The Future of Computer Vision and Video Intelligence: Insights from Kimberly Tan

The Future of Computer Vision and Video Intelligence: Insights from Kimberly Tan

‘I think leveraging insights from video data has become pretty commonplace in the enterprise to help companies make better-informed business decisions, but this capability could be even more powerful in the real world given how rich and comprehensive the nature of the available data is.’ – Kimberly Tan

In this insightful discussion, Kimberly Tan, a partner at a16z, explores the potential of computer vision and video intelligence in various industries by 2024.

She delves into how companies could provide both hardware and software to customers, tailor-made to their specific needs.

Table of Contents

  1. The Hardware-Software Model
  2. Unlocking Video Data Potential
  3. Contributing Factors for Efficient Use of Video Data
  4. Applications Across Sectors
  5. Addressing Privacy Concerns
  6. 2024: A Tipping Point?
  7. The Rise of AI in Traditional Industries
  8. AI Beyond Creative Fields
  9. Influence of Successful Companies
  10. Maritime Exploration via AI
  11. Never-Ending AI-First Games
  12. Rise of Voice-First Apps

The Hardware-Software Model

A rising trend in businesses is the adoption of a hardware-software model where both video cameras (hardware) and data interpretation software are sold to customers.

This approach is customized to suit specific customer requirements.

‘I would say there’s a amount of video data that is being captured just given the general prevalence of cameras either on smartphones or just um in a lot of places that we live our day-to-day lives and I think the real question is how much of that data is actually being captured and utilized in some interesting way versus just you know passively existing on different devices and not actually being analyzed or processed in any way.’ – Kimberly Tan

Unlocking Video Data Potential

Despite an abundance of video data captured through smartphones and other devices, its potential remains largely untapped.

The key lies in advancing hardware and software capabilities to make meaningful use of this data.

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