Amazon Science: R&D projects to Inspire Your Next Project

Amazon Science

Your business might be planning an R&D project in the future. It might be to design a new product or service, or innovate on something that’s already there. Either way, there’s one place to easily find some inspiration for your next project: Amazon Science.

Dollar for dollar, no one spends more on research and development than Amazon. Every year they dedicate more and more of their budget to it. In 2021, they spent over $56 Billion (Yes, billions with a b) on R&D. That’s a 31.15% increase from the previous year.

The projects found on Amazon Science include innovations in machine learning, Artificial Intelligence, Sustainability, operation optimization, and more. So, let’s take a look at some of them and see if we can’t inspire your next R&D project!

Subjective influence of camera-gaze angular offset

This first study was conducted to evaluate the difficulty in maintaining eye contact during a teleconference due to misalignment between the centre of the screen and the camera.

“The effect of camera-gaze angular offset was quantified by assessing Effectiveness and Engagement ratings. It was shown that even 10 degrees of misalignment cause a statistically significant drop in Effectiveness for business-type teleconference calls. Camera-gaze angular offset is an important parameter to be considered during video conferencing equipment design or setup. Higher misalignment may cause significant drops in perceived call quality (Quality of Experience).”

So, what’s the practical upside? The results of this study can be used in conferencing equipment design and setup, modern telecommunication equipment design, workplace ergonomics, or distance learning equipment setup.

Go green: A decision-tree framework to select optimal box-sizes for product shipments

This study made advances in both sustainability and reducing overall shipping costs.

Since creating a unique box for every single product isn’t practical, Amazon found a process companies can use to find the right number of boxes to manufacture and what their dimensions should be.

“By just modifying the existing box dimensions and not even adding a new size variant, we achieved a reduction of 4.4% in the shipment volume, contributing to the decrease in non-utilized, air volume space by 2.2%. The reduction in shipment volume and air volume improved significantly to 10.3% and 6.1% when we introduced 4 additional boxes.”

Profiling deep learning workloads at scale using Amazon SageMaker

Part of the larger machine learning family, Deep Learning is based on artificial neural networks. The cost of conducting deep learning has roughly doubled every single year since 2012. Due to this, Amazon conducted a study on a way to implement a new technology into their own SageMaker machine learning program.

“The tool supports profiling DL models at scale, identifies performance bottlenecks, and provides insights with recommendations. We deployed the profiling functionality as an add-on to Amazon SageMaker Debugger, a fully-managed service that leverages an on-the-fly analysis system (called rules) to automatically identify complex issues in DL training jobs.”

For companies that use SageMaker, this innovation led to a reduction in training time and cost.

Conducting your own research and development

When it comes to your own R&D projects, there are two things you can do.

First, keep exploring more Amazon Science projects to see just how many applications and benefits can come from these projects.

Second, and most importantly, make sure you’re benefiting from the Scientific Research and Experimental Development tax incentives offered by the Government of Canada.

If you need some help, that’s why Maxim Innovation is here.

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