The objective of the recognition pattern of AI is to have machines identify and understand the real world and unstructured data. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define and discuss at a high level the terms Recognition Systems, Computer Vision, and ImageNet, how they are related, and why it’s important to have a light level understanding of these terms.
Adding intelligence to automation enables greater degrees of variability and unpredictability. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss what it means to have Level 1 automation to handle variability and unpredictability, how to incorporate NLP and computer vision to help handle tasks with unstructured data, some of …
AI Today Podcast: Automation Roadmap Series: Advancing to Level 1 Intelligent Automation Read More »
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Matt Chambers, Principal Architect & Juan Buhler, Sr. Data Science Engineer at Boon AI. They share with us some challenges they see organizations face today with trying to make sense of their unstructured data, especially video data, as it relates …
In this bonus episode of the AI Today podcast we interview Aniket Bera, Assistant Research Professor in Computer Science at University of Maryland GAMMA lab to get his insights into the robotics industry, why some companies fail and others succeed, and where he sees the future of robotics heading. Show Notes: AI Today Podcast with …
Machine learning is great at identifying and understanding the real world and unstructured data. ML can identify and understand images, sound, items, handwriting, faces, and gestures. In this podcast hosts Kathleen Walch and Ron Schmelzer discuss various use cases in the recognition pattern on AI. Show Notes: Recognition & Computer Vision Workshop & Certification CPMAI …
AI Today Podcast #90: Understanding The Recognition Pattern of AI Read More »
Cognilytica has spent a considerable amount of time on AI use cases and how different industries are using various AI and cognitive technologies and we’ve found that there are seven common patterns that seem to continuously show up in all these use cases. Some use cases use a single pattern for their application while others …
Artificial Intelligence and machine learning has matured considerably over the past few years. We can now find AI projects in every industry and across every potential application and project type. In our AI vendor classification matrix, we identified over 3000 vendor companies across over 100 subsegments of the AI market implementing a wide range of …
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