonated: “Scale is not always the measure. That is the Big Tech paradigm. This could look like an Indigenous elder in the Brazilian Amazon using a tool built in Kenya to be able to pass down ecological knowledge in their own language.”

That’s the kind of infrastructure worth building.

The bottom line

If you’re building with AI tools — whether it’s automating workflows or testing productivity tools — keep an eye on Current AI. Open infrastructure benefits everyone, even if you never touch their code directly. Competition drives prices down, open standards prevent lock-in, and community-owned data means fewer surprises.

Want to explore more AI tools that won’t break the bank? Check out the AI Tool Advisor or start here.