In this episode of the Restaurant AI Podcast, host Matt Wampler, Co-Founder and CEO of ClearCOGS, sits down with Aaron Knape, Chief Revenue Officer at Amniscient, to unpack one of the most talked-about but least understood areas of AI: computer vision.

While most AI conversations today focus on voice and text, Aaron explains why computer vision is different, and why it may be the missing layer that allows AI to finally understand the physical world. From grocery stores and restaurants to manufacturing and security, computer vision gives AI eyes, context, and ground truth data that language models alone can’t provide.

Aaron breaks down what computer vision actually is, why it’s historically been so expensive and slow to adopt, and what’s finally changing. The conversation explores real-world use cases like self-checkout, inventory tracking, quality control, and operational visibility, along with the harder questions around privacy, data ownership, liability, and regulation.

They also dive into the convergence of LLMs + computer vision, edge vs cloud processing, the future of robotics, deepfakes, and why adoption isn’t just a technology problem, it’s an education and implementation problem.
Episode Links:

Chapters + Timestamps
00:00 Intro & Coming Up
02:51 What Computer Vision Actually Is
04:15 CAPTCHA & Training AI
04:58 Why Computer Vision Stayed in Infancy
06:56 The “Autocomplete on Steroids” Moment
09:36 LLMs + Computer Vision: Giving AI Eyes
11:35 Why Video Hasn’t Delivered ROI Yet
13:17 Self-Checkout & Retail Use Cases
16:43 The SKU & Packaging Problem
19:35 Aaron’s Journey into Computer Vision
22:50 Cameras, 4K & Hardware Evolution
24:45 Edge vs Cloud Computing
29:47 Privacy, Data Ownership & Liability
35:00 Deepfakes & Regulation
41:58 The Risk of Too Much Visibility
46:18 AI, Education & The Next Generation
52:21 Where Computer Vision Is Headed
1:15:19 Final Thoughts & Where to Find Aaron