In the rapidly evolving landscape of artificial intelligence (AI), two distinct paradigms have emerged: ScreenAI and Dimensional AI. While ScreenAI focuses on enhancing productivity and screen-based interactions, Dimensional AI is paving the way for transformative advancements across various industries, ranging from healthcare and agriculture to transportation and manufacturing. In this blog, we explore the fundamental differences between ScreenAI and Dimensional AI, the risks and rewards associated with building startups in these areas, and the key requirements for successfully establishing Dimensional AI startups.
A. What is ScreenAI vs Dimensional AI ?
ScreenAI primarily encompasses applications and tools that facilitate 2D interactions on screens. Examples include productivity software, video editing tools, chat-based AI models, and dashboard applications. These solutions rely on data primarily sourced from the shallow web and contribute to improving screen-based productivity. The focus of ScreenAI lies in training pre-existing models and optimizing inference. Interactions and outputs are typically text-based or presented through screen interfaces.
On the other hand, Dimensional AI is dedicated to harnessing AI’s potential in sectors like healthcare, agriculture, transportation, and manufacturing. These applications transcend the limitations of 2D screens and employ AI to address real-world challenges. Examples of Dimensional AI include AI doctors, smart cities that predict and prevent problems like crime and pollution, technologies for eliminating disabilities, and assisting professionals in their respective fields. The data utilized in Dimensional AI originates from various sources such as sensors, satellites, human interactions (e.g., through VR/AR devices), and enterprise data. Analyzing this data requires not only training large foundation models but also customizing them for real-world scenarios, incorporating elements of reinforcement learning and personalization. Dimensional AI’s outputs and interactions extend beyond text and screens, incorporating rich multimodal interfaces like audio, visual overlays, and AR/VR technologies.
B. The Risk and Reward of Building Startups in ScreenAI and Dimensional AI:
ScreenAI startups offer relative ease of development as they can leverage existing APIs from major players or modify existing software approaches. However, these startups often operate as features rather than distinct products. Consequently, they face a higher risk of disruption when larger companies launch similar features or create plugins to connect with various services. The constantly evolving nature of ScreenAI solutions demands continuous innovation to remain competitive in the market.
In contrast, Dimensional AI startups face greater challenges due to the need for domain expertise, coordination within larger ecosystems, and multidimensional software development. Nevertheless, these startups have the potential to establish strong market positions by creating unique value propositions, capturing higher value, and becoming iconic companies in their respective domains. The complexity involved in building Dimensional AI solutions acts as a barrier to entry for competitors, offering a level of protection and creating a moat around the startup.
