A farmer in rural India photographs a dying crop and wants to look it up online. She doesn’t speak English, and a nonprofit called Current AI argues she shouldn’t have to. According to TechCrunch AI, that gap is exactly what the organization is trying to close by building open, public AI infrastructure that anyone can use for free.
The pitch from CEO Ayah Bdeir is blunt. Every major AI system today, from OpenAI to Google to Anthropic, belongs to a private company. “If AI is truly a transformative technology, if it’s going to change every aspect of everyone’s life, there has to be a public alternative,” she told TechCrunch AI. Her model is the early World Wide Web: open, shared, and available to anyone at no cost.
What Current AI is building
Founded in February 2025 by Martin Tisne, the nonprofit is moving quickly. TechCrunch AI reports it has stacked up real output in a matter of months:
- Suno Sutra, a pocket-sized offline device built with India’s government AI language division, Bhashini. It runs AI in 22 Indian languages with no internet connection, and it’s open-sourced for developers to build on.
- $3.2 million in grants deployed last month across four organizations in Kenya, Lebanon, and the Brazilian Amazon.
- Alpha Chat, an open-source chatbot assembled in seven weeks by a coalition of ten groups, including Hugging Face, Mozilla, and MIT Media Lab.
Bdeir joined in January after leading Mozilla’s AI strategy. Before that she founded littleBits, the STEM education company that reached millions of kids before selling to Sphero in 2019.
Who’s paying for it
This isn’t a scrappy side project. Current AI runs as what Bdeir calls a public-private partnership, pulling together governments, companies, and philanthropies. The French government seeded it with $100 million. The Ford Foundation, MacArthur Foundation, DeepMind, and Salesforce joined in, bringing total committed funding to $400 million.
The distinction Bdeir draws matters. “They’re not investors; they’re funders,” she said. No one is expecting a return, which is what lets the group prioritize communities that commercial AI tends to skip.
Why this matters
The language problem is the sharp end of the argument. Half the world’s spoken languages face extinction, and English drives the largest models. That leaves a huge share of the world’s languages, and the cultures attached to them, out of the systems now shaping daily life.
Bdeir is skeptical of Big Tech’s multilingual efforts. “Big tech builds multilingual models to expand their market,” she said, “regardless of consent or context.” She points to a concrete harm: for Indigenous languages, missionary Bible translations often become training data before communities set any rules of their own.
Her framing goes past translation. “Language is how knowledge, tradition, memory and identity get carried from one generation to the next. So when a technology can’t speak your language, it can’t hold your culture either,” she said.
The data ownership question
What stands out here is that Current AI isn’t pretending to have solved the hardest part. The grantees are wrestling with who owns community data, and none have fully cracked it. Bdeir treats that as the point, not a failure. Each project keeps models and data stored locally, brings in community experts before building, and writes consent protocols into the pipeline so a community can halt the work at any time.
“It shouldn’t be a company in Silicon Valley trying to make a select few thousand people wealthier,” she said.
She also rejects scale as the only scorecard. A $3.2 million budget split four ways won’t rival a frontier lab’s compute bill, and she says that’s fine. “Scale is not always the measure. That is the Big Tech paradigm.”
What comes next
The roadmap is expansion of the stack, not just the reach. Current AI struck a deal with Tokyo-based Sakana AI to build a shared open-source stack supporting Japanese language and culture, plus communities across the Global South. Expect more grant cohorts, more contributors piecing together the open stack, and a longer test of whether a public alternative can hold up next to trillion-dollar rivals.
Whether the World Wide Web analogy holds is the open question. For now, the money is committed and the tools are shipping. Full details are available in the original TechCrunch AI report.