Video · Matthew Berman ·

Who is local AI really for?

Matthew Berman argues that local AI 'makes no sense' for the average person right now, claiming it is expensive, hard to set up, and inferior to frontier models like ChatGPT and Claude. He distinguishes local AI—running a model on your own device so it works offline—from open-source/open-weights AI, where labs release models freely and companies such as AWS, Google, and the neoclouds serve them from data centers. He notes the best open-weights models sit a generation behind the frontier and are too large to run on consumer or even professional hardware without racks of GPUs costing hundreds of thousands to millions of dollars. He explains why he wants local AI to succeed: data sovereignty, protection from AI labs cutting off access (citing Anthropic restricting Claude use with OpenClaude), and—especially for enterprises—these same benefits. He promises to walk through the math on whether local AI makes financial sense today and to sketch a future vision for it.

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