Today’s “cloud” is concentrated in a handful of mega data centers. Acurast is flipping that model by turning smartphones into a confidential, verifiable compute network—made for Web3 and AI. Founder Dr. Christian Killer explains how they verify hardware, encrypt workloads end-to-end, and deliver trust-minimized compute for price feeds, bridging, LLM inference, web scraping, residential proxy/VPN, and even distributed agent indexing (MIT NANDA).

Timestamps

• [00:00 ] Intro & the problem: compute is centralized in ~5 companies

• [00:02 ] Christian’s path (gaming → Bitcoin Lightning NFC → Web3 infra)

• [00:04 ] Why decentralize compute? Cost, control, and data misuse risk

• [00:05 ] Phones vs servers: performance-per-watt, economics, upcycling

• [00:07 ] The hard bit: verifying hardware + trusted execution environments

• [00:08 ] How Acurast works (supply/demand, encrypted jobs, scheduling)

• [00:09 ] Web3 demand: price feeds & bridging done trust-minimized

• [00:10 ] Web2 demand: scraping + residential IP/VPN for AI startups

• [00:11 ] AI focus: inference today, confidential LLMs, agent guardrails

• [00:13 ] “Agentic AI” hype vs practice—what actually matters

• [00:16 ] Distributed agent indexing (MIT NANDA) explained simply

• [00:18 ] What most people miss about LLMs (probabilistic behavior)

• [00:20 ] Quantum computing: progress, hype, and reality

• [00:21 ] Biggest technical challenges ahead (clustering, MPC, DKG)

• [00:24 ] Moore’s Law → performance per watt (phones keep winning)

• [00:25 ] DePIN’s real challenge: organic demand & dev UX

• [00:27 ] North star metrics & real adoption vs spam

• [00:28 ] Roadmap: Cargo (containers), clustering, futures for compute

• [00:30 ] The ask: strategic partners & builders; grants/hackathons coming
  

Connect

https://acurast.com/

https://x.com/acurast

https://x.com/killercsecurity

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