Vision

While LLMs changed the world with text, Multi-modal AI is changing how we interact with the physical world. In 2026, we’ve moved past “GPT-4o style” multimodal inputs toward deep, integrated reasoning across vision, voice, and even spatial data. Developers are no longer just building chatbots; they are building “Vision-Native” and “Voice-First” applications that understand context as humans do. The Shift to Multi-modal Reasoning In the early 2020s, multi-modal was often a series of “converters”—speech-to-text, then text-to-LLM, then text-to-speech. Today, we use single models with unified token spaces. This reduces latency and, more importantly, preserves the nuance lost in transcription. ...