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.