Autonomous, Responsive, and Collaborative
- The Artificial Intelligence of Things (AIoT) integrates the pervasive sensing and connectivity of IoT with the decision-making power of AI. The latter transforms sensing into understanding, while former’s interconnectivity and interoperability facilitate the scaling, coordination, and collaboration of autonomous systems. At the edge, light-weight and real-time inference enables faster responsiveness, while cloud platforms provide large-scale learning and global knowledge.
Foundational, Multimodal, and Reasoning
- This decade has seen the emergence of foundation models in the cloud (e.g. OpenAI GPT, Gemini, Claude) which have reshaped how AI is delivered and used. Unlike earlier task-specific AI models, foundation models are trained on broad, diverse datasets at massive scale — gaining general and emergent capabilities. For example, Large Language Models (LLMs) exhibit capabilities such as writing, summarizing, translating, coding, reasoning, etc. Increasingly, foundational models are becoming multimodal, spanning natural language, vision, audio, and even action (for robotics and embodied AI).
- Chat interfaces (web, mobile app, and voice) brought foundation models to the general public, making products like ChatGPT explode in popularity. Nevertheless, these foundation models are also accessible as-a-Service via an Application Programming Interface (API). As a maker/engineer, accelerate your AI innovation journey by taking advantage of cloud AI APIs for complex problem-solving, logical reasoning, and multimodal capabilities.
