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For technical people: GS is an end-to-end development environment for building AI and machine learning systems. It can do anything frameworks can do (like tensorflow or pytorch) but with infinitely less friction.
For non-technical people: GS allows people to build AI and machine learning systems visually, instead of using code.
Additionally:
- The primary goal for GS is to be an answer to the question: "What is the best way to build AI?"
- It hopes to simplify, without oversimplifying and be as flexible and useful as code.
- Code is the wrong medium for building AI/ML systems. Code is high-friction when building, modifying, and communicating.
- The democratization of building and understanding AI/ML is extremely important. Lowering the barrier-to-entry and opening up the AI 'black box' is crucial for a good outcome for humanity.
- Current codeless building tools are extremely rigid, resulting in oversimplifying and blocking off parts of the system which could be central to the user's problem space. These platforms are codeless for the sake of being codeless and ultimately don't add value beyond what developers already use.
- Generating code is great for building quickly, but it's inherently more time consuming to understand than writing the code yourself. GS shows what's built visually, giving the user's a comprehensive and clear view of the system. GS will soon incorporate an LLM agent for helping users build systems within the platform - allowing them to build anything while also giving them the ability to understand quickly.
- Depending on a user's problem space, they might find it imperative to have full flexibility and the ability to modify both the low-level and high-level. Some might stay at the same-level of abstraction, but dive deeper for debugging purposes. Some might only work with high-level components, and never go deeper.
- When learning, it's necessary for building a full understanding.