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Computerworld更新于 10月24日 10:30

Tether 用免费 AI 弥合智能鸿沟

Tether Is bridging the intelligence gap with free AI

AI 导读

Tether 推出仅 800 万参数的免费开源模型 TranslatePsy-AfriSLM,支持 19 种撒哈拉以南非洲语言的机器翻译,小到可在多数智能手机上运行。Tether 还开发了无云 AI 平台 QVAC,通过 QVAC Fabric 的 SDK 或 QV.AC 应用集成开源语言模型,可在现成 GPU、笔记本和手机上直接推理、训练与个性化,无订阅费、无供应商依赖。Tether CEO Paolo Ardoino 称公司早已不再把自己视为加密公司,而是基础设施提供商。

正文

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The world is advancing toward a future in which over 10 billion humans coexist with trillions of autonomous agents in a superintelligent universe.

But as AI becomes more intelligent, humanity is being divided into those who can access intelligent tools and those who will remain isolated from one of the greatest technological revolutions in decades.

As a response, Tether is building powerful infrastructure across AI, communication, finance, and neurotechnology for a future that doesn’t exclude people based on geography or wealth.

AI should be the great equalizer, but is it?

AI brings a powerful technology to the global population, currently around 17.8% of the world’s working-age population, according to Microsoft’s Global AI Diffusion report .

However, access to its benefits remains uneven.

Economies with the largest quarter-over-quarter gains in AI adoption include the United Arab Emirates, with Singapore and the North Atlantic following behind.

Despite a growing wealth and intelligence gap, with barriers around cost, privacy, and availability, AI adoption continues to grow in the world’s leading economies.

Between H2 2025 and Q1 2026, the rate of AI adoption grew more than twice as much in the Global North compared to the Global South.

The disparity reflects persistent structural barriers in the Global South, including limited access to reliable electricity, internet connectivity, and digital skills.

Machine translation research has largely focused on Asian and European languages with large quantities of training resources.

Meanwhile, African languages spoken by hundreds of millions of people remain relatively neglected compared to their high-resource counterparts.

As long as these languages remain underserved by AI tools, African adoption of the technology risks falling even further behind.

To help advance machine translation across 19 Sub-Saharan African languages, Tether has developed TranslatePsy-AfriSLM , a free collection of open-source AI resources.

At just 800 million parameters, the model is small enough to run comfortably on most smartphones, enabling it to deliver courses, educational content, scientific material, and AI-powered learning tools to traditionally excluded populations in their own languages.

Technology that gives all humans access to intelligence Over the past several years, Tether has developed and invested in AI, energy, and communications, building the systems that let humans and machines work at scale, without depending on a handful of gatekeepers.

This includes Keet , brain-computer interfaces ( BCI ), and investments in robotics .

While many people still view Tether as a stablecoin company, it prefers to describe itself as an infrastructure provider.

“It’s been a while since we’ve considered ourselves crypto,” Tether CEO Paolo Ardoino said in a recent Fortune interview.

Tether is building technology that empowers governments, businesses, and individuals alike, developing universally accessible AI that is modular enough to be embedded in the fabric of any device, system, or environment.

Alongside neurotechnology, P2P communications, and robotics, Tether has developed QVAC, a cloud-free AI platform that grants users full control over their data.

Enabling peer-to-peer connections between devices, QVAC operates directly where it is needed, without intermediaries.

There are no subscription fees, no vendor dependencies, and no data leakage.

Open-source language models can be integrated via QVAC Fabric using a dedicated SDK or the QV.AC app.

The inference runtime and fine-tuning framework let you execute, train, and personalize models directly on everyday hardware, including off-the-shelf GPUs, laptops, and smartphones.

Privacy-first infrastructure that lets users run AI locally without routing everything via centralized data centers is needed to build a more sovereign digital future.

This means making AI more accessible, more resilient, and not exposing vast quantities of personal data to a handful of giant cloud providers.

来源

Computerworld