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Some people truly believe AI is still a delusion and assume it's hype that will fade away. We explore four categories of AI skeptics and what they're getting wrong. Technologists argue LLMs aren't sufficient to achieve AGI because we're training them on the entire internet and YouTube, yet they still make basic mistakes about the world. About 60% of people think AI simply retrieves from a database and don't understand hallucination as a possibility. Economic naysayers ask why AI hasn't shown up in productivity numbers yet with 10% economic growth. AI Luddites believe it only degrades quality of life after one bad experience. ChatGPT reported 800 million weekly users, meaning one out of six people are using generative AI in their daily workflows. This is no longer a niche experiment but incorporated into daily life. Adoption is not directly equal to trust though. The demand is changing towards people wanting evidence, controls, and more guardrails themselves because skepticism isn't going anywhere. Consumers ask simple YouTube style questions that now get served as AI summaries in Google search results. Local 4 billion parameter models can run on your iPhone and tell you how to boil an egg. The convenience usage of AI and basic productivity tasks are with us for good. Are you one of the 60% who still thinks AI is just a fancy database? -------------------------------------------------------------------------------------------------------------------------- About Ambient.xyz: Ambient is an SVM-compatible Proof of Work Layer 1 that pairs Solana-style execution with a new consensus mechanism called Proof of Logits (PoL). The goal is simple but non-negotiable: deliver fast, cheap, verified AI inference at scale, and do it in a way developers can integrate into on-chain, cross-chain, and web2 applications. Ambient’s design centers on one large network model (600B+ parameters) and its fine-tunes, so miners optimize for utilization instead of wasting cycles across fragmented “model marketplaces.” The project positions verified inference as infrastructure: low overhead verification, high throughput, and a path toward open, transparent training over time. —------------------------------------------------------------------------------------ About Travis Good: Travis Godwin Good, PhD is the CEO and Co-founder of Ambient.xyz. His public writing and research focuses on trustworthy AI infrastructure, verification vs. “truth,” incentives that degrade model quality, and why agentic systems need auditability down to execution rather than vibes and benchmark screenshots. —------------------------------------------------------------------------------------ Key words: verified inference, Proof of Logits, useful PoW, SVM, Solana-style dApps, agentic economy, on-chain AI, open weights, audit trails, model provenance, censorship resistance, privacy-preserving compute, miner economics, decentralized training, Travis Good Ambient, verifiable inference