Why On-Device AI Matters
The case for sovereign intelligence: how running AI locally on Apple Silicon changes privacy, speed, and ownership.
The Cloud AI Bargain
Every time you type a prompt into a cloud AI service, you're making a trade: your data for intelligence. Your documents, conversations, code, and ideas travel to a remote server, get processed, and a response comes back. What happens to your data in between? You're trusting the provider's privacy policy — a document that can change at any time.
For most people, this trade feels invisible. But for professionals handling sensitive information — legal documents, medical records, financial data, proprietary code — it's a serious liability.
When your AI runs locally, your data never leaves your machine. There's no server to hack, no policy to trust, no jurisdiction to worry about.
The Sovereignty Alternative
On-device AI eliminates this trade entirely. When your AI runs locally on your Mac, your data never leaves your machine. There's no server to hack, no policy to trust, no jurisdiction to worry about. The AI is yours in the most literal sense — it runs on hardware you own, processes data you control, and answers only to you.
This isn't a theoretical advantage. Apple Silicon's unified memory architecture means that a 16GB Mac can run capable language models at interactive speeds. The Neural Engine provides dedicated AI acceleration. Metal shaders handle parallel computation. All of this runs locally, with zero network latency.
Speed Without Compromise
Cloud AI adds latency at every stage: your prompt travels to a server, waits in a queue, gets processed, and the response streams back. Even with fast connections, this adds hundreds of milliseconds to every interaction.
On-device AI starts generating tokens the moment you press enter. There's no queue, no server warm-up, no network jitter. On an M3 Pro, you can expect 30+ tokens per second from a 7B parameter model — fast enough to feel instantaneous.
The Personal Context Advantage
Cloud AI services are stateless by design. Each conversation starts fresh. They don't remember your preferences, your vocabulary, your work patterns. Every session, you re-explain context.
On-device AI can maintain persistent, private context. ARKANA builds a personal intelligence layer that learns your patterns over time — your coding style, your writing voice, your domain knowledge. This context never leaves your device, creating an AI that gets more useful the longer you use it.
We're approaching a tipping point where on-device AI isn't just a privacy choice — it's the superior experience.
The Future is Local
The trend is clear: model sizes are shrinking while capability is growing. Quantisation techniques like 4-bit precision make powerful models fit in 4-8GB of RAM. Apple's MLX framework is purpose-built for efficient local inference. Every new generation of Apple Silicon is faster at AI workloads.
We're approaching a tipping point where on-device AI isn't just a privacy choice — it's the superior experience. Faster, more personal, and fully under your control.