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A set of 26 predictions for how AI, geopolitics, and emerging technologies will evolve in 2026.

As AI architectures shift from brute-force scaling to elegant efficiency, value will migrate from compute power to trust infrastructure, and crypto holds the key to verification in an age of abundant intelligence.

AI will catalyze a shift from viewing minds as mystical phenomena to treating them as executable, self-organizing control processes, reframing consciousness as a functional coherence mechanism rather than an enigma and positioning machine minds as an inevitable extension of biological ones.

Leaders from Ambient, Gensyn, Nous Research, and NEAR AI argue decentralized AI can overcome centralized bias and platform risk through crypto-economic incentives: tokens align global contributors, burn with inference demand, and enable user-owned models.

The US-China AI race pits capital-driven frontier research against state-coordinated diffusion, with America excelling at breakthrough innovation while China leads in open-source deployment and manufacturing scale: two complementary approaches that may both be necessary to navigate AI's risks.

VCs debate whether venture remains viable amid AI's transformation: talent and capital consolidate at major labs paying $10M+ salaries, open-source lags despite philosophical appeal, and the power law intensifies. 95% of funds may fail while trillion-dollar outcomes become possible for the first time in history.

AI agents will shift the economy from capturing attention to fulfilling intention, slashing transaction costs and moving work from in-house teams to competitive agent markets.

The race to automate human labor
Intelligence is massively parallel tree search guided by memory and logic. From evolution's glacial updates to humanity's network-speed learning, we trace how the speed of belief updates determines intelligence levels — and why AGI will emerge from millions of specialized agents, not a single superintelligence.
