Problems & Solutions
Problems and Solutions
Problem #1: Centralized Cloud Monopolies
Centralized cloud providers dominate the compute market, leading to high costs, opaque pricing, and vulnerability to outages and censorship. Planck’s Solution:
A decentralized GPU network offering up to 90% lower costs, transparent pricing, and composable access to bare-metal infrastructure.
Problem #2: Lack of AI-Native Infrastructure
Traditional blockchains are not optimized for AI workloads, lacking GPU integration, parallelism, or compute orchestration. Planck’s Solution:
Planck₁ provides on-chain GPU scheduling, compute payments, and orchestration primitives purpose-built for AI.
Problem #3: Bottlenecks in Model Training & Inference
Training large models or running inference pipelines is slow and expensive on centralized infrastructure. Planck’s Solution:
Spin up H100/H200 GPU clusters instantly using GPU Console, with elastic scaling and distributed compute support.
Problem #4: Limited Sovereignty for AI and DePIN Apps
Emerging AI and infrastructure protocols lack sovereignty and composability when built on legacy L1s. Planck’s Solution:
Planck₀ allows launching sovereign AI chains and DePIN L1s with shared security, rollup SDKs, and interoperability tooling.
Problem #5: Fragmented Tooling for Developers
Developers must cobble together fragmented tools for training, deploying, and coordinating AI systems. Planck’s Solution:
Planck’s unified stack includes AI Studio for model development, Planck₁ for execution, and GPU Console for infrastructure—all composable on-chain.
Problem #6: Regulatory and Enterprise Adoption Barriers
Enterprises require certification, reliability, and uptime guarantees that most decentralized networks lack. Planck’s Solution:
Enterprise-grade SLAs, Tier 3/4 facilities, and upcoming industry-standard certifications through Rollman Group partnerships.
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