PH Deck

The current situation for AI developers involves sourcing expensive and sometimes unreliable computing power to run AI models. Current approaches often depend on centralized data centers with limited scalability.

Drawbacks of this old situation include: finding affordable computing power, scalability issues, and security concerns.

Users need to gather news from multiple platforms and manually filter content, which is time-consuming manual filtering and limited language options for global audiences.

Users aiming to launch an AI tools marketplace face high development costs, technical complexity, and long timelines when building from scratch.

Industries manage energy, water, and emissions with manual processes or fragmented tools, leading to high operational costs, inefficient resource allocation, and slow progress toward net-zero goals.

Users manually search GitHub with complex queries/filters to find developers, leading to time-consuming, inefficient discovery of relevant talent.

Developers integrate AI features manually from scratch, facing extra infrastructure and effort to build and maintain AI-powered app components.

Users manage real-world assets through traditional methods involving manual processes, intermediaries, and fragmented systems, leading to low liquidity, high transaction costs, and limited accessibility to global investors.

Users struggle to utilize AI models, integrate knowledge bases, and simplify tasks without expertise

Users face outdated corporate and academic training methods that are often not engaging and lack personalization for different learning styles.

Lack of engagement and tailored content leads to less effective learning experiences.

Users struggle with understanding complex texts and retaining information through traditional reading methods. The drawbacks include manual note-taking, fragmented summarization tools, and lack of real-time contextual insights.