AI & Machine Learning

Review of Attention (Vision Models) – Part 3

In the previous article, we reviewed several approaches to applying attention to vision models. We will continue our discussion, present a few additional vision models approaches in this article, and discuss their advantages over traditional approaches. Stand-Alone Self Attention Ramachandran et al. 2019 proposed an attention mechanism like the 2-D attention in Image Transformer [1].

Review of Attention (Vision Models) – Part 2

 Attention in Vision Models: In the previous article, we briefly discussed the concept of attention and its application in the language domain. In this article, we will discuss some of the works that have applied attention in visual models tasks. Although vision models have traditionally used Convolution Networks (ConvNet) as the standard for image encoders,

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Attention Mechanisms

Review of Attention – 1

Attention mechanisms have greatly helped accelerate the progress in deep learning [1] [2]. Although initially developed for language, Attention has become a popular technique in several domains such as Vision and RL. In this series of articles, we will briefly review the concept of attention and discuss some of the works that have applied attention

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  • Closing The Responsible AI Gap

    This blog post is the first in a series of Perspectives in Responsible AI. We present a framework that lays out a series of steps to operationalize Responsible AI. We discuss the challenges at each stage and how to progress to the next one. In our first issue, we’ll present an overview of the framework

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    How Can Augmented Reality Deliver Impactful Communications?

    The era of flat content seems to be over now because of the emergence of immersive technologies such as Augmented Reality (AR), Virtual Reality (VR) and 3D visuals. We have already entered a new technological era where content increasingly tends to be dynamic. Just like the dynamic content created through these immersive visuals, customer communication

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    How AI And The IoT Are Advancing The Non-Destructive Testing Space

    Non-destructive testing (NDT) is an essential part of many quality control processes. NDT can be time-consuming, however. And, certain tasks — like visual inspection of a product or component for defects — have proven difficult to automate in many cases. Artificial Intelligence (AI) is changing this. With enough data, it’s often possible to automate a

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    Here’s Why The Robots Won’t Really Take Over

    If robots are truly taking over, then why are having trouble finding enough humans to do work that needs being done? The truth is that automation doesn’t replace jobs, it replaces tasks and when tasks become automated, they largely become commoditized. So while there are significant causes for concern about automation, such as increasing returns to capital amid decreasing returns to labor, the real danger isn’t with automation itself, but what we choose to do with it.

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