PH Deck

Users creating GPU shaders for spatial computing face challenges with traditional coding environments that lack real-time feedback and integration with mixed reality features.

Users need to measure GPU performance using traditional methods that require installation or lack real-time data. require installation or lack real-time data

The current situation of users involves manually tracking their earnings over time or relying on traditional financial tracking systems. Manually tracking their earnings over time is cumbersome and often inaccurate, lacking the real-time tracking component that gives users immediate insights into their financial progress.

Users manually calculate their income per second based on monthly salary, which is time-consuming and lacks real-time visibility into earnings during work hours.

Users need to create spatial videos and photo slideshows but rely on fragmented tools for 2D-to-3D conversion and editing, which require multiple software, lack on-device privacy, and produce less immersive content.

Users currently rely on manual checks or basic tools for monitoring NVIDIA GPU servers, leading to slow update intervals (e.g., minutes) and complex infrastructure setup

Job seekers practice interviews alone or with non-professional peers, leading to missed improvement areas and inconsistent feedback

Call center agents struggle to handle calls efficiently and to provide accurate information to the customers, resulting in long call times and decreased customer satisfaction.

Developers building CUDA applications use traditional code editors without integrated GPU profiling and AI optimization tools, leading to manual debugging, slower performance tuning, and inefficient resource utilization.

Users face language barriers when communicating in real-time with people who speak different languages

Current solutions lack real-time translation capabilities, leading to miscommunication and misunderstandings